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description Publicationkeyboard_double_arrow_right Article 2012Publisher:Oxford University Press (OUP) Funded by:EC | ESNATSEC| ESNATSAuthors: Kolde, R.; Laur, S.; Adler, P.; Vilo, J.;Kolde, R.; Laur, S.; Adler, P.; Vilo, J.;Abstract Motivation: The continued progress in developing technological platforms, availability of many published experimental datasets, as well as different statistical methods to analyze those data have allowed approaching the same research question using various methods simultaneously. To get the best out of all these alternatives, we need to integrate their results in an unbiased manner. Prioritized gene lists are a common result presentation method in genomic data analysis applications. Thus, the rank aggregation methods can become a useful and general solution for the integration task. Results: Standard rank aggregation methods are often ill-suited for biological settings where the gene lists are inherently noisy. As a remedy, we propose a novel robust rank aggregation (RRA) method. Our method detects genes that are ranked consistently better than expected under null hypothesis of uncorrelated inputs and assigns a significance score for each gene. The underlying probabilistic model makes the algorithm parameter free and robust to outliers, noise and errors. Significance scores also provide a rigorous way to keep only the statistically relevant genes in the final list. These properties make our approach robust and compelling for many settings. Availability: All the methods are implemented as a GNU R package RobustRankAggreg, freely available at the Comprehensive R Archive Network http://cran.r-project.org/. Contact: vilo@ut.ee Supplementary information Supplementary data are available at Bioinformatics online.
Europe PubMed Centra... arrow_drop_down Europe PubMed CentralArticle . 2012Full-Text: http://europepmc.org/articles/PMC3278763Data 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=10.1093/bioinformatics/btr709&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen hybrid 759 citations 759 popularity Top 0.1% influence Top 1% impulse Top 1% Powered by BIP!more_vert Europe PubMed Centra... arrow_drop_down Europe PubMed CentralArticle . 2012Full-Text: http://europepmc.org/articles/PMC3278763Data 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=10.1093/bioinformatics/btr709&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Preprint 2021Publisher:Cold Spring Harbor Laboratory Itsuki Sugita; Shohei Matsuyama; Hiroki Dobashi; Daisuke Komura; Shumpei Ishikawa;Abstract Summary Here, we present Viola, a Python package that provides structural variant (SV; large scale genome DNA variations that can result in disease, e.g. cancer) signature analytical functions and utilities for custom SV classification, merging multi-SV-caller output files and SV annotation. We demonstrate that Viola can extract biologically meaningful SV signatures from publicly available SV data for cancer and we evaluate the computational time necessary for annotation of the data. Availability and implementation Viola is available on pip (https://pypi.org/project/Viola-SV/) and the source code is on GitHub (https://github.com/dermasugita/Viola-SV). Supplementary information Supplementary data are available at Bioinformatics online.
Europe PubMed Centra... arrow_drop_down Europe PubMed CentralArticle . 2021Full-Text: http://europepmc.org/articles/PMC8723148Data 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=10.1101/2021.03.31.437648&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen hybrid 3 citations 3 popularity Average influence Average impulse Average Powered by BIP!more_vert Europe PubMed Centra... arrow_drop_down Europe PubMed CentralArticle . 2021Full-Text: http://europepmc.org/articles/PMC8723148Data 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=10.1101/2021.03.31.437648&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2015Funded by:EC | iManageCancer, EC | P-MEDICINEEC| iManageCancer ,EC| P-MEDICINESfakianaki, Pepi; Koumakis, Lefteris; Sfakianakis, Stelios; Iatraki, Galatia; Zacharioudakis, Giorgos; Graf, Norbert; Marias, Kostas; Tsiknakis, Manolis;Background A plethora of publicly available biomedical resources do currently exist and are constantly increasing at a fast rate. In parallel, specialized repositories are been developed, indexing numerous clinical and biomedical tools. The main drawback of such repositories is the difficulty in locating appropriate resources for a clinical or biomedical decision task, especially for non-Information Technology expert users. In parallel, although NLP research in the clinical domain has been active since the 1960s, progress in the development of NLP applications has been slow and lags behind progress in the general NLP domain. The aim of the present study is to investigate the use of semantics for biomedical resources annotation with domain specific ontologies and exploit Natural Language Processing methods in empowering the non-Information Technology expert users to efficiently search for biomedical resources using natural language. Methods A Natural Language Processing engine which can “translate” free text into targeted queries, automatically transforming a clinical research question into a request description that contains only terms of ontologies, has been implemented. The implementation is based on information extraction techniques for text in natural language, guided by integrated ontologies. Furthermore, knowledge from robust text mining methods has been incorporated to map descriptions into suitable domain ontologies in order to ensure that the biomedical resources descriptions are domain oriented and enhance the accuracy of services discovery. The framework is freely available as a web application at (http://calchas.ics.forth.gr/). Results For our experiments, a range of clinical questions were established based on descriptions of clinical trials from the ClinicalTrials.gov registry as well as recommendations from clinicians. Domain experts manually identified the available tools in a tools repository which are suitable for addressing the clinical questions at hand, either individually or as a set of tools forming a computational pipeline. The results were compared with those obtained from an automated discovery of candidate biomedical tools. For the evaluation of the results, precision and recall measurements were used. Our results indicate that the proposed framework has a high precision and low recall, implying that the system returns essentially more relevant results than irrelevant. Conclusions There are adequate biomedical ontologies already available, sufficiency of existing NLP tools and quality of biomedical annotation systems for the implementation of a biomedical resources discovery framework, based on the semantic annotation of resources and the use on NLP techniques. The results of the present study demonstrate the clinical utility of the application of the proposed framework which aims to bridge the gap between clinical question in natural language and efficient dynamic biomedical resources discovery. Electronic supplementary material The online version of this article (doi:10.1186/s12911-015-0200-4) contains supplementary material, which is available to authorized users.
Europe PubMed Centra... arrow_drop_down Europe PubMed CentralArticle . 2015Full-Text: http://europepmc.org/articles/PMC4591066Data sources: PubMed CentralBMC Medical Informatics and Decision Making; ZENODO; OpenAPC Global InitiativeOther literature type . Article . Conference object . 2015 . Peer-reviewedLicense: Springer TDMadd 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/s12911-015-0200-4&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen gold 28 citations 28 popularity Top 10% influence Top 10% impulse Top 10% Powered by BIP!more_vert Europe PubMed Centra... arrow_drop_down Europe PubMed CentralArticle . 2015Full-Text: http://europepmc.org/articles/PMC4591066Data sources: PubMed CentralBMC Medical Informatics and Decision Making; ZENODO; OpenAPC Global InitiativeOther literature type . Article . Conference object . 2015 . Peer-reviewedLicense: Springer TDMadd 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/s12911-015-0200-4&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu
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description Publicationkeyboard_double_arrow_right Article 2012Publisher:Oxford University Press (OUP) Funded by:EC | ESNATSEC| ESNATSAuthors: Kolde, R.; Laur, S.; Adler, P.; Vilo, J.;Kolde, R.; Laur, S.; Adler, P.; Vilo, J.;Abstract Motivation: The continued progress in developing technological platforms, availability of many published experimental datasets, as well as different statistical methods to analyze those data have allowed approaching the same research question using various methods simultaneously. To get the best out of all these alternatives, we need to integrate their results in an unbiased manner. Prioritized gene lists are a common result presentation method in genomic data analysis applications. Thus, the rank aggregation methods can become a useful and general solution for the integration task. Results: Standard rank aggregation methods are often ill-suited for biological settings where the gene lists are inherently noisy. As a remedy, we propose a novel robust rank aggregation (RRA) method. Our method detects genes that are ranked consistently better than expected under null hypothesis of uncorrelated inputs and assigns a significance score for each gene. The underlying probabilistic model makes the algorithm parameter free and robust to outliers, noise and errors. Significance scores also provide a rigorous way to keep only the statistically relevant genes in the final list. These properties make our approach robust and compelling for many settings. Availability: All the methods are implemented as a GNU R package RobustRankAggreg, freely available at the Comprehensive R Archive Network http://cran.r-project.org/. Contact: vilo@ut.ee Supplementary information Supplementary data are available at Bioinformatics online.
Europe PubMed Centra... arrow_drop_down Europe PubMed CentralArticle . 2012Full-Text: http://europepmc.org/articles/PMC3278763Data 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=10.1093/bioinformatics/btr709&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen hybrid 759 citations 759 popularity Top 0.1% influence Top 1% impulse Top 1% Powered by BIP!more_vert Europe PubMed Centra... arrow_drop_down Europe PubMed CentralArticle . 2012Full-Text: http://europepmc.org/articles/PMC3278763Data 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=10.1093/bioinformatics/btr709&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Preprint 2021Publisher:Cold Spring Harbor Laboratory Itsuki Sugita; Shohei Matsuyama; Hiroki Dobashi; Daisuke Komura; Shumpei Ishikawa;Abstract Summary Here, we present Viola, a Python package that provides structural variant (SV; large scale genome DNA variations that can result in disease, e.g. cancer) signature analytical functions and utilities for custom SV classification, merging multi-SV-caller output files and SV annotation. We demonstrate that Viola can extract biologically meaningful SV signatures from publicly available SV data for cancer and we evaluate the computational time necessary for annotation of the data. Availability and implementation Viola is available on pip (https://pypi.org/project/Viola-SV/) and the source code is on GitHub (https://github.com/dermasugita/Viola-SV). Supplementary information Supplementary data are available at Bioinformatics online.
Europe PubMed Centra... arrow_drop_down Europe PubMed CentralArticle . 2021Full-Text: http://europepmc.org/articles/PMC8723148Data 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=10.1101/2021.03.31.437648&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen hybrid 3 citations 3 popularity Average influence Average impulse Average Powered by BIP!more_vert Europe PubMed Centra... arrow_drop_down Europe PubMed CentralArticle . 2021Full-Text: http://europepmc.org/articles/PMC8723148Data 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=10.1101/2021.03.31.437648&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2015Funded by:EC | iManageCancer, EC | P-MEDICINEEC| iManageCancer ,EC| P-MEDICINESfakianaki, Pepi; Koumakis, Lefteris; Sfakianakis, Stelios; Iatraki, Galatia; Zacharioudakis, Giorgos; Graf, Norbert; Marias, Kostas; Tsiknakis, Manolis;Background A plethora of publicly available biomedical resources do currently exist and are constantly increasing at a fast rate. In parallel, specialized repositories are been developed, indexing numerous clinical and biomedical tools. The main drawback of such repositories is the difficulty in locating appropriate resources for a clinical or biomedical decision task, especially for non-Information Technology expert users. In parallel, although NLP research in the clinical domain has been active since the 1960s, progress in the development of NLP applications has been slow and lags behind progress in the general NLP domain. The aim of the present study is to investigate the use of semantics for biomedical resources annotation with domain specific ontologies and exploit Natural Language Processing methods in empowering the non-Information Technology expert users to efficiently search for biomedical resources using natural language. Methods A Natural Language Processing engine which can “translate” free text into targeted queries, automatically transforming a clinical research question into a request description that contains only terms of ontologies, has been implemented. The implementation is based on information extraction techniques for text in natural language, guided by integrated ontologies. Furthermore, knowledge from robust text mining methods has been incorporated to map descriptions into suitable domain ontologies in order to ensure that the biomedical resources descriptions are domain oriented and enhance the accuracy of services discovery. The framework is freely available as a web application at (http://calchas.ics.forth.gr/). Results For our experiments, a range of clinical questions were established based on descriptions of clinical trials from the ClinicalTrials.gov registry as well as recommendations from clinicians. Domain experts manually identified the available tools in a tools repository which are suitable for addressing the clinical questions at hand, either individually or as a set of tools forming a computational pipeline. The results were compared with those obtained from an automated discovery of candidate biomedical tools. For the evaluation of the results, precision and recall measurements were used. Our results indicate that the proposed framework has a high precision and low recall, implying that the system returns essentially more relevant results than irrelevant. Conclusions There are adequate biomedical ontologies already available, sufficiency of existing NLP tools and quality of biomedical annotation systems for the implementation of a biomedical resources discovery framework, based on the semantic annotation of resources and the use on NLP techniques. The results of the present study demonstrate the clinical utility of the application of the proposed framework which aims to bridge the gap between clinical question in natural language and efficient dynamic biomedical resources discovery. Electronic supplementary material The online version of this article (doi:10.1186/s12911-015-0200-4) contains supplementary material, which is available to authorized users.
Europe PubMed Centra... arrow_drop_down Europe PubMed CentralArticle . 2015Full-Text: http://europepmc.org/articles/PMC4591066Data sources: PubMed CentralBMC Medical Informatics and Decision Making; ZENODO; OpenAPC Global InitiativeOther literature type . Article . Conference object . 2015 . Peer-reviewedLicense: Springer TDMadd 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/s12911-015-0200-4&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen gold 28 citations 28 popularity Top 10% influence Top 10% impulse Top 10% Powered by BIP!more_vert Europe PubMed Centra... arrow_drop_down Europe PubMed CentralArticle . 2015Full-Text: http://europepmc.org/articles/PMC4591066Data sources: PubMed CentralBMC Medical Informatics and Decision Making; ZENODO; OpenAPC Global InitiativeOther literature type . Article . Conference object . 2015 . Peer-reviewedLicense: Springer TDMadd 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/s12911-015-0200-4&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu