In silico Pathway Activation Network Decomposition Analysis (iPANDA) as a method for biomarker development
Pathway analysis aids interpretation of large-scale gene expression data, but existing algorithms fall short of providing robust pathway identification. The method introduced here includes coexpression analysis and gene importance estimation to robustly identify relevant pathways and biomarkers for...
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Nature Portfolio
2016
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oai:doaj.org-article:2c57748e19064775b999e9d5f44aa2b92021-12-02T14:39:52ZIn silico Pathway Activation Network Decomposition Analysis (iPANDA) as a method for biomarker development10.1038/ncomms134272041-1723https://doaj.org/article/2c57748e19064775b999e9d5f44aa2b92016-11-01T00:00:00Zhttps://doi.org/10.1038/ncomms13427https://doaj.org/toc/2041-1723Pathway analysis aids interpretation of large-scale gene expression data, but existing algorithms fall short of providing robust pathway identification. The method introduced here includes coexpression analysis and gene importance estimation to robustly identify relevant pathways and biomarkers for patient stratification.Ivan V. OzerovKsenia V. LezhninaEvgeny IzumchenkoArtem V. ArtemovSergey MedintsevQuentin VanhaelenAlexander AliperJan VijgAndreyan N. OsipovIvan LabatMichael D. WestAnton BuzdinCharles R. CantorYuri NikolskyNikolay BorisovIrina IrincheevaEdward KhokhlovichDavid SidranskyMiguel Luiz CamargoAlex ZhavoronkovNature PortfolioarticleScienceQENNature Communications, Vol 7, Iss 1, Pp 1-11 (2016) |
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Science Q |
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Science Q Ivan V. Ozerov Ksenia V. Lezhnina Evgeny Izumchenko Artem V. Artemov Sergey Medintsev Quentin Vanhaelen Alexander Aliper Jan Vijg Andreyan N. Osipov Ivan Labat Michael D. West Anton Buzdin Charles R. Cantor Yuri Nikolsky Nikolay Borisov Irina Irincheeva Edward Khokhlovich David Sidransky Miguel Luiz Camargo Alex Zhavoronkov In silico Pathway Activation Network Decomposition Analysis (iPANDA) as a method for biomarker development |
description |
Pathway analysis aids interpretation of large-scale gene expression data, but existing algorithms fall short of providing robust pathway identification. The method introduced here includes coexpression analysis and gene importance estimation to robustly identify relevant pathways and biomarkers for patient stratification. |
format |
article |
author |
Ivan V. Ozerov Ksenia V. Lezhnina Evgeny Izumchenko Artem V. Artemov Sergey Medintsev Quentin Vanhaelen Alexander Aliper Jan Vijg Andreyan N. Osipov Ivan Labat Michael D. West Anton Buzdin Charles R. Cantor Yuri Nikolsky Nikolay Borisov Irina Irincheeva Edward Khokhlovich David Sidransky Miguel Luiz Camargo Alex Zhavoronkov |
author_facet |
Ivan V. Ozerov Ksenia V. Lezhnina Evgeny Izumchenko Artem V. Artemov Sergey Medintsev Quentin Vanhaelen Alexander Aliper Jan Vijg Andreyan N. Osipov Ivan Labat Michael D. West Anton Buzdin Charles R. Cantor Yuri Nikolsky Nikolay Borisov Irina Irincheeva Edward Khokhlovich David Sidransky Miguel Luiz Camargo Alex Zhavoronkov |
author_sort |
Ivan V. Ozerov |
title |
In silico Pathway Activation Network Decomposition Analysis (iPANDA) as a method for biomarker development |
title_short |
In silico Pathway Activation Network Decomposition Analysis (iPANDA) as a method for biomarker development |
title_full |
In silico Pathway Activation Network Decomposition Analysis (iPANDA) as a method for biomarker development |
title_fullStr |
In silico Pathway Activation Network Decomposition Analysis (iPANDA) as a method for biomarker development |
title_full_unstemmed |
In silico Pathway Activation Network Decomposition Analysis (iPANDA) as a method for biomarker development |
title_sort |
in silico pathway activation network decomposition analysis (ipanda) as a method for biomarker development |
publisher |
Nature Portfolio |
publishDate |
2016 |
url |
https://doaj.org/article/2c57748e19064775b999e9d5f44aa2b9 |
work_keys_str_mv |
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