Discovering combinatorial interactions in survival data | Zendy

David A. duVerle | Zendy; Ichiro Takeuchi | Zendy; Yuko MurakamiTonami | Zendy; Kenji Kadomatsu | Zendy; Koji Tsuda | Zendy

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Discovering combinatorial interactions in survival data

Author(s) -

David A. duVerle,

Ichiro Takeuchi,

Yuko MurakamiTonami,

Kenji Kadomatsu,

Koji Tsuda

Publication year - 2013

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/btt532

Subject(s) - computer science , regularization (linguistics) , data mining , regression , path (computing) , variable (mathematics) , r package , outcome (game theory) , machine learning , artificial intelligence , mathematics , statistics , mathematical economics , programming language , mathematical analysis , computational science

Although several methods exist to relate high-dimensional gene expression data to various clinical phenotypes, finding combinations of features in such input remains a challenge, particularly when fitting complex statistical models such as those used for survival studies.

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