On the performance of de novo pathway enrichment

Computational biology: Evaluation of network-based pathway enrichment tools De novo pathway enrichment methods are essential to understand disease complexity. They can uncover disease-specific functional modules by integrating molecular interaction networks with expression profiles. However, how sho...

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Autores principales:	Richa Batra, Nicolas Alcaraz, Kevin Gitzhofer, Josch Pauling, Henrik J. Ditzel, Marc Hellmuth, Jan Baumbach, Markus List
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2017
Materias:	Biology (General) QH301-705.5
Acceso en línea:	https://doaj.org/article/d4aeb2316347474c8564b07783489ae1
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spelling	oai:doaj.org-article:d4aeb2316347474c8564b07783489ae12021-12-02T16:08:59ZOn the performance of de novo pathway enrichment10.1038/s41540-017-0007-22056-7189https://doaj.org/article/d4aeb2316347474c8564b07783489ae12017-03-01T00:00:00Zhttps://doi.org/10.1038/s41540-017-0007-2https://doaj.org/toc/2056-7189Computational biology: Evaluation of network-based pathway enrichment tools De novo pathway enrichment methods are essential to understand disease complexity. They can uncover disease-specific functional modules by integrating molecular interaction networks with expression profiles. However, how should researchers choose one method out of several? In this article, a group of scientists from Denmark and Germany presents the first attempt to quantitatively evaluate existing methods. This framework will help the biomedical community to find the appropriate tool(s) for their data. They created synthetic gold standards and simulated expression profiles to perform a systematic assessment of various tools. They observed that the choice of interaction network, parameter settings, preprocessing of expression data and statistical properties of the expression profiles influence the results to a large extent. The results reveal strengths and limitations of the individual methods and suggest using two or more tools to obtain comprehensive disease-modules.Richa BatraNicolas AlcarazKevin GitzhoferJosch PaulingHenrik J. DitzelMarc HellmuthJan BaumbachMarkus ListNature PortfolioarticleBiology (General)QH301-705.5ENnpj Systems Biology and Applications, Vol 3, Iss 1, Pp 1-8 (2017)
institution	DOAJ
collection	DOAJ
language	EN
topic	Biology (General) QH301-705.5
spellingShingle	Biology (General) QH301-705.5 Richa Batra Nicolas Alcaraz Kevin Gitzhofer Josch Pauling Henrik J. Ditzel Marc Hellmuth Jan Baumbach Markus List On the performance of de novo pathway enrichment
description	Computational biology: Evaluation of network-based pathway enrichment tools De novo pathway enrichment methods are essential to understand disease complexity. They can uncover disease-specific functional modules by integrating molecular interaction networks with expression profiles. However, how should researchers choose one method out of several? In this article, a group of scientists from Denmark and Germany presents the first attempt to quantitatively evaluate existing methods. This framework will help the biomedical community to find the appropriate tool(s) for their data. They created synthetic gold standards and simulated expression profiles to perform a systematic assessment of various tools. They observed that the choice of interaction network, parameter settings, preprocessing of expression data and statistical properties of the expression profiles influence the results to a large extent. The results reveal strengths and limitations of the individual methods and suggest using two or more tools to obtain comprehensive disease-modules.
format	article
author	Richa Batra Nicolas Alcaraz Kevin Gitzhofer Josch Pauling Henrik J. Ditzel Marc Hellmuth Jan Baumbach Markus List
author_facet	Richa Batra Nicolas Alcaraz Kevin Gitzhofer Josch Pauling Henrik J. Ditzel Marc Hellmuth Jan Baumbach Markus List
author_sort	Richa Batra
title	On the performance of de novo pathway enrichment
title_short	On the performance of de novo pathway enrichment
title_full	On the performance of de novo pathway enrichment
title_fullStr	On the performance of de novo pathway enrichment
title_full_unstemmed	On the performance of de novo pathway enrichment
title_sort	on the performance of de novo pathway enrichment
publisher	Nature Portfolio
publishDate	2017
url	https://doaj.org/article/d4aeb2316347474c8564b07783489ae1
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On the performance of de novo pathway enrichment

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