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description Publicationkeyboard_double_arrow_right Article 2010Publisher:Wiley Kenny, Helsens; Niklaas, Colaert; Harald, Barsnes; Thilo, Muth; Kristian, Flikka; An, Staes; Evy, Timmerman; Steffi, Wortelkamp; Albert, Sickmann; Joël, Vandekerckhove; Kris, Gevaert; Lennart, Martens;pmid: 20058248
AbstractMS‐based proteomics produces large amounts of mass spectra that require processing, identification and possibly quantification before interpretation can be undertaken. High‐throughput studies require automation of these various steps, and management of the data in association with the results obtained. We here present ms_lims (http://genesis.UGent.be/ms_lims), a freely available, open‐source system based on a central database to automate data management and processing in MS‐driven proteomics analyses.
PROTEOMICS arrow_drop_down PROTEOMICSArticle . 2010 . Peer-reviewedLicense: Wiley Online Library User AgreementData sources: Crossrefadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1002/pmic.200900409&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess Routesbronze 78 citations 78 popularity Top 10% influence Top 10% impulse Top 1% Powered by BIP!more_vert PROTEOMICS arrow_drop_down PROTEOMICSArticle . 2010 . Peer-reviewedLicense: Wiley Online Library User AgreementData sources: Crossrefadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1002/pmic.200900409&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2019 NorwayPublisher:Springer Science and Business Media LLC Funded by:WT | Development and applicati..., WTWT| Development and application of statistical methodology for the detection and characterisation of genetic factors in complex disease. ,WTAuthors: Miriam Gjerdevik; Astanand Jugessur; Øystein Ariansen Haaland; Julia Romanowska; +3 AuthorsMiriam Gjerdevik; Astanand Jugessur; Øystein Ariansen Haaland; Julia Romanowska; Rolv T. Lie; Heather J. Cordell; Håkon K. Gjessing;Background Log-linear and multinomial modeling offer a flexible framework for genetic association analyses of offspring (child), parent-of-origin and maternal effects, based on genotype data from a variety of child-parent configurations. Although the calculation of statistical power or sample size is an important first step in the planning of any scientific study, there is currently a lack of software for genetic power calculations in family-based study designs. Here, we address this shortcoming through new implementations of power calculations in the R package Haplin, which is a flexible and robust software for genetic epidemiological analyses. Power calculations in Haplin can be performed analytically using the asymptotic variance-covariance structure of the parameter estimator, or else by a straightforward simulation approach. Haplin performs power calculations for child, parent-of-origin and maternal effects, as well as for gene-environment interactions. The power can be calculated for both single SNPs and haplotypes, either autosomal or X-linked. Moreover, Haplin enables power calculations for different child-parent configurations, including (but not limited to) case-parent triads, case-mother dyads, and case-parent triads in combination with unrelated control-parent triads. Results We compared the asymptotic power approximations to the power of analysis attained with Haplin. For external validation, the results were further compared to the power of analysis attained by the EMIM software using data simulations from Haplin. Consistency observed between Haplin and EMIM across various genetic scenarios confirms the computational accuracy of the inference methods used in both programs. The results also demonstrate that power calculations in Haplin are applicable to genetic association studies using either log-linear or multinomial modeling approaches. Conclusions Haplin provides a robust and reliable framework for power calculations in genetic association analyses for a wide range of genetic effects and etiologic scenarios, based on genotype data from a variety of child-parent configurations. Electronic supplementary material The online version of this article (10.1186/s12859-019-2727-3) contains supplementary material, which is available to authorized users.
Europe PubMed Centra... arrow_drop_down Europe PubMed CentralArticle . 2019Full-Text: http://europepmc.org/articles/PMC6444579Data sources: PubMed CentralNorwegian Institute of Public Health Open RepositoryArticle . 2019Data sources: Norwegian Institute of Public Health Open RepositoryBergen Open Research Archive - UiBArticle . 2019 . Peer-reviewedLicense: CC BYData sources: Bergen Open Research Archive - UiBNorwegian Institute of Public Health Open RepositoryArticle . 2019Data sources: Norwegian Institute of Public Health Open Repositoryadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.euAccess RoutesGreen gold 12 citations 12 popularity Top 10% influence Average impulse Top 10% Powered by BIP!more_vert Europe PubMed Centra... arrow_drop_down Europe PubMed CentralArticle . 2019Full-Text: http://europepmc.org/articles/PMC6444579Data sources: PubMed CentralNorwegian Institute of Public Health Open RepositoryArticle . 2019Data sources: Norwegian Institute of Public Health Open RepositoryBergen Open Research Archive - UiBArticle . 2019 . Peer-reviewedLicense: CC BYData sources: Bergen Open Research Archive - UiBNorwegian Institute of Public Health Open RepositoryArticle . 2019Data sources: Norwegian Institute of Public Health Open Repositoryadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1186/s12859-019-2727-3&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2009 NorwayPublisher:Oxford University Press (OUP) Funded by:EC | DTSSCP, CIHREC| DTSSCP ,CIHRPortales-Casamar, E.; Thongjuea, S.; Kwon, A. T.; Arenillas, D.; Zhao, X.; Valen, E.; Yusuf, D.; Lenhard, B.; Wasserman, W. W.; Sandelin, A.;JASPAR (http://jaspar.genereg.net) is the leading open-access database of matrix profiles describing the DNA-binding patterns of transcription factors (TFs) and other proteins interacting with DNA in a sequence-specific manner. Its fourth major release is the largest expansion of the core database to date: the database now holds 457 non-redundant, curated profiles. The new entries include the first batch of profiles derived from ChIP-seq and ChIPchip whole-genome binding experiments, and 177 yeast TF binding profiles. The introduction of a yeast division brings the convenience of JASPAR to an active research community. As binding models are refined by newer data, the JASPAR database now uses versioning of matrices: in this release, 12% of the older models were updated to improved versions. Classification of TF families has been improved by adopting a new DNA-binding domain nomenclature. A curated catalog of mammalian TFs is provided, extending the use of the JASPAR profiles to additional TFs belonging to the same structural family. The changes in the database set the system ready for more rapid acquisition of new high-throughput data sources. Additionally, three new special collections provide matrix profile data produced by recent alternative high-throughput approaches. publishedVersion
Europe PubMed Centra... arrow_drop_down Europe PubMed CentralArticle . 2009Full-Text: http://europepmc.org/articles/PMC2808906Data sources: PubMed CentralBergen Open Research Archive - UiBArticle . 2010 . Peer-reviewedData sources: Bergen Open Research Archive - UiBadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1093/nar/gkp950&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen gold 560 citations 560 popularity Top 0.1% influence Top 1% impulse Top 0.1% Powered by BIP!more_vert Europe PubMed Centra... arrow_drop_down Europe PubMed CentralArticle . 2009Full-Text: http://europepmc.org/articles/PMC2808906Data sources: PubMed CentralBergen Open Research Archive - UiBArticle . 2010 . Peer-reviewedData sources: Bergen Open Research Archive - UiBadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1093/nar/gkp950&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Preprint 2019Publisher:Cold Spring Harbor Laboratory Funded by:WT | PRIDE Atlas., NIH | Development of Trans Prot..., NIH | Identification of synapti... +4 projectsWT| PRIDE Atlas. ,NIH| Development of Trans Proteomic Pipeline, an Analysis Suite for Mass Spectrometry ,NIH| Identification of synaptic gene sets for CNS synapse taxonomy and antibodies for their engagement ,NIH| Big Data for Discovery Science ,WT| The PRIDE database: A proteomics data hub in the life sciences ,NIH| Consortium to Study the Genetics of Longevity ,NIH| Advancing data and metadata standards for proteomics mass spectraPierre-Alain Binz; Jim Shofstahl; Juan Antonio Vizcaíno; Harald Barsnes; Robert J. Chalkley; Gerben Menschaert; Emanuele Alpi; Karl R. Clauser; Jimmy K. Eng; Lydie Lane; Sean L. Seymour; Luis Francisco Hernández Sánchez; Gerhard Mayer; Martin Eisenacher; Yasset Perez-Riverol; Eugene A. Kapp; Luis Mendoza; Peter R. Baker; Andrew Collins; Tim Van Den Bossche; Eric W. Deutsch;doi: 10.1101/624494
AbstractMass spectrometry-based proteomics enables the high-throughput identification and quantification of proteins, including sequence variants and post-translational modifications (PTMs), in biological samples. However, most workflows require that such variations be included in the search space used to analyze the data, and doing so remains challenging with most analysis tools. In order to facilitate the search for known sequence variants and PTMs, the Proteomics Standards Initiative (PSI) has designed and implemented the PSI Extended FASTA Format (PEFF). PEFF is based on the very popular FASTA format but adds a uniform mechanism for encoding substantially more metadata about the sequence collection as well as individual entries, including support for encoding known sequence variants, PTMs, and proteoforms. The format is very nearly backwards compatible, and as such, existing FASTA parsers will require little or no changes to be able to read PEFF files as FASTA files, although without supporting any of the extra capabilities of PEFF. PEFF is defined by a full specification document, controlled vocabulary terms, a set of example files, software libraries, and a file validator. Popular software and resources are starting to support PEFF, including the sequence search engine Comet and the knowledge bases neXtProt and UniProtKB. Widespread implementation of PEFF is expected to further enable proteogenomics and top-down proteomics applications by providing a standardized mechanism for encoding protein sequences and their known variations. All the related documentation, including the detailed file format specification and example files, are available athttp://www.psidev.info/peff.
add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1101/624494&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu1 citations 1 popularity Average influence Average impulse Average Powered by BIP!more_vert add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1101/624494&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2013 NorwayPublisher:Springer Science and Business Media LLC Authors: Klepper, Kjetil; Drabløs, Finn;Klepper, Kjetil; Drabløs, Finn;Background: Traditional methods for computational motif discovery often suffer from poor performance. In particular, methods that search for sequence matches to known binding motifs tend to predict many non-functional binding sites because they fail to take into consideration the biological state of the cell. In recent years, genome-wide studies have generated a lot of data that has the potential to improve our ability to identify functional motifs and binding sites, such as information about chromatin accessibility and epigenetic states in different cell types. However, it is not always trivial to make use of this data in combination with existing motif discovery tools, especially for researchers who are not skilled in bioinformatics programming. Results: Here we present MotifLab, a general workbench for analysing regulatory sequence regions and discovering transcription factor binding sites and cis-regulatory modules. MotifLab supports comprehensive motif discovery and analysis by allowing users to integrate several popular motif discovery tools as well as different kinds of additional information, including phylogenetic conservation, epigenetic marks, DNase hypersensitive sites, ChIP-Seq data, positional binding preferences of transcription factors, transcription factor interactions and gene expression. MotifLab offers several data-processing operations that can be used to create, manipulate and analyse data objects, and complete analysis workflows can be constructed and automatically executed within MotifLab, including graphical presentation of the results. Conclusions: We have developed MotifLab as a flexible workbench for motif analysis in a genomic context. The flexibility and effectiveness of this workbench has been demonstrated on selected test cases, in particular two previously published benchmark data sets for single motifs and modules, and a realistic example of genes responding to treatment with forskolin. MotifLab is freely available at http://www.motiflab.org. © 2013 Klepper and Drabløs; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Europe PubMed Centra... arrow_drop_down Europe PubMed CentralArticle . 2013Full-Text: http://europepmc.org/articles/PMC3556059Data sources: PubMed Centraladd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1186/1471-2105-14-9&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen gold 34 citations 34 popularity Average influence Average impulse Top 10% Powered by BIP!more_vert Europe PubMed Centra... arrow_drop_down Europe PubMed CentralArticle . 2013Full-Text: http://europepmc.org/articles/PMC3556059Data sources: PubMed Centraladd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1186/1471-2105-14-9&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2010 NorwayPublisher:Springer Science and Business Media LLC Authors: Thorvaldsen, Steinar; Flå, Tor; Willassen, Nils P;Thorvaldsen, Steinar; Flå, Tor; Willassen, Nils P;Abstract Background Statistical bioinformatics is the study of biological data sets obtained by new micro-technologies by means of proper statistical methods. For a better understanding of environmental adaptations of proteins, orthologous sequences from different habitats may be explored and compared. The main goal of the DeltaProt Toolbox is to provide users with important functionality that is needed for comparative screening and studies of extremophile proteins and protein classes. Visualization of the data sets is also the focus of this article, since visualizations can play a key role in making the various relationships transparent. This application paper is intended to inform the reader of the existence, functionality, and applicability of the toolbox. Results We present the DeltaProt Toolbox, a software toolbox that may be useful in importing, analyzing and visualizing data from multiple alignments of proteins. The toolbox has been written in MATLAB™ to provide an easy and user-friendly platform, including a graphical user interface, while ensuring good numerical performance. Problems in genome biology may be easily stated thanks to a compact input format. The toolbox also offers the possibility of utilizing structural information from the SABLE or other structure predictors. Different sequence plots can then be viewed and compared in order to find their similarities and differences. Detailed statistics are also calculated during the procedure. Conclusions The DeltaProt package is open source and freely available for academic, non-commercial use. The latest version of DeltaProt can be obtained from http://services.cbu.uib.no/software/deltaprot/. The website also contains documentation, and the toolbox comes with real data sets that are intended for training in applying the models to carry out bioinformatical and statistical analyses of protein sequences. Equipped with the new algorithms proposed here, DeltaProt serves as an auxiliary analysis tool capable of visualizing and comparing orthologus protein sequences. The framework of the algorithms also enables easy incorporation of extra information on structure, if such data is available.
Europe PubMed Centra... arrow_drop_down Europe PubMed CentralArticle . 2010Full-Text: http://europepmc.org/articles/PMC3001747Data sources: PubMed CentralMunin - Open Research Archive; Norwegian Open Research ArchivesArticle . 2010 . Peer-reviewedadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1186/1471-2105-11-573&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen gold 14 citations 14 popularity Top 10% influence Average impulse Average Powered by BIP!more_vert Europe PubMed Centra... arrow_drop_down Europe PubMed CentralArticle . 2010Full-Text: http://europepmc.org/articles/PMC3001747Data sources: PubMed CentralMunin - Open Research Archive; Norwegian Open Research ArchivesArticle . 2010 . Peer-reviewedadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1186/1471-2105-11-573&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2017 United Kingdom, France, Belgium, DenmarkPublisher:Oxford University Press (OUP) Funded by:UKRI | DanioPeaks: A Central Res..., UKRI | Computational Regulatory ..., NSERC +2 projectsUKRI| DanioPeaks: A Central Resource for Standardised Annotation and Re-annotation of Whole-Genome Data for the Model Vertebrate Zebrafish ,UKRI| Computational Regulatory Genomics ,NSERC ,CIHR ,WT| The core promoter: an unexplored regulatory level of transcription during vertebrate development.Aziz Khan; Oriol Fornes; Arnaud Stigliani; Marius Gheorghe; Jaime A. Castro-Mondragon; Robin van der Lee; Adrien Bessy; Jeanne Chèneby; Shubhada Rajabhau Kulkarni; Ge Tan; Damir Baranasic; David J. Arenillas; Albin Sandelin; Klaas Vandepoele; Boris Lenhard; Benoit Ballester; Wyeth W. Wasserman; François Parcy; Anthony Mathelier;pmc: PMC5753243 , PMC5753202
handle: 1854/LU-8558108
International audience; JASPAR (http://jaspar.genereg.net) is an open-access database of curated, non-redundant transcription factor (TF)-binding profiles stored as position frequency matrices (PFMs) and TF flexible models (TFFMs) for TFs across multiple species in six tax-onomic groups. In the 2018 release of JASPAR, the CORE collection has been expanded with 322 new PFMs (60 for vertebrates and 262 for plants) and 33 PFMs were updated (24 for vertebrates, 8 for plants and 1 for insects). These new profiles represent a 30% expansion compared to the 2016 release. In addition , we have introduced 316 TFFMs (95 for vertebrates , 218 for plants and 3 for insects). This release incorporates clusters of similar PFMs in each taxon and each TF class per taxon. The JASPAR 2018 CORE vertebrate collection of PFMs was used to predict TF-binding sites in the human genome. The predictions are made available to the scientific community through a UCSC Genome Browser track data hub. Finally , this update comes with a new web framework with an interactive and responsive user-interface, along with new features. All the underlying data can be retrieved programmatically using a RESTful API and through the JASPAR 2018 R/Bioconductor package .
Norwegian Open Resea... arrow_drop_down Europe PubMed CentralArticle . 2017Full-Text: http://europepmc.org/articles/PMC5753243Data sources: PubMed CentralEurope PubMed CentralArticle . 2017Full-Text: http://europepmc.org/articles/PMC5753202Data sources: PubMed CentralSpiral - Imperial College Digital RepositoryArticle . 2017Data sources: Spiral - Imperial College Digital RepositoryGhent University Academic BibliographyArticle . 2018Data sources: Ghent University Academic BibliographySpiral - Imperial College Digital RepositoryArticle . 2017Data sources: Spiral - Imperial College Digital RepositoryCopenhagen University Research Information SystemArticle . 2018Data sources: Copenhagen University Research Information SystemMémoires en Sciences de l'Information et de la Communication; HAL AMU; HAL-CEAArticle . 2018License: CC BYMémoires en Sciences de l'Information et de la Communication; HAL AMU; HAL-CEAArticle . 2018License: CC BYGhent University Academic BibliographyArticle . 2018Data sources: Ghent University Academic Bibliographyadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1093/nar/gkx1126&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen gold 1K citations 1,384 popularity Top 0.01% influence Top 1% impulse Top 0.01% Powered by BIP!visibility 26visibility views 26 download downloads 174 Powered bymore_vert Norwegian Open Resea... arrow_drop_down Europe PubMed CentralArticle . 2017Full-Text: http://europepmc.org/articles/PMC5753243Data sources: PubMed CentralEurope PubMed CentralArticle . 2017Full-Text: http://europepmc.org/articles/PMC5753202Data sources: PubMed CentralSpiral - Imperial College Digital RepositoryArticle . 2017Data sources: Spiral - Imperial College Digital RepositoryGhent University Academic BibliographyArticle . 2018Data sources: Ghent University Academic BibliographySpiral - Imperial College Digital RepositoryArticle . 2017Data sources: Spiral - Imperial College Digital RepositoryCopenhagen University Research Information SystemArticle . 2018Data sources: Copenhagen University Research Information SystemMémoires en Sciences de l'Information et de la Communication; HAL AMU; HAL-CEAArticle . 2018License: CC BYMémoires en Sciences de l'Information et de la Communication; HAL AMU; HAL-CEAArticle . 2018License: CC BYGhent University Academic BibliographyArticle . 2018Data sources: Ghent University Academic Bibliographyadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1093/nar/gkx1126&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2018Konstadia Lika; Tiago Domingos; Gonçalo Marques; Laure Pecquerie; starrlight augustine;We developed new methods for parameter estimation-in-context and, with the help of 125 authors, built the AmP (Add-my-Pet) database of Dynamic Energy Budget (DEB) models, parameters and referenced underlying data for animals, where each species constitutes one database entry. The combination of DEB parameters covers all aspects of energetics throughout the full organism’s life cycle, from the start of embryo development to death by aging. The species-specific parameter values capture biodiversity and can now, for the first time, be compared between animals species. An important insight brought by the AmP project is the classification of animal energetics according to a family of related DEB models that is structured on the basis of the mode of metabolic acceleration, which links up with the development of larval stages. We discuss the evolution of metabolism in this context, among animals in general, and ray-finned fish, mollusks and crustaceans in particular. New DEBtool code for estimating DEB parameters from data has been written. AmPtool code for analyzing patterns in parameter values has also been created. A new web-interface supports multiple ways to visualize data, parameters, and implied properties from the entire collection as well as on an entry by entry basis. The DEB models proved to fit data well, the median relative error is only 0.07, for the 1035 animal species at 2018/03/12, including some extinct ones, from all large phyla and all chordate orders, spanning a range of body masses of 16 orders of magnitude. This study is a first step to include evolutionary aspects into parameter estimation, allowing to infer properties of species for which very little is known.
PLoS Computational B... arrow_drop_down PLoS Computational Biology; OpenAPC Global InitiativeArticle . Conference object . 2018 . Peer-reviewedLicense: CC BYadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1371/journal.pcbi.1006100&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen gold 130 citations 130 popularity Top 1% influence Top 10% impulse Top 1% Powered by BIP!more_vert PLoS Computational B... arrow_drop_down PLoS Computational Biology; OpenAPC Global InitiativeArticle . Conference object . 2018 . Peer-reviewedLicense: CC BYadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Other literature type , Article 2009Publisher:Informa UK Limited Authors: Robert B, Scharpf; Håkon, Tjelmeland; Giovanni, Parmigiani; Andrew B, Nobel;Robert B, Scharpf; Håkon, Tjelmeland; Giovanni, Parmigiani; Andrew B, Nobel;In this paper we define a hierarchical Bayesian model for microarray expression data collected from several studies and use it to identify genes that show differential expression between two conditions. Key features include shrinkage across both genes and studies, and flexible modeling that allows for interactions between platforms and the estimated effect, as well as concordant and discordant differential expression across studies. We evaluated the performance of our model in a comprehensive fashion, using both artificial data, and a “split-study” validation approach that provides an agnostic assessment of the model's behavior not only under the null hypothesis, but also under a realistic alternative. The simulation results from the artificial data demonstrate the advantages of the Bayesian model. The 1 – AUC values for the Bayesian model are roughly half of the corresponding values for a direct combination of t- and SAM-statistics. Furthermore, the simulations provide guidelines for when the Bayesian model is most likely to be useful. Most noticeably, in small studies the Bayesian model generally outperforms other methods when evaluated by AUC, FDR, and MDR across a range of simulation parameters, and this difference diminishes for larger sample sizes in the individual studies. The split-study validation illustrates appropriate shrinkage of the Bayesian model in the absence of platform-, sample-, and annotation-differences that otherwise complicate experimental data analyses. Finally, we fit our model to four breast cancer studies employing different technologies (cDNA and Affymetrix) to estimate differential expression in estrogen receptor positive tumors versus negative ones. Software and data for reproducing our analysis are publicly available.
Europe PubMed Centra... arrow_drop_down Journal of the American Statistical AssociationArticle . 2009 . Peer-reviewedData sources: Crossrefadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.euAccess RoutesGreen bronze 30 citations 30 popularity Average influence Top 10% impulse Top 10% Powered by BIP!more_vert Europe PubMed Centra... arrow_drop_down Journal of the American Statistical AssociationArticle . 2009 . Peer-reviewedData sources: Crossrefadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Preprint , Article 2016 GermanyPublisher:Cold Spring Harbor Laboratory Funded by:EC | MICRODEEC| MICRODEAaron Weimann; Kyra Mooren; Jeremy Frank; Phillip B. Pope; Andreas Bremges; Alice C. McHardy; Nicola Segata;ABSTRACT The number of sequenced genomes is growing exponentially, profoundly shifting the bottleneck from data generation to genome interpretation. Traits are often used to characterize and distinguish bacteria and are likely a driving factor in microbial community composition, yet little is known about the traits of most microbes. We describe Traitar, the microbial trait analyzer, which is a fully automated software package for deriving phenotypes from a genome sequence. Traitar provides phenotype classifiers to predict 67 traits related to the use of various substrates as carbon and energy sources, oxygen requirement, morphology, antibiotic susceptibility, proteolysis, and enzymatic activities. Furthermore, it suggests protein families associated with the presence of particular phenotypes. Our method uses L1-regularized L2-loss support vector machines for phenotype assignments based on phyletic patterns of protein families and their evolutionary histories across a diverse set of microbial species. We demonstrate reliable phenotype assignment for Traitar to bacterial genomes from 572 species of eight phyla, also based on incomplete single-cell genomes and simulated draft genomes. We also showcase its application in metagenomics by verifying and complementing a manual metabolic reconstruction of two novel Clostridiales species based on draft genomes recovered from commercial biogas reactors. Traitar is available at https://github.com/hzi-bifo/traitar. IMPORTANCE Bacteria are ubiquitous in our ecosystem and have a major impact on human health, e.g., by supporting digestion in the human gut. Bacterial communities can also aid in biotechnological processes such as wastewater treatment or decontamination of polluted soils. Diverse bacteria contribute with their unique capabilities to the functioning of such ecosystems, but lab experiments to investigate those capabilities are labor-intensive. Major advances in sequencing techniques open up the opportunity to study bacteria by their genome sequences. For this purpose, we have developed Traitar, software that predicts traits of bacteria on the basis of their genomes. It is applicable to studies with tens or hundreds of bacterial genomes. Traitar may help researchers in microbiology to pinpoint the traits of interest, reducing the amount of wet lab work required. Bacteria are ubiquitous in our ecosystem and have a major impact on human health, e.g., by supporting digestion in the human gut. Bacterial communities can also aid in biotechnological processes such as wastewater treatment or decontamination of polluted soils. Diverse bacteria contribute with their unique capabilities to the functioning of such ecosystems, but lab experiments to investigate those capabilities are labor-intensive. Major advances in sequencing techniques open up the opportunity to study bacteria by their genome sequences. For this purpose, we have developed Traitar, software that predicts traits of bacteria on the basis of their genomes. It is applicable to studies with tens or hundreds of bacterial genomes. Traitar may help researchers in microbiology to pinpoint the traits of interest, reducing the amount of wet lab work required.
bioRxiv arrow_drop_down bioRxivPreprint . 2016Europe PubMed CentralArticle . 2016Full-Text: http://europepmc.org/articles/PMC5192078Data sources: PubMed CentralHelmholtz Zentrum für Infektionsforschung RepositoryArticle . 2017License: CC BY NC SAData sources: Helmholtz Zentrum für Infektionsforschung Repositoryhttps://doi.org/10.1128/mSyste...Article . Peer-reviewedData sources: European Union Open Data Portaladd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.euAccess RoutesGreen gold 84 citations 84 popularity Top 1% influence Top 10% impulse Top 10% Powered by BIP!more_vert bioRxiv arrow_drop_down bioRxivPreprint . 2016Europe PubMed CentralArticle . 2016Full-Text: http://europepmc.org/articles/PMC5192078Data sources: PubMed CentralHelmholtz Zentrum für Infektionsforschung RepositoryArticle . 2017License: CC BY NC SAData sources: Helmholtz Zentrum für Infektionsforschung Repositoryhttps://doi.org/10.1128/mSyste...Article . Peer-reviewedData sources: European Union Open Data Portaladd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
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description Publicationkeyboard_double_arrow_right Article 2010Publisher:Wiley Kenny, Helsens; Niklaas, Colaert; Harald, Barsnes; Thilo, Muth; Kristian, Flikka; An, Staes; Evy, Timmerman; Steffi, Wortelkamp; Albert, Sickmann; Joël, Vandekerckhove; Kris, Gevaert; Lennart, Martens;pmid: 20058248
AbstractMS‐based proteomics produces large amounts of mass spectra that require processing, identification and possibly quantification before interpretation can be undertaken. High‐throughput studies require automation of these various steps, and management of the data in association with the results obtained. We here present ms_lims (http://genesis.UGent.be/ms_lims), a freely available, open‐source system based on a central database to automate data management and processing in MS‐driven proteomics analyses.
PROTEOMICS arrow_drop_down PROTEOMICSArticle . 2010 . Peer-reviewedLicense: Wiley Online Library User AgreementData sources: Crossrefadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.euAccess Routesbronze 78 citations 78 popularity Top 10% influence Top 10% impulse Top 1% Powered by BIP!more_vert PROTEOMICS arrow_drop_down PROTEOMICSArticle . 2010 . Peer-reviewedLicense: Wiley Online Library User AgreementData sources: Crossrefadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1002/pmic.200900409&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2019 NorwayPublisher:Springer Science and Business Media LLC Funded by:WT | Development and applicati..., WTWT| Development and application of statistical methodology for the detection and characterisation of genetic factors in complex disease. ,WTAuthors: Miriam Gjerdevik; Astanand Jugessur; Øystein Ariansen Haaland; Julia Romanowska; +3 AuthorsMiriam Gjerdevik; Astanand Jugessur; Øystein Ariansen Haaland; Julia Romanowska; Rolv T. Lie; Heather J. Cordell; Håkon K. Gjessing;Background Log-linear and multinomial modeling offer a flexible framework for genetic association analyses of offspring (child), parent-of-origin and maternal effects, based on genotype data from a variety of child-parent configurations. Although the calculation of statistical power or sample size is an important first step in the planning of any scientific study, there is currently a lack of software for genetic power calculations in family-based study designs. Here, we address this shortcoming through new implementations of power calculations in the R package Haplin, which is a flexible and robust software for genetic epidemiological analyses. Power calculations in Haplin can be performed analytically using the asymptotic variance-covariance structure of the parameter estimator, or else by a straightforward simulation approach. Haplin performs power calculations for child, parent-of-origin and maternal effects, as well as for gene-environment interactions. The power can be calculated for both single SNPs and haplotypes, either autosomal or X-linked. Moreover, Haplin enables power calculations for different child-parent configurations, including (but not limited to) case-parent triads, case-mother dyads, and case-parent triads in combination with unrelated control-parent triads. Results We compared the asymptotic power approximations to the power of analysis attained with Haplin. For external validation, the results were further compared to the power of analysis attained by the EMIM software using data simulations from Haplin. Consistency observed between Haplin and EMIM across various genetic scenarios confirms the computational accuracy of the inference methods used in both programs. The results also demonstrate that power calculations in Haplin are applicable to genetic association studies using either log-linear or multinomial modeling approaches. Conclusions Haplin provides a robust and reliable framework for power calculations in genetic association analyses for a wide range of genetic effects and etiologic scenarios, based on genotype data from a variety of child-parent configurations. Electronic supplementary material The online version of this article (10.1186/s12859-019-2727-3) contains supplementary material, which is available to authorized users.
Europe PubMed Centra... arrow_drop_down Europe PubMed CentralArticle . 2019Full-Text: http://europepmc.org/articles/PMC6444579Data sources: PubMed CentralNorwegian Institute of Public Health Open RepositoryArticle . 2019Data sources: Norwegian Institute of Public Health Open RepositoryBergen Open Research Archive - UiBArticle . 2019 . Peer-reviewedLicense: CC BYData sources: Bergen Open Research Archive - UiBNorwegian Institute of Public Health Open RepositoryArticle . 2019Data sources: Norwegian Institute of Public Health Open Repositoryadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.euAccess RoutesGreen gold 12 citations 12 popularity Top 10% influence Average impulse Top 10% Powered by BIP!more_vert Europe PubMed Centra... arrow_drop_down Europe PubMed CentralArticle . 2019Full-Text: http://europepmc.org/articles/PMC6444579Data sources: PubMed CentralNorwegian Institute of Public Health Open RepositoryArticle . 2019Data sources: Norwegian Institute of Public Health Open RepositoryBergen Open Research Archive - UiBArticle . 2019 . Peer-reviewedLicense: CC BYData sources: Bergen Open Research Archive - UiBNorwegian Institute of Public Health Open RepositoryArticle . 2019Data sources: Norwegian Institute of Public Health Open Repositoryadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1186/s12859-019-2727-3&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2009 NorwayPublisher:Oxford University Press (OUP) Funded by:EC | DTSSCP, CIHREC| DTSSCP ,CIHRPortales-Casamar, E.; Thongjuea, S.; Kwon, A. T.; Arenillas, D.; Zhao, X.; Valen, E.; Yusuf, D.; Lenhard, B.; Wasserman, W. W.; Sandelin, A.;JASPAR (http://jaspar.genereg.net) is the leading open-access database of matrix profiles describing the DNA-binding patterns of transcription factors (TFs) and other proteins interacting with DNA in a sequence-specific manner. Its fourth major release is the largest expansion of the core database to date: the database now holds 457 non-redundant, curated profiles. The new entries include the first batch of profiles derived from ChIP-seq and ChIPchip whole-genome binding experiments, and 177 yeast TF binding profiles. The introduction of a yeast division brings the convenience of JASPAR to an active research community. As binding models are refined by newer data, the JASPAR database now uses versioning of matrices: in this release, 12% of the older models were updated to improved versions. Classification of TF families has been improved by adopting a new DNA-binding domain nomenclature. A curated catalog of mammalian TFs is provided, extending the use of the JASPAR profiles to additional TFs belonging to the same structural family. The changes in the database set the system ready for more rapid acquisition of new high-throughput data sources. Additionally, three new special collections provide matrix profile data produced by recent alternative high-throughput approaches. publishedVersion
Europe PubMed Centra... arrow_drop_down Europe PubMed CentralArticle . 2009Full-Text: http://europepmc.org/articles/PMC2808906Data sources: PubMed CentralBergen Open Research Archive - UiBArticle . 2010 . Peer-reviewedData sources: Bergen Open Research Archive - UiBadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1093/nar/gkp950&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen gold 560 citations 560 popularity Top 0.1% influence Top 1% impulse Top 0.1% Powered by BIP!more_vert Europe PubMed Centra... arrow_drop_down Europe PubMed CentralArticle . 2009Full-Text: http://europepmc.org/articles/PMC2808906Data sources: PubMed CentralBergen Open Research Archive - UiBArticle . 2010 . Peer-reviewedData sources: Bergen Open Research Archive - UiBadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1093/nar/gkp950&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Preprint 2019Publisher:Cold Spring Harbor Laboratory Funded by:WT | PRIDE Atlas., NIH | Development of Trans Prot..., NIH | Identification of synapti... +4 projectsWT| PRIDE Atlas. ,NIH| Development of Trans Proteomic Pipeline, an Analysis Suite for Mass Spectrometry ,NIH| Identification of synaptic gene sets for CNS synapse taxonomy and antibodies for their engagement ,NIH| Big Data for Discovery Science ,WT| The PRIDE database: A proteomics data hub in the life sciences ,NIH| Consortium to Study the Genetics of Longevity ,NIH| Advancing data and metadata standards for proteomics mass spectraPierre-Alain Binz; Jim Shofstahl; Juan Antonio Vizcaíno; Harald Barsnes; Robert J. Chalkley; Gerben Menschaert; Emanuele Alpi; Karl R. Clauser; Jimmy K. Eng; Lydie Lane; Sean L. Seymour; Luis Francisco Hernández Sánchez; Gerhard Mayer; Martin Eisenacher; Yasset Perez-Riverol; Eugene A. Kapp; Luis Mendoza; Peter R. Baker; Andrew Collins; Tim Van Den Bossche; Eric W. Deutsch;doi: 10.1101/624494
AbstractMass spectrometry-based proteomics enables the high-throughput identification and quantification of proteins, including sequence variants and post-translational modifications (PTMs), in biological samples. However, most workflows require that such variations be included in the search space used to analyze the data, and doing so remains challenging with most analysis tools. In order to facilitate the search for known sequence variants and PTMs, the Proteomics Standards Initiative (PSI) has designed and implemented the PSI Extended FASTA Format (PEFF). PEFF is based on the very popular FASTA format but adds a uniform mechanism for encoding substantially more metadata about the sequence collection as well as individual entries, including support for encoding known sequence variants, PTMs, and proteoforms. The format is very nearly backwards compatible, and as such, existing FASTA parsers will require little or no changes to be able to read PEFF files as FASTA files, although without supporting any of the extra capabilities of PEFF. PEFF is defined by a full specification document, controlled vocabulary terms, a set of example files, software libraries, and a file validator. Popular software and resources are starting to support PEFF, including the sequence search engine Comet and the knowledge bases neXtProt and UniProtKB. Widespread implementation of PEFF is expected to further enable proteogenomics and top-down proteomics applications by providing a standardized mechanism for encoding protein sequences and their known variations. All the related documentation, including the detailed file format specification and example files, are available athttp://www.psidev.info/peff.
add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.eu1 citations 1 popularity Average influence Average impulse Average Powered by BIP!more_vert add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1101/624494&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2013 NorwayPublisher:Springer Science and Business Media LLC Authors: Klepper, Kjetil; Drabløs, Finn;Klepper, Kjetil; Drabløs, Finn;Background: Traditional methods for computational motif discovery often suffer from poor performance. In particular, methods that search for sequence matches to known binding motifs tend to predict many non-functional binding sites because they fail to take into consideration the biological state of the cell. In recent years, genome-wide studies have generated a lot of data that has the potential to improve our ability to identify functional motifs and binding sites, such as information about chromatin accessibility and epigenetic states in different cell types. However, it is not always trivial to make use of this data in combination with existing motif discovery tools, especially for researchers who are not skilled in bioinformatics programming. Results: Here we present MotifLab, a general workbench for analysing regulatory sequence regions and discovering transcription factor binding sites and cis-regulatory modules. MotifLab supports comprehensive motif discovery and analysis by allowing users to integrate several popular motif discovery tools as well as different kinds of additional information, including phylogenetic conservation, epigenetic marks, DNase hypersensitive sites, ChIP-Seq data, positional binding preferences of transcription factors, transcription factor interactions and gene expression. MotifLab offers several data-processing operations that can be used to create, manipulate and analyse data objects, and complete analysis workflows can be constructed and automatically executed within MotifLab, including graphical presentation of the results. Conclusions: We have developed MotifLab as a flexible workbench for motif analysis in a genomic context. The flexibility and effectiveness of this workbench has been demonstrated on selected test cases, in particular two previously published benchmark data sets for single motifs and modules, and a realistic example of genes responding to treatment with forskolin. MotifLab is freely available at http://www.motiflab.org. © 2013 Klepper and Drabløs; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Europe PubMed Centra... arrow_drop_down Europe PubMed CentralArticle . 2013Full-Text: http://europepmc.org/articles/PMC3556059Data sources: PubMed Centraladd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.euAccess RoutesGreen gold 34 citations 34 popularity Average influence Average impulse Top 10% Powered by BIP!more_vert Europe PubMed Centra... arrow_drop_down Europe PubMed CentralArticle . 2013Full-Text: http://europepmc.org/articles/PMC3556059Data sources: PubMed Centraladd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1186/1471-2105-14-9&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2010 NorwayPublisher:Springer Science and Business Media LLC Authors: Thorvaldsen, Steinar; Flå, Tor; Willassen, Nils P;Thorvaldsen, Steinar; Flå, Tor; Willassen, Nils P;Abstract Background Statistical bioinformatics is the study of biological data sets obtained by new micro-technologies by means of proper statistical methods. For a better understanding of environmental adaptations of proteins, orthologous sequences from different habitats may be explored and compared. The main goal of the DeltaProt Toolbox is to provide users with important functionality that is needed for comparative screening and studies of extremophile proteins and protein classes. Visualization of the data sets is also the focus of this article, since visualizations can play a key role in making the various relationships transparent. This application paper is intended to inform the reader of the existence, functionality, and applicability of the toolbox. Results We present the DeltaProt Toolbox, a software toolbox that may be useful in importing, analyzing and visualizing data from multiple alignments of proteins. The toolbox has been written in MATLAB™ to provide an easy and user-friendly platform, including a graphical user interface, while ensuring good numerical performance. Problems in genome biology may be easily stated thanks to a compact input format. The toolbox also offers the possibility of utilizing structural information from the SABLE or other structure predictors. Different sequence plots can then be viewed and compared in order to find their similarities and differences. Detailed statistics are also calculated during the procedure. Conclusions The DeltaProt package is open source and freely available for academic, non-commercial use. The latest version of DeltaProt can be obtained from http://services.cbu.uib.no/software/deltaprot/. The website also contains documentation, and the toolbox comes with real data sets that are intended for training in applying the models to carry out bioinformatical and statistical analyses of protein sequences. Equipped with the new algorithms proposed here, DeltaProt serves as an auxiliary analysis tool capable of visualizing and comparing orthologus protein sequences. The framework of the algorithms also enables easy incorporation of extra information on structure, if such data is available.
Europe PubMed Centra... arrow_drop_down Europe PubMed CentralArticle . 2010Full-Text: http://europepmc.org/articles/PMC3001747Data sources: PubMed CentralMunin - Open Research Archive; Norwegian Open Research ArchivesArticle . 2010 . Peer-reviewedadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1186/1471-2105-11-573&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen gold 14 citations 14 popularity Top 10% influence Average impulse Average Powered by BIP!more_vert Europe PubMed Centra... arrow_drop_down Europe PubMed CentralArticle . 2010Full-Text: http://europepmc.org/articles/PMC3001747Data sources: PubMed CentralMunin - Open Research Archive; Norwegian Open Research ArchivesArticle . 2010 . Peer-reviewedadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1186/1471-2105-11-573&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2017 United Kingdom, France, Belgium, DenmarkPublisher:Oxford University Press (OUP) Funded by:UKRI | DanioPeaks: A Central Res..., UKRI | Computational Regulatory ..., NSERC +2 projectsUKRI| DanioPeaks: A Central Resource for Standardised Annotation and Re-annotation of Whole-Genome Data for the Model Vertebrate Zebrafish ,UKRI| Computational Regulatory Genomics ,NSERC ,CIHR ,WT| The core promoter: an unexplored regulatory level of transcription during vertebrate development.Aziz Khan; Oriol Fornes; Arnaud Stigliani; Marius Gheorghe; Jaime A. Castro-Mondragon; Robin van der Lee; Adrien Bessy; Jeanne Chèneby; Shubhada Rajabhau Kulkarni; Ge Tan; Damir Baranasic; David J. Arenillas; Albin Sandelin; Klaas Vandepoele; Boris Lenhard; Benoit Ballester; Wyeth W. Wasserman; François Parcy; Anthony Mathelier;pmc: PMC5753243 , PMC5753202
handle: 1854/LU-8558108
International audience; JASPAR (http://jaspar.genereg.net) is an open-access database of curated, non-redundant transcription factor (TF)-binding profiles stored as position frequency matrices (PFMs) and TF flexible models (TFFMs) for TFs across multiple species in six tax-onomic groups. In the 2018 release of JASPAR, the CORE collection has been expanded with 322 new PFMs (60 for vertebrates and 262 for plants) and 33 PFMs were updated (24 for vertebrates, 8 for plants and 1 for insects). These new profiles represent a 30% expansion compared to the 2016 release. In addition , we have introduced 316 TFFMs (95 for vertebrates , 218 for plants and 3 for insects). This release incorporates clusters of similar PFMs in each taxon and each TF class per taxon. The JASPAR 2018 CORE vertebrate collection of PFMs was used to predict TF-binding sites in the human genome. The predictions are made available to the scientific community through a UCSC Genome Browser track data hub. Finally , this update comes with a new web framework with an interactive and responsive user-interface, along with new features. All the underlying data can be retrieved programmatically using a RESTful API and through the JASPAR 2018 R/Bioconductor package .
Norwegian Open Resea... arrow_drop_down Europe PubMed CentralArticle . 2017Full-Text: http://europepmc.org/articles/PMC5753243Data sources: PubMed CentralEurope PubMed CentralArticle . 2017Full-Text: http://europepmc.org/articles/PMC5753202Data sources: PubMed CentralSpiral - Imperial College Digital RepositoryArticle . 2017Data sources: Spiral - Imperial College Digital RepositoryGhent University Academic BibliographyArticle . 2018Data sources: Ghent University Academic BibliographySpiral - Imperial College Digital RepositoryArticle . 2017Data sources: Spiral - Imperial College Digital RepositoryCopenhagen University Research Information SystemArticle . 2018Data sources: Copenhagen University Research Information SystemMémoires en Sciences de l'Information et de la Communication; HAL AMU; HAL-CEAArticle . 2018License: CC BYMémoires en Sciences de l'Information et de la Communication; HAL AMU; HAL-CEAArticle . 2018License: CC BYGhent University Academic BibliographyArticle . 2018Data sources: Ghent University Academic Bibliographyadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1093/nar/gkx1126&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen gold 1K citations 1,384 popularity Top 0.01% influence Top 1% impulse Top 0.01% Powered by BIP!visibility 26visibility views 26 download downloads 174 Powered bymore_vert Norwegian Open Resea... arrow_drop_down Europe PubMed CentralArticle . 2017Full-Text: http://europepmc.org/articles/PMC5753243Data sources: PubMed CentralEurope PubMed CentralArticle . 2017Full-Text: http://europepmc.org/articles/PMC5753202Data sources: PubMed CentralSpiral - Imperial College Digital RepositoryArticle . 2017Data sources: Spiral - Imperial College Digital RepositoryGhent University Academic BibliographyArticle . 2018Data sources: Ghent University Academic BibliographySpiral - Imperial College Digital RepositoryArticle . 2017Data sources: Spiral - Imperial College Digital RepositoryCopenhagen University Research Information SystemArticle . 2018Data sources: Copenhagen University Research Information SystemMémoires en Sciences de l'Information et de la Communication; HAL AMU; HAL-CEAArticle . 2018License: CC BYMémoires en Sciences de l'Information et de la Communication; HAL AMU; HAL-CEAArticle . 2018License: CC BYGhent University Academic BibliographyArticle . 2018Data sources: Ghent University Academic Bibliographyadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1093/nar/gkx1126&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2018Konstadia Lika; Tiago Domingos; Gonçalo Marques; Laure Pecquerie; starrlight augustine;We developed new methods for parameter estimation-in-context and, with the help of 125 authors, built the AmP (Add-my-Pet) database of Dynamic Energy Budget (DEB) models, parameters and referenced underlying data for animals, where each species constitutes one database entry. The combination of DEB parameters covers all aspects of energetics throughout the full organism’s life cycle, from the start of embryo development to death by aging. The species-specific parameter values capture biodiversity and can now, for the first time, be compared between animals species. An important insight brought by the AmP project is the classification of animal energetics according to a family of related DEB models that is structured on the basis of the mode of metabolic acceleration, which links up with the development of larval stages. We discuss the evolution of metabolism in this context, among animals in general, and ray-finned fish, mollusks and crustaceans in particular. New DEBtool code for estimating DEB parameters from data has been written. AmPtool code for analyzing patterns in parameter values has also been created. A new web-interface supports multiple ways to visualize data, parameters, and implied properties from the entire collection as well as on an entry by entry basis. The DEB models proved to fit data well, the median relative error is only 0.07, for the 1035 animal species at 2018/03/12, including some extinct ones, from all large phyla and all chordate orders, spanning a range of body masses of 16 orders of magnitude. This study is a first step to include evolutionary aspects into parameter estimation, allowing to infer properties of species for which very little is known.
PLoS Computational B... arrow_drop_down PLoS Computational Biology; OpenAPC Global InitiativeArticle . Conference object . 2018 . Peer-reviewedLicense: CC BYadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1371/journal.pcbi.1006100&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen gold 130 citations 130 popularity Top 1% influence Top 10% impulse Top 1% Powered by BIP!more_vert PLoS Computational B... arrow_drop_down PLoS Computational Biology; OpenAPC Global InitiativeArticle . Conference object . 2018 . Peer-reviewedLicense: CC BYadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1371/journal.pcbi.1006100&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Other literature type , Article 2009Publisher:Informa UK Limited Authors: Robert B, Scharpf; Håkon, Tjelmeland; Giovanni, Parmigiani; Andrew B, Nobel;Robert B, Scharpf; Håkon, Tjelmeland; Giovanni, Parmigiani; Andrew B, Nobel;In this paper we define a hierarchical Bayesian model for microarray expression data collected from several studies and use it to identify genes that show differential expression between two conditions. Key features include shrinkage across both genes and studies, and flexible modeling that allows for interactions between platforms and the estimated effect, as well as concordant and discordant differential expression across studies. We evaluated the performance of our model in a comprehensive fashion, using both artificial data, and a “split-study” validation approach that provides an agnostic assessment of the model's behavior not only under the null hypothesis, but also under a realistic alternative. The simulation results from the artificial data demonstrate the advantages of the Bayesian model. The 1 – AUC values for the Bayesian model are roughly half of the corresponding values for a direct combination of t- and SAM-statistics. Furthermore, the simulations provide guidelines for when the Bayesian model is most likely to be useful. Most noticeably, in small studies the Bayesian model generally outperforms other methods when evaluated by AUC, FDR, and MDR across a range of simulation parameters, and this difference diminishes for larger sample sizes in the individual studies. The split-study validation illustrates appropriate shrinkage of the Bayesian model in the absence of platform-, sample-, and annotation-differences that otherwise complicate experimental data analyses. Finally, we fit our model to four breast cancer studies employing different technologies (cDNA and Affymetrix) to estimate differential expression in estrogen receptor positive tumors versus negative ones. Software and data for reproducing our analysis are publicly available.
Europe PubMed Centra... arrow_drop_down Journal of the American Statistical AssociationArticle . 2009 . Peer-reviewedData sources: Crossrefadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1198/jasa.2009.ap07611&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen bronze 30 citations 30 popularity Average influence Top 10% impulse Top 10% Powered by BIP!more_vert Europe PubMed Centra... arrow_drop_down Journal of the American Statistical AssociationArticle . 2009 . Peer-reviewedData sources: Crossrefadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1198/jasa.2009.ap07611&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Preprint , Article 2016 GermanyPublisher:Cold Spring Harbor Laboratory Funded by:EC | MICRODEEC| MICRODEAaron Weimann; Kyra Mooren; Jeremy Frank; Phillip B. Pope; Andreas Bremges; Alice C. McHardy; Nicola Segata;ABSTRACT The number of sequenced genomes is growing exponentially, profoundly shifting the bottleneck from data generation to genome interpretation. Traits are often used to characterize and distinguish bacteria and are likely a driving factor in microbial community composition, yet little is known about the traits of most microbes. We describe Traitar, the microbial trait analyzer, which is a fully automated software package for deriving phenotypes from a genome sequence. Traitar provides phenotype classifiers to predict 67 traits related to the use of various substrates as carbon and energy sources, oxygen requirement, morphology, antibiotic susceptibility, proteolysis, and enzymatic activities. Furthermore, it suggests protein families associated with the presence of particular phenotypes. Our method uses L1-regularized L2-loss support vector machines for phenotype assignments based on phyletic patterns of protein families and their evolutionary histories across a diverse set of microbial species. We demonstrate reliable phenotype assignment for Traitar to bacterial genomes from 572 species of eight phyla, also based on incomplete single-cell genomes and simulated draft genomes. We also showcase its application in metagenomics by verifying and complementing a manual metabolic reconstruction of two novel Clostridiales species based on draft genomes recovered from commercial biogas reactors. Traitar is available at https://github.com/hzi-bifo/traitar. IMPORTANCE Bacteria are ubiquitous in our ecosystem and have a major impact on human health, e.g., by supporting digestion in the human gut. Bacterial communities can also aid in biotechnological processes such as wastewater treatment or decontamination of polluted soils. Diverse bacteria contribute with their unique capabilities to the functioning of such ecosystems, but lab experiments to investigate those capabilities are labor-intensive. Major advances in sequencing techniques open up the opportunity to study bacteria by their genome sequences. For this purpose, we have developed Traitar, software that predicts traits of bacteria on the basis of their genomes. It is applicable to studies with tens or hundreds of bacterial genomes. Traitar may help researchers in microbiology to pinpoint the traits of interest, reducing the amount of wet lab work required. Bacteria are ubiquitous in our ecosystem and have a major impact on human health, e.g., by supporting digestion in the human gut. Bacterial communities can also aid in biotechnological processes such as wastewater treatment or decontamination of polluted soils. Diverse bacteria contribute with their unique capabilities to the functioning of such ecosystems, but lab experiments to investigate those capabilities are labor-intensive. Major advances in sequencing techniques open up the opportunity to study bacteria by their genome sequences. For this purpose, we have developed Traitar, software that predicts traits of bacteria on the basis of their genomes. It is applicable to studies with tens or hundreds of bacterial genomes. Traitar may help researchers in microbiology to pinpoint the traits of interest, reducing the amount of wet lab work required.
bioRxiv arrow_drop_down bioRxivPreprint . 2016Europe PubMed CentralArticle . 2016Full-Text: http://europepmc.org/articles/PMC5192078Data sources: PubMed CentralHelmholtz Zentrum für Infektionsforschung RepositoryArticle . 2017License: CC BY NC SAData sources: Helmholtz Zentrum für Infektionsforschung Repositoryhttps://doi.org/10.1128/mSyste...Article . Peer-reviewedData sources: European Union Open Data Portaladd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1101/043315&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen gold 84 citations 84 popularity Top 1% influence Top 10% impulse Top 10% Powered by BIP!more_vert bioRxiv arrow_drop_down bioRxivPreprint . 2016Europe PubMed CentralArticle . 2016Full-Text: http://europepmc.org/articles/PMC5192078Data sources: PubMed CentralHelmholtz Zentrum für Infektionsforschung RepositoryArticle . 2017License: CC BY NC SAData sources: Helmholtz Zentrum für Infektionsforschung Repositoryhttps://doi.org/10.1128/mSyste...Article . Peer-reviewedData sources: European Union Open Data Portaladd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1101/043315&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu