- home
- Search
- ELIXIR GR
- Open Access
- ELIXIR GR
- Open Access
Loading
description Publicationkeyboard_double_arrow_right Preprint 2021Publisher:Cold Spring Harbor Laboratory Romain Lopez; Baoguo Li; Hadas Keren-Shaul; Pierre Boyeau; Kedmi M; David Pilzer; Adam Jelinski; Eyal David; Allon Wagner; Addad Y; Michael I. Jordan; Ido Amit; Nir Yosef;AbstractThe function of mammalian cells is largely influenced by their tissue microenvironment. Advances in spatial transcriptomics open the way for studying these important determinants of cellular function by enabling a transcriptome-wide evaluation of gene expressionin situ. A critical limitation of the current technologies, however, is that their resolution is limited to niches (spots) of sizes well beyond that of a single cell, thus providing measurements for cell aggregates which may mask critical interactions between neighboring cells of different types. While joint analysis with single-cell RNA-sequencing (scRNA-seq) can be leveraged to alleviate this problem, current analyses are limited to a discrete view of cell type proportion inside every spot. This limitation becomes critical in the common case where, even within a cell type, there is a continuum of cell states that cannot be clearly demarcated but reflects important differences in the way cells function and interact with their surroundings. To address this, we developed Deconvolution of Spatial Transcriptomics profiles using Variational Inference (DestVI), a probabilistic method for multi-resolution analysis for spatial transcriptomics that explicitly models continuous variation within cell types. Using simulations, we demonstrate that DestVI is capable of providing higher resolution compared to the existing methods and that it can estimate gene expression by every cell type inside every spot. We then introduce an automated pipeline that uses DestVI for analysis of single tissue slices and comparison between tissues. We apply this pipeline to study the immune crosstalk within lymph nodes to infection and explore the spatial organization of a mouse tumor model. In both cases, we demonstrate that DestVI can provide a high resolution and accurate spatial characterization of the cellular organization of these tissues, and that it is capable of identifying important cell-type-specific changes in gene expression - between different tissue regions or between conditions. DestVI is available as an open-source software package in the scvi-tools codebase (https://scvi-tools.org).
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=10.1101/2021.05.10.443517&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu20 citations 20 popularity Top 10% influence Average impulse Top 10% 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=10.1101/2021.05.10.443517&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2020 EnglishPublisher:Frontiers Media S.A. Authors: Paraskevi Manolaki; Paraskevi Manolaki; Georgia Tooulakou; Caroline Urup Byberg; +4 AuthorsParaskevi Manolaki; Paraskevi Manolaki; Georgia Tooulakou; Caroline Urup Byberg; Franziska Eller; Brian K. Sorrell; Maria I. Klapa; Tenna Riis;Amphibious plants, living in land-water ecotones, have to cope with challenging and continuously changing growth conditions in their habitats with respect to nutrient and light availability. They have thus evolved a variety of mechanisms to tolerate and adapt to these changes. Therefore, the study of these plants is a major area of ecophysiology and environmental ecological research. However, our understanding of their capacity for physiological adaptation and tolerance remains limited and requires systemic approaches for comprehensive analyses. To this end, in this study, we have conducted a mesocosm experiment to analyze the response of Butomus umbellatus, a common amphibious species in Denmark, to nutrient enrichment and shading. Our study follows a systematic integration of morphological (including plant height, leaf number, and biomass accumulation), ecophysiological (photosynthesis-irradiance responses, leaf pigment content, and C and N content in plant organs), and leaf metabolomic measurements using gas chromatography-mass spectrometry (39 mainly primary metabolites), based on bioinformatic methods. No studies of this type have been previously reported for this plant species. We observed that B. umbellatus responds to nutrient enrichment and light reduction through different mechanisms and were able to identify its nutrient enrichment acclimation threshold within the applied nutrient gradient. Up to that threshold, the morpho-physiological response to nutrient enrichment was profound, indicating fast-growing trends (higher growth rates and biomass accumulation), but only few parameters changed significantly from light to shade [specific leaf area (SLA); quantum yield (φ)]. Metabolomic analysis supported the morpho-physiological results regarding nutrient overloading, indicating also subtle changes due to shading not directly apparent in the other measurements. The combined profile analysis revealed leaf metabolite and morpho-physiological parameter associations. In this context, leaf lactate, currently of uncertain role in higher plants, emerged as a shading acclimation biomarker, along with SLA and φ. The study enhances both the ecophysiology methodological toolbox and our knowledge of the adaptive capacity of amphibious species. It demonstrates that the educated combination of physiological with metabolomic measurements using bioinformatic approaches is a promising approach for ecophysiology research, enabling the elucidation of discriminatory metabolic shifts to be used for early diagnosis and even prognosis of natural ecosystem responses to climate change.
Frontiers in Plant S... arrow_drop_down Frontiers in Plant ScienceArticle . 2020Full-Text: http://europepmc.org/articles/PMC7772459Data 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=10.3389/fpls.2020.581787&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess Routesgold 2 citations 2 popularity Average influence Average impulse Average Powered by BIP!more_vert Frontiers in Plant S... arrow_drop_down Frontiers in Plant ScienceArticle . 2020Full-Text: http://europepmc.org/articles/PMC7772459Data 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=10.3389/fpls.2020.581787&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Other literature type 2010 FrancePublisher:Wiley Fabrice Legeai; Shuji Shigenobu; Jean-Pierre Gauthier; John K. Colbourne; Claude Rispe; Olivier Collin; Stephen Richards; Alex C.C. Wilson; Terence Murphy; Denis Tagu;AbstractAphidBase is a centralized bioinformatic resource that was developed to facilitate community annotation of the pea aphid genome by the International Aphid Genomics Consortium (IAGC). The AphidBase Information System designed to organize and distribute genomic data and annotations for a large international community was constructed using open source software tools from the Generic Model Organism Database (GMOD). The system includes Apollo and GBrowse utilities as well as a wiki, blast search capabilities and a full text search engine. AphidBase strongly supported community cooperation and coordination in the curation of gene models during community annotation of the pea aphid genome. AphidBase can be accessed at http://www.aphidbase.com.
Insect Molecular Bio... arrow_drop_down Insect Molecular BiologyArticle . 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=10.1111/j.1365-2583.2009.00930.x&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen bronze 104 citations 104 popularity Top 10% influence Top 10% impulse Top 1% Powered by BIP!more_vert Insect Molecular Bio... arrow_drop_down Insect Molecular BiologyArticle . 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=10.1111/j.1365-2583.2009.00930.x&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Preprint , Article , Other literature type 2020 GermanyPublisher:Cold Spring Harbor Laboratory Authors: Dominik Kopczynski; Nils Hoffmann; Bing Peng; Robert Ahrends;Dominik Kopczynski; Nils Hoffmann; Bing Peng; Robert Ahrends;We introduce Goslin, a polyglot grammar for common lipid shorthand nomenclatures based on the LIPID MAPS nomenclature and the shorthand nomenclature established by Liebisch and coauthors and used by LipidHome and SwissLipids. Goslin was designed to address the following pressing issues in the lipidomics field: (1) to simplify the implementation of lipid name handling for developers of mass spectrometry-based lipidomics tools, (2) to offer a tool that unifies and normalizes the main existing lipid name dialects enabling a lipidomics analysis in a high-throughput fashion, and (3) to provide a consistent mapping from lipid shorthand names to lipid building blocks and structural properties. We provide implementations of Goslin in four major programming languages, namely, C++, Java, Python 3, and R to kick-start adoption and integration. Further, we set up a web service for users to work with Goslin directly. All implementations are available free of charge under a permissive open source license.
bioRxiv arrow_drop_down bioRxivPreprint . 2020Europe PubMed CentralArticle . 2020Full-Text: http://europepmc.org/articles/PMC7467413Data sources: PubMed CentralPublications at Bielefeld UniversityOther literature type . 2020License: "In Copyright" Rights StatementData sources: Publications at Bielefeld Universityadd 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=10.1101/2020.04.17.046656&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen hybrid 14 citations 14 popularity Top 10% influence Average impulse Top 10% Powered by BIP!more_vert bioRxiv arrow_drop_down bioRxivPreprint . 2020Europe PubMed CentralArticle . 2020Full-Text: http://europepmc.org/articles/PMC7467413Data sources: PubMed CentralPublications at Bielefeld UniversityOther literature type . 2020License: "In Copyright" Rights StatementData sources: Publications at Bielefeld Universityadd 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=10.1101/2020.04.17.046656&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2021Publisher:Oxford University Press (OUP) Fernando Pozo; Laura Martinez-Gomez; Thomas A Walsh; Jose Manuel Rodriguez; Tomás Di Domenico; Federico Abascal; Jesús Vázquez; Michael L. Tress;AbstractAlternative splicing of messenger RNA can generate an array of mature transcripts, but it is not clear how many go on to produce functionally relevant protein isoforms. There is only limited evidence for alternative proteins in proteomics analyses and data from population genetic variation studies indicate that most alternative exons are evolving neutrally. Determining which transcripts produce biologically important isoforms is key to understanding isoform function and to interpreting the real impact of somatic mutations and germline variations. Here we have developed a method, TRIFID, to classify the functional importance of splice isoforms. TRIFID was trained on isoforms detected in large-scale proteomics analyses and distinguishes these biologically important splice isoforms with high confidence. Isoforms predicted as functionally important by the algorithm had measurable cross species conservation and significantly fewer broken functional domains. Additionally, exons that code for these functionally important protein isoforms are under purifying selection, while exons from low scoring transcripts largely appear to be evolving neutrally. TRIFID has been developed for the human genome, but it could in principle be applied to other well-annotated species. We believe that this method will generate valuable insights into the cellular importance of alternative splicing.
Europe PubMed Centra... arrow_drop_down Europe PubMed CentralArticle . 2021Full-Text: http://europepmc.org/articles/PMC8140736Data sources: PubMed CentralNAR Genomics and BioinformaticsArticle . 2021 . Peer-reviewedLicense: CC BY NCData 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=10.1093/nargab/lqab044&type=result"></script>'); --> </script>
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 . 2021Full-Text: http://europepmc.org/articles/PMC8140736Data sources: PubMed CentralNAR Genomics and BioinformaticsArticle . 2021 . Peer-reviewedLicense: CC BY NCData 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=10.1093/nargab/lqab044&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2018Publisher:Springer Science and Business Media LLC Authors: Abhik Seal; David J. Wild;Abhik Seal; David J. Wild;Abstract Background Netpredictor is an R package for prediction of missing links in any given unipartite or bipartite network. The package provides utilities to compute missing links in a bipartite and well as unipartite networks using Random Walk with Restart and Network inference algorithm and a combination of both. The package also allows computation of Bipartite network properties, visualization of communities for two different sets of nodes, and calculation of significant interactions between two sets of nodes using permutation based testing. The application can also be used to search for top-K shortest paths between interactome and use enrichment analysis for disease, pathway and ontology. The R standalone package (including detailed introductory vignettes) and associated R Shiny web application is available under the GPL-2 Open Source license and is freely available to download. Results We compared different algorithms performance in different small datasets and found random walk supersedes rest of the algorithms. The package is developed to perform network based prediction of unipartite and bipartite networks and use the results to understand the functionality of proteins in an interactome using enrichment analysis. Conclusion The rapid application development envrionment like shiny, helps non programmers to develop fast rich visualization apps and we beleieve it would continue to grow in future with further enhancements. We plan to update our algorithms in the package in near future and help scientist to analyse data in a much streamlined fashion.
Europe PubMed Centra... arrow_drop_down Europe PubMed CentralArticle . 2018Full-Text: http://europepmc.org/articles/PMC6047136Data 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/s12859-018-2254-7&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen gold 14 citations 14 popularity Top 10% influence Average impulse Top 10% Powered by BIP!more_vert Europe PubMed Centra... arrow_drop_down Europe PubMed CentralArticle . 2018Full-Text: http://europepmc.org/articles/PMC6047136Data 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/s12859-018-2254-7&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2012Publisher:Public Library of Science (PLoS) Funded by:NIH | Translational Research at..., NIH | Semantic Approaches to Ph..., NIH | CORE--COMPUTATIONAL SCIEN...NIH| Translational Research at The University of Chicago (UL1) ,NIH| Semantic Approaches to Phenotypic Databases Analyses ,NIH| CORE--COMPUTATIONAL SCIENCESXinan, Yang; Kelly, Regan; Yong, Huang; Qingbei, Zhang; Jianrong, Li; Tanguy Y, Seiwert; Ezra E W, Cohen; H Rosie, Xing; Yves A, Lussier;Gene expression signatures that are predictive of therapeutic response or prognosis are increasingly useful in clinical care; however, mechanistic (and intuitive) interpretation of expression arrays remains an unmet challenge. Additionally, there is surprisingly little gene overlap among distinct clinically validated expression signatures. These “causality challenges” hinder the adoption of signatures as compared to functionally well-characterized single gene biomarkers. To increase the utility of multi-gene signatures in survival studies, we developed a novel approach to generate “personal mechanism signatures” of molecular pathways and functions from gene expression arrays. FAIME, the Functional Analysis of Individual Microarray Expression, computes mechanism scores using rank-weighted gene expression of an individual sample. By comparing head and neck squamous cell carcinoma (HNSCC) samples with non-tumor control tissues, the precision and recall of deregulated FAIME-derived mechanisms of pathways and molecular functions are comparable to those produced by conventional cohort-wide methods (e.g. GSEA). The overlap of “Oncogenic FAIME Features of HNSCC” (statistically significant and differentially regulated FAIME-derived genesets representing GO functions or KEGG pathways derived from HNSCC tissue) among three distinct HNSCC datasets (pathways:46%, p<0.001) is more significant than the gene overlap (genes:4%). These Oncogenic FAIME Features of HNSCC can accurately discriminate tumors from control tissues in two additional HNSCC datasets (n = 35 and 91, F-accuracy = 100% and 97%, empirical p<0.001, area under the receiver operating characteristic curves = 99% and 92%), and stratify recurrence-free survival in patients from two independent studies (p = 0.0018 and p = 0.032, log-rank). Previous approaches depending on group assignment of individual samples before selecting features or learning a classifier are limited by design to discrete-class prediction. In contrast, FAIME calculates mechanism profiles for individual patients without requiring group assignment in validation sets. FAIME is more amenable for clinical deployment since it translates the gene-level measurements of each given sample into pathways and molecular function profiles that can be applied to analyze continuous phenotypes in clinical outcome studies (e.g. survival time, tumor volume). Author Summary Clinical utilization of multi-gene expression signatures that are predictive of therapeutic response has been steadily increasing, however, interpretation of such results remains challenging because multi-gene signatures, generated from analyzing different patient cohorts, tend to be equally predictive but contain minimal overlap. Whereas pathway-level analyses of expression arrays show promise for generating clinically meaningful mechanistic signatures, current approaches do not permit single-patient based analyses that are independent of cross-group calculations. To bridge the gap between deterministic biological mechanisms of single-gene biomarkers and the statistical predictive power of multi-gene signatures that are disconnected from mechanisms, we developed FAIME, a novel method that transforms microarray gene expression data into individualized patient profiles of molecular mechanisms. We have validated its capability for predicting clinical outcomes, including cancer patient samples derived from six different clinical trial cohorts of head and neck cancers. This method provides opportunities to harness an untapped resource for personal genomics: clinical evaluation and testing of individually interpretable mechanistic profiles derived from gene expression arrays.
Europe PubMed Centra... arrow_drop_down Europe PubMed CentralArticle . 2012Full-Text: http://europepmc.org/articles/PMC3266878Data 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=10.1371/journal.pcbi.1002350&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen gold 66 citations 66 popularity Top 10% influence Top 10% impulse Top 10% Powered by BIP!more_vert Europe PubMed Centra... arrow_drop_down Europe PubMed CentralArticle . 2012Full-Text: http://europepmc.org/articles/PMC3266878Data 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=10.1371/journal.pcbi.1002350&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2018 NetherlandsPublisher:Springer Science and Business Media LLC Singh, Gurnoor; Kuzniar, Arnold; van Mulligen, Erik M.; Gavai, Anand; Bachem, Christian W.; Visser, Richard G.F.; Finkers, Richard;Background A quantitative trait locus (QTL) is a genomic region that correlates with a phenotype. Most of the experimental information about QTL mapping studies is described in tables of scientific publications. Traditional text mining techniques aim to extract information from unstructured text rather than from tables. We present QTLTableMiner++ (QTM), a table mining tool that extracts and semantically annotates QTL information buried in (heterogeneous) tables of plant science literature. QTM is a command line tool written in the Java programming language. This tool takes scientific articles from the Europe PMC repository as input, extracts QTL tables using keyword matching and ontology-based concept identification. The tables are further normalized using rules derived from table properties such as captions, column headers and table footers. Furthermore, table columns are classified into three categories namely column descriptors, properties and values based on column headers and data types of cell entries. Abbreviations found in the tables are expanded using the Schwartz and Hearst algorithm. Finally, the content of QTL tables is semantically enriched with domain-specific ontologies (e.g. Crop Ontology, Plant Ontology and Trait Ontology) using the Apache Solr search platform and the results are stored in a relational database and a text file. Results The performance of the QTM tool was assessed by precision and recall based on the information retrieved from two manually annotated corpora of open access articles, i.e. QTL mapping studies in tomato (Solanum lycopersicum) and in potato (S. tuberosum). In summary, QTM detected QTL statements in tomato with 74.53% precision and 92.56% recall and in potato with 82.82% precision and 98.94% recall. Conclusion QTM is a unique tool that aids in providing QTL information in machine-readable and semantically interoperable formats. Electronic supplementary material The online version of this article (10.1186/s12859-018-2165-7) contains supplementary material, which is available to authorized users.
NARCIS; Research@WUR arrow_drop_down NARCIS; Research@WUROther literature type . Article . 2018License: CC BYFull-Text: https://edepot.wur.nl/452409Europe PubMed CentralArticle . 2018Full-Text: http://europepmc.org/articles/PMC5970438Data 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/s12859-018-2165-7&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen gold 8 citations 8 popularity Average influence Average impulse Top 10% Powered by BIP!more_vert NARCIS; Research@WUR arrow_drop_down NARCIS; Research@WUROther literature type . Article . 2018License: CC BYFull-Text: https://edepot.wur.nl/452409Europe PubMed CentralArticle . 2018Full-Text: http://europepmc.org/articles/PMC5970438Data 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/s12859-018-2165-7&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Other literature type , Presentation 2020 EnglishPublisher:Zenodo Authors: Zogopoulos, Vasileios; Malatras, Apostolos; Vasileiou, Christos; Kyriakidis, Konstantinos V.; +1 AuthorsZogopoulos, Vasileios; Malatras, Apostolos; Vasileiou, Christos; Kyriakidis, Konstantinos V.; Michalopoulos, Ioannis;Creation of a WebTool based on human gene coexpression analysis, that discovers functional partners to a gene of interest or proposes biological roles to genes of unknown function
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=10.5281/zenodo.4042975&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen 0 citations 0 popularity Average influence Average impulse Average Powered by BIP!visibility 91visibility views 91 download downloads 13 Powered bymore_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=10.5281/zenodo.4042975&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2018Publisher:Elsevier BV Authors: Juan Rafael Orozco-Arroyave; Juan Camilo Vásquez-Correa; Jesús Francisco Vargas-Bonilla; R. Arora; +12 AuthorsJuan Rafael Orozco-Arroyave; Juan Camilo Vásquez-Correa; Jesús Francisco Vargas-Bonilla; R. Arora; N. Dehak; P.S. Nidadavolu; H. Christensen; F. Rudzicz; M. Yancheva; H. Chinaei; A. Vann; N. Vogler; T. Bocklet; M. Cernak; J. Hannink; Elmar Nöth;NeuroSpeech is a software for modeling pathological speech signals considering different speech dimensions: phonation, articulation, prosody, and intelligibility. Although it was developed to model dysarthric speech signals from Parkinson’s patients, its structure allows other computer scientists or developers to include other pathologies and/or measures. Different tasks can be performed: (1) modeling of the signals considering the aforementioned speech dimensions, (2) automatic discrimination of Parkinson’s vs. non-Parkinson’s, and (3) prediction of the neurological state according to the Unified Parkinson’s Disease Rating Scale (UPDRS) score. The prediction of the dysarthria level according to the Frenchay Dysarthria Assessment scale is also provided. Keywords: Speech processing, Dysarthria, Parkinson’s disease, Phonation, Articulation, Prosody, Intelligibility, Python, Software
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=10.1016/j.softx.2017.08.004&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess Routesgold 2 citations 2 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=10.1016/j.softx.2017.08.004&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu
Loading
description Publicationkeyboard_double_arrow_right Preprint 2021Publisher:Cold Spring Harbor Laboratory Romain Lopez; Baoguo Li; Hadas Keren-Shaul; Pierre Boyeau; Kedmi M; David Pilzer; Adam Jelinski; Eyal David; Allon Wagner; Addad Y; Michael I. Jordan; Ido Amit; Nir Yosef;AbstractThe function of mammalian cells is largely influenced by their tissue microenvironment. Advances in spatial transcriptomics open the way for studying these important determinants of cellular function by enabling a transcriptome-wide evaluation of gene expressionin situ. A critical limitation of the current technologies, however, is that their resolution is limited to niches (spots) of sizes well beyond that of a single cell, thus providing measurements for cell aggregates which may mask critical interactions between neighboring cells of different types. While joint analysis with single-cell RNA-sequencing (scRNA-seq) can be leveraged to alleviate this problem, current analyses are limited to a discrete view of cell type proportion inside every spot. This limitation becomes critical in the common case where, even within a cell type, there is a continuum of cell states that cannot be clearly demarcated but reflects important differences in the way cells function and interact with their surroundings. To address this, we developed Deconvolution of Spatial Transcriptomics profiles using Variational Inference (DestVI), a probabilistic method for multi-resolution analysis for spatial transcriptomics that explicitly models continuous variation within cell types. Using simulations, we demonstrate that DestVI is capable of providing higher resolution compared to the existing methods and that it can estimate gene expression by every cell type inside every spot. We then introduce an automated pipeline that uses DestVI for analysis of single tissue slices and comparison between tissues. We apply this pipeline to study the immune crosstalk within lymph nodes to infection and explore the spatial organization of a mouse tumor model. In both cases, we demonstrate that DestVI can provide a high resolution and accurate spatial characterization of the cellular organization of these tissues, and that it is capable of identifying important cell-type-specific changes in gene expression - between different tissue regions or between conditions. DestVI is available as an open-source software package in the scvi-tools codebase (https://scvi-tools.org).
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=10.1101/2021.05.10.443517&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu20 citations 20 popularity Top 10% influence Average impulse Top 10% 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=10.1101/2021.05.10.443517&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2020 EnglishPublisher:Frontiers Media S.A. Authors: Paraskevi Manolaki; Paraskevi Manolaki; Georgia Tooulakou; Caroline Urup Byberg; +4 AuthorsParaskevi Manolaki; Paraskevi Manolaki; Georgia Tooulakou; Caroline Urup Byberg; Franziska Eller; Brian K. Sorrell; Maria I. Klapa; Tenna Riis;Amphibious plants, living in land-water ecotones, have to cope with challenging and continuously changing growth conditions in their habitats with respect to nutrient and light availability. They have thus evolved a variety of mechanisms to tolerate and adapt to these changes. Therefore, the study of these plants is a major area of ecophysiology and environmental ecological research. However, our understanding of their capacity for physiological adaptation and tolerance remains limited and requires systemic approaches for comprehensive analyses. To this end, in this study, we have conducted a mesocosm experiment to analyze the response of Butomus umbellatus, a common amphibious species in Denmark, to nutrient enrichment and shading. Our study follows a systematic integration of morphological (including plant height, leaf number, and biomass accumulation), ecophysiological (photosynthesis-irradiance responses, leaf pigment content, and C and N content in plant organs), and leaf metabolomic measurements using gas chromatography-mass spectrometry (39 mainly primary metabolites), based on bioinformatic methods. No studies of this type have been previously reported for this plant species. We observed that B. umbellatus responds to nutrient enrichment and light reduction through different mechanisms and were able to identify its nutrient enrichment acclimation threshold within the applied nutrient gradient. Up to that threshold, the morpho-physiological response to nutrient enrichment was profound, indicating fast-growing trends (higher growth rates and biomass accumulation), but only few parameters changed significantly from light to shade [specific leaf area (SLA); quantum yield (φ)]. Metabolomic analysis supported the morpho-physiological results regarding nutrient overloading, indicating also subtle changes due to shading not directly apparent in the other measurements. The combined profile analysis revealed leaf metabolite and morpho-physiological parameter associations. In this context, leaf lactate, currently of uncertain role in higher plants, emerged as a shading acclimation biomarker, along with SLA and φ. The study enhances both the ecophysiology methodological toolbox and our knowledge of the adaptive capacity of amphibious species. It demonstrates that the educated combination of physiological with metabolomic measurements using bioinformatic approaches is a promising approach for ecophysiology research, enabling the elucidation of discriminatory metabolic shifts to be used for early diagnosis and even prognosis of natural ecosystem responses to climate change.
Frontiers in Plant S... arrow_drop_down Frontiers in Plant ScienceArticle . 2020Full-Text: http://europepmc.org/articles/PMC7772459Data 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=10.3389/fpls.2020.581787&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess Routesgold 2 citations 2 popularity Average influence Average impulse Average Powered by BIP!more_vert Frontiers in Plant S... arrow_drop_down Frontiers in Plant ScienceArticle . 2020Full-Text: http://europepmc.org/articles/PMC7772459Data 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=10.3389/fpls.2020.581787&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Other literature type 2010 FrancePublisher:Wiley Fabrice Legeai; Shuji Shigenobu; Jean-Pierre Gauthier; John K. Colbourne; Claude Rispe; Olivier Collin; Stephen Richards; Alex C.C. Wilson; Terence Murphy; Denis Tagu;AbstractAphidBase is a centralized bioinformatic resource that was developed to facilitate community annotation of the pea aphid genome by the International Aphid Genomics Consortium (IAGC). The AphidBase Information System designed to organize and distribute genomic data and annotations for a large international community was constructed using open source software tools from the Generic Model Organism Database (GMOD). The system includes Apollo and GBrowse utilities as well as a wiki, blast search capabilities and a full text search engine. AphidBase strongly supported community cooperation and coordination in the curation of gene models during community annotation of the pea aphid genome. AphidBase can be accessed at http://www.aphidbase.com.
Insect Molecular Bio... arrow_drop_down Insect Molecular BiologyArticle . 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=10.1111/j.1365-2583.2009.00930.x&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen bronze 104 citations 104 popularity Top 10% influence Top 10% impulse Top 1% Powered by BIP!more_vert Insect Molecular Bio... arrow_drop_down Insect Molecular BiologyArticle . 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=10.1111/j.1365-2583.2009.00930.x&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Preprint , Article , Other literature type 2020 GermanyPublisher:Cold Spring Harbor Laboratory Authors: Dominik Kopczynski; Nils Hoffmann; Bing Peng; Robert Ahrends;Dominik Kopczynski; Nils Hoffmann; Bing Peng; Robert Ahrends;We introduce Goslin, a polyglot grammar for common lipid shorthand nomenclatures based on the LIPID MAPS nomenclature and the shorthand nomenclature established by Liebisch and coauthors and used by LipidHome and SwissLipids. Goslin was designed to address the following pressing issues in the lipidomics field: (1) to simplify the implementation of lipid name handling for developers of mass spectrometry-based lipidomics tools, (2) to offer a tool that unifies and normalizes the main existing lipid name dialects enabling a lipidomics analysis in a high-throughput fashion, and (3) to provide a consistent mapping from lipid shorthand names to lipid building blocks and structural properties. We provide implementations of Goslin in four major programming languages, namely, C++, Java, Python 3, and R to kick-start adoption and integration. Further, we set up a web service for users to work with Goslin directly. All implementations are available free of charge under a permissive open source license.
bioRxiv arrow_drop_down bioRxivPreprint . 2020Europe PubMed CentralArticle . 2020Full-Text: http://europepmc.org/articles/PMC7467413Data sources: PubMed CentralPublications at Bielefeld UniversityOther literature type . 2020License: "In Copyright" Rights StatementData sources: Publications at Bielefeld Universityadd 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=10.1101/2020.04.17.046656&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen hybrid 14 citations 14 popularity Top 10% influence Average impulse Top 10% Powered by BIP!more_vert bioRxiv arrow_drop_down bioRxivPreprint . 2020Europe PubMed CentralArticle . 2020Full-Text: http://europepmc.org/articles/PMC7467413Data sources: PubMed CentralPublications at Bielefeld UniversityOther literature type . 2020License: "In Copyright" Rights StatementData sources: Publications at Bielefeld Universityadd 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=10.1101/2020.04.17.046656&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2021Publisher:Oxford University Press (OUP) Fernando Pozo; Laura Martinez-Gomez; Thomas A Walsh; Jose Manuel Rodriguez; Tomás Di Domenico; Federico Abascal; Jesús Vázquez; Michael L. Tress;AbstractAlternative splicing of messenger RNA can generate an array of mature transcripts, but it is not clear how many go on to produce functionally relevant protein isoforms. There is only limited evidence for alternative proteins in proteomics analyses and data from population genetic variation studies indicate that most alternative exons are evolving neutrally. Determining which transcripts produce biologically important isoforms is key to understanding isoform function and to interpreting the real impact of somatic mutations and germline variations. Here we have developed a method, TRIFID, to classify the functional importance of splice isoforms. TRIFID was trained on isoforms detected in large-scale proteomics analyses and distinguishes these biologically important splice isoforms with high confidence. Isoforms predicted as functionally important by the algorithm had measurable cross species conservation and significantly fewer broken functional domains. Additionally, exons that code for these functionally important protein isoforms are under purifying selection, while exons from low scoring transcripts largely appear to be evolving neutrally. TRIFID has been developed for the human genome, but it could in principle be applied to other well-annotated species. We believe that this method will generate valuable insights into the cellular importance of alternative splicing.
Europe PubMed Centra... arrow_drop_down Europe PubMed CentralArticle . 2021Full-Text: http://europepmc.org/articles/PMC8140736Data sources: PubMed CentralNAR Genomics and BioinformaticsArticle . 2021 . Peer-reviewedLicense: CC BY NCData 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=10.1093/nargab/lqab044&type=result"></script>'); --> </script>
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 . 2021Full-Text: http://europepmc.org/articles/PMC8140736Data sources: PubMed CentralNAR Genomics and BioinformaticsArticle . 2021 . Peer-reviewedLicense: CC BY NCData 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=10.1093/nargab/lqab044&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2018Publisher:Springer Science and Business Media LLC Authors: Abhik Seal; David J. Wild;Abhik Seal; David J. Wild;Abstract Background Netpredictor is an R package for prediction of missing links in any given unipartite or bipartite network. The package provides utilities to compute missing links in a bipartite and well as unipartite networks using Random Walk with Restart and Network inference algorithm and a combination of both. The package also allows computation of Bipartite network properties, visualization of communities for two different sets of nodes, and calculation of significant interactions between two sets of nodes using permutation based testing. The application can also be used to search for top-K shortest paths between interactome and use enrichment analysis for disease, pathway and ontology. The R standalone package (including detailed introductory vignettes) and associated R Shiny web application is available under the GPL-2 Open Source license and is freely available to download. Results We compared different algorithms performance in different small datasets and found random walk supersedes rest of the algorithms. The package is developed to perform network based prediction of unipartite and bipartite networks and use the results to understand the functionality of proteins in an interactome using enrichment analysis. Conclusion The rapid application development envrionment like shiny, helps non programmers to develop fast rich visualization apps and we beleieve it would continue to grow in future with further enhancements. We plan to update our algorithms in the package in near future and help scientist to analyse data in a much streamlined fashion.
Europe PubMed Centra... arrow_drop_down Europe PubMed CentralArticle . 2018Full-Text: http://europepmc.org/articles/PMC6047136Data 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/s12859-018-2254-7&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen gold 14 citations 14 popularity Top 10% influence Average impulse Top 10% Powered by BIP!more_vert Europe PubMed Centra... arrow_drop_down Europe PubMed CentralArticle . 2018Full-Text: http://europepmc.org/articles/PMC6047136Data 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/s12859-018-2254-7&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2012Publisher:Public Library of Science (PLoS) Funded by:NIH | Translational Research at..., NIH | Semantic Approaches to Ph..., NIH | CORE--COMPUTATIONAL SCIEN...NIH| Translational Research at The University of Chicago (UL1) ,NIH| Semantic Approaches to Phenotypic Databases Analyses ,NIH| CORE--COMPUTATIONAL SCIENCESXinan, Yang; Kelly, Regan; Yong, Huang; Qingbei, Zhang; Jianrong, Li; Tanguy Y, Seiwert; Ezra E W, Cohen; H Rosie, Xing; Yves A, Lussier;Gene expression signatures that are predictive of therapeutic response or prognosis are increasingly useful in clinical care; however, mechanistic (and intuitive) interpretation of expression arrays remains an unmet challenge. Additionally, there is surprisingly little gene overlap among distinct clinically validated expression signatures. These “causality challenges” hinder the adoption of signatures as compared to functionally well-characterized single gene biomarkers. To increase the utility of multi-gene signatures in survival studies, we developed a novel approach to generate “personal mechanism signatures” of molecular pathways and functions from gene expression arrays. FAIME, the Functional Analysis of Individual Microarray Expression, computes mechanism scores using rank-weighted gene expression of an individual sample. By comparing head and neck squamous cell carcinoma (HNSCC) samples with non-tumor control tissues, the precision and recall of deregulated FAIME-derived mechanisms of pathways and molecular functions are comparable to those produced by conventional cohort-wide methods (e.g. GSEA). The overlap of “Oncogenic FAIME Features of HNSCC” (statistically significant and differentially regulated FAIME-derived genesets representing GO functions or KEGG pathways derived from HNSCC tissue) among three distinct HNSCC datasets (pathways:46%, p<0.001) is more significant than the gene overlap (genes:4%). These Oncogenic FAIME Features of HNSCC can accurately discriminate tumors from control tissues in two additional HNSCC datasets (n = 35 and 91, F-accuracy = 100% and 97%, empirical p<0.001, area under the receiver operating characteristic curves = 99% and 92%), and stratify recurrence-free survival in patients from two independent studies (p = 0.0018 and p = 0.032, log-rank). Previous approaches depending on group assignment of individual samples before selecting features or learning a classifier are limited by design to discrete-class prediction. In contrast, FAIME calculates mechanism profiles for individual patients without requiring group assignment in validation sets. FAIME is more amenable for clinical deployment since it translates the gene-level measurements of each given sample into pathways and molecular function profiles that can be applied to analyze continuous phenotypes in clinical outcome studies (e.g. survival time, tumor volume). Author Summary Clinical utilization of multi-gene expression signatures that are predictive of therapeutic response has been steadily increasing, however, interpretation of such results remains challenging because multi-gene signatures, generated from analyzing different patient cohorts, tend to be equally predictive but contain minimal overlap. Whereas pathway-level analyses of expression arrays show promise for generating clinically meaningful mechanistic signatures, current approaches do not permit single-patient based analyses that are independent of cross-group calculations. To bridge the gap between deterministic biological mechanisms of single-gene biomarkers and the statistical predictive power of multi-gene signatures that are disconnected from mechanisms, we developed FAIME, a novel method that transforms microarray gene expression data into individualized patient profiles of molecular mechanisms. We have validated its capability for predicting clinical outcomes, including cancer patient samples derived from six different clinical trial cohorts of head and neck cancers. This method provides opportunities to harness an untapped resource for personal genomics: clinical evaluation and testing of individually interpretable mechanistic profiles derived from gene expression arrays.
Europe PubMed Centra... arrow_drop_down Europe PubMed CentralArticle . 2012Full-Text: http://europepmc.org/articles/PMC3266878Data 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=10.1371/journal.pcbi.1002350&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen gold 66 citations 66 popularity Top 10% influence Top 10% impulse Top 10% Powered by BIP!more_vert Europe PubMed Centra... arrow_drop_down Europe PubMed CentralArticle . 2012Full-Text: http://europepmc.org/articles/PMC3266878Data 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=10.1371/journal.pcbi.1002350&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2018 NetherlandsPublisher:Springer Science and Business Media LLC Singh, Gurnoor; Kuzniar, Arnold; van Mulligen, Erik M.; Gavai, Anand; Bachem, Christian W.; Visser, Richard G.F.; Finkers, Richard;Background A quantitative trait locus (QTL) is a genomic region that correlates with a phenotype. Most of the experimental information about QTL mapping studies is described in tables of scientific publications. Traditional text mining techniques aim to extract information from unstructured text rather than from tables. We present QTLTableMiner++ (QTM), a table mining tool that extracts and semantically annotates QTL information buried in (heterogeneous) tables of plant science literature. QTM is a command line tool written in the Java programming language. This tool takes scientific articles from the Europe PMC repository as input, extracts QTL tables using keyword matching and ontology-based concept identification. The tables are further normalized using rules derived from table properties such as captions, column headers and table footers. Furthermore, table columns are classified into three categories namely column descriptors, properties and values based on column headers and data types of cell entries. Abbreviations found in the tables are expanded using the Schwartz and Hearst algorithm. Finally, the content of QTL tables is semantically enriched with domain-specific ontologies (e.g. Crop Ontology, Plant Ontology and Trait Ontology) using the Apache Solr search platform and the results are stored in a relational database and a text file. Results The performance of the QTM tool was assessed by precision and recall based on the information retrieved from two manually annotated corpora of open access articles, i.e. QTL mapping studies in tomato (Solanum lycopersicum) and in potato (S. tuberosum). In summary, QTM detected QTL statements in tomato with 74.53% precision and 92.56% recall and in potato with 82.82% precision and 98.94% recall. Conclusion QTM is a unique tool that aids in providing QTL information in machine-readable and semantically interoperable formats. Electronic supplementary material The online version of this article (10.1186/s12859-018-2165-7) contains supplementary material, which is available to authorized users.
NARCIS; Research@WUR arrow_drop_down NARCIS; Research@WUROther literature type . Article . 2018License: CC BYFull-Text: https://edepot.wur.nl/452409Europe PubMed CentralArticle . 2018Full-Text: http://europepmc.org/articles/PMC5970438Data 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/s12859-018-2165-7&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen gold 8 citations 8 popularity Average influence Average impulse Top 10% Powered by BIP!more_vert NARCIS; Research@WUR arrow_drop_down NARCIS; Research@WUROther literature type . Article . 2018License: CC BYFull-Text: https://edepot.wur.nl/452409Europe PubMed CentralArticle . 2018Full-Text: http://europepmc.org/articles/PMC5970438Data 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/s12859-018-2165-7&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Other literature type , Presentation 2020 EnglishPublisher:Zenodo Authors: Zogopoulos, Vasileios; Malatras, Apostolos; Vasileiou, Christos; Kyriakidis, Konstantinos V.; +1 AuthorsZogopoulos, Vasileios; Malatras, Apostolos; Vasileiou, Christos; Kyriakidis, Konstantinos V.; Michalopoulos, Ioannis;Creation of a WebTool based on human gene coexpression analysis, that discovers functional partners to a gene of interest or proposes biological roles to genes of unknown function
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=10.5281/zenodo.4042975&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen 0 citations 0 popularity Average influence Average impulse Average Powered by BIP!visibility 91visibility views 91 download downloads 13 Powered bymore_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=10.5281/zenodo.4042975&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2018Publisher:Elsevier BV Authors: Juan Rafael Orozco-Arroyave; Juan Camilo Vásquez-Correa; Jesús Francisco Vargas-Bonilla; R. Arora; +12 AuthorsJuan Rafael Orozco-Arroyave; Juan Camilo Vásquez-Correa; Jesús Francisco Vargas-Bonilla; R. Arora; N. Dehak; P.S. Nidadavolu; H. Christensen; F. Rudzicz; M. Yancheva; H. Chinaei; A. Vann; N. Vogler; T. Bocklet; M. Cernak; J. Hannink; Elmar Nöth;NeuroSpeech is a software for modeling pathological speech signals considering different speech dimensions: phonation, articulation, prosody, and intelligibility. Although it was developed to model dysarthric speech signals from Parkinson’s patients, its structure allows other computer scientists or developers to include other pathologies and/or measures. Different tasks can be performed: (1) modeling of the signals considering the aforementioned speech dimensions, (2) automatic discrimination of Parkinson’s vs. non-Parkinson’s, and (3) prediction of the neurological state according to the Unified Parkinson’s Disease Rating Scale (UPDRS) score. The prediction of the dysarthria level according to the Frenchay Dysarthria Assessment scale is also provided. Keywords: Speech processing, Dysarthria, Parkinson’s disease, Phonation, Articulation, Prosody, Intelligibility, Python, Software
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=10.1016/j.softx.2017.08.004&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess Routesgold 2 citations 2 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=10.1016/j.softx.2017.08.004&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu