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Robust de novo pathway enrichment with KeyPathwayMiner 5
Identifying functional modules or novel active pathways, recently termed de novo pathway enrichment, is a computational systems biology challenge that has gained much attention during the last decade. Given a large biological interaction network, KeyPathwayMiner extracts connected subnetworks that a...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
F1000Research
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4965696/ https://www.ncbi.nlm.nih.gov/pubmed/27540470 http://dx.doi.org/10.12688/f1000research.9054.1 |
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author | Alcaraz, Nicolas List, Markus Dissing-Hansen, Martin Rehmsmeier, Marc Tan, Qihua Mollenhauer, Jan Ditzel, Henrik J. Baumbach, Jan |
author_facet | Alcaraz, Nicolas List, Markus Dissing-Hansen, Martin Rehmsmeier, Marc Tan, Qihua Mollenhauer, Jan Ditzel, Henrik J. Baumbach, Jan |
author_sort | Alcaraz, Nicolas |
collection | PubMed |
description | Identifying functional modules or novel active pathways, recently termed de novo pathway enrichment, is a computational systems biology challenge that has gained much attention during the last decade. Given a large biological interaction network, KeyPathwayMiner extracts connected subnetworks that are enriched for differentially active entities from a series of molecular profiles encoded as binary indicator matrices. Since interaction networks constantly evolve, an important question is how robust the extracted results are when the network is modified. We enable users to study this effect through several network perturbation techniques and over a range of perturbation degrees. In addition, users may now provide a gold-standard set to determine how enriched extracted pathways are with relevant genes compared to randomized versions of the original network. |
format | Online Article Text |
id | pubmed-4965696 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | F1000Research |
record_format | MEDLINE/PubMed |
spelling | pubmed-49656962016-08-17 Robust de novo pathway enrichment with KeyPathwayMiner 5 Alcaraz, Nicolas List, Markus Dissing-Hansen, Martin Rehmsmeier, Marc Tan, Qihua Mollenhauer, Jan Ditzel, Henrik J. Baumbach, Jan F1000Res Software Tool Article Identifying functional modules or novel active pathways, recently termed de novo pathway enrichment, is a computational systems biology challenge that has gained much attention during the last decade. Given a large biological interaction network, KeyPathwayMiner extracts connected subnetworks that are enriched for differentially active entities from a series of molecular profiles encoded as binary indicator matrices. Since interaction networks constantly evolve, an important question is how robust the extracted results are when the network is modified. We enable users to study this effect through several network perturbation techniques and over a range of perturbation degrees. In addition, users may now provide a gold-standard set to determine how enriched extracted pathways are with relevant genes compared to randomized versions of the original network. F1000Research 2016-06-28 /pmc/articles/PMC4965696/ /pubmed/27540470 http://dx.doi.org/10.12688/f1000research.9054.1 Text en Copyright: © 2016 Alcaraz N et al. http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Software Tool Article Alcaraz, Nicolas List, Markus Dissing-Hansen, Martin Rehmsmeier, Marc Tan, Qihua Mollenhauer, Jan Ditzel, Henrik J. Baumbach, Jan Robust de novo pathway enrichment with KeyPathwayMiner 5 |
title | Robust
de novo pathway enrichment with
KeyPathwayMiner 5
|
title_full | Robust
de novo pathway enrichment with
KeyPathwayMiner 5
|
title_fullStr | Robust
de novo pathway enrichment with
KeyPathwayMiner 5
|
title_full_unstemmed | Robust
de novo pathway enrichment with
KeyPathwayMiner 5
|
title_short | Robust
de novo pathway enrichment with
KeyPathwayMiner 5
|
title_sort | robust
de novo pathway enrichment with
keypathwayminer 5 |
topic | Software Tool Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4965696/ https://www.ncbi.nlm.nih.gov/pubmed/27540470 http://dx.doi.org/10.12688/f1000research.9054.1 |
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