Comparing enrichment analysis and machine learning for identifying gene properties that discriminate between gene classes.

Fabris, Fabio; Palmer, Daniel; de Magalhães, João Pedro; Freitas, Alex A

Fabris, Fabio; Palmer, Daniel; de Magalhães, João Pedro; Freitas, Alex A.

Affiliation

Fabris F; School of Computing, University of Kent, Kent, CT2 7NF, UK.
Palmer D; Integrative Genomics of Ageing Group, Institute of Ageing and Chronic Disease, University of Liverpool, Liverpool, UK.
de Magalhães JP; Integrative Genomics of Ageing Group, Institute of Ageing and Chronic Disease, University of Liverpool, Liverpool, UK.
Freitas AA; School of Computing, University of Kent, Kent, CT2 7NF, UK.

Brief Bioinform ; 21(3): 803-814, 2020 05 21.

Article in En | MEDLINE | ID: mdl-30895300

Subject(s)

Computational Biology/methods; Gene Expression Profiling/methods; Machine Learning; Algorithms

Key words

classification; enrichment analysis; machine learning; statistical hypothesis testing

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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Computational Biology / Gene Expression Profiling / Machine Learning Type of study: Guideline / Prognostic_studies Language: En Journal: Brief Bioinform Journal subject: BIOLOGIA / INFORMATICA MEDICA Year: 2020 Document type: Article Affiliation country: United kingdom Country of publication: United kingdom

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