Using deep learning to associate human genes with age-related diseases | Zendy

Fábio Fabris | Zendy; Daniel H. Palmer | Zendy; Khalid M. Salama | Zendy; João Pedro de Magalhães | Zendy; Alex A. Freitas | Zendy

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Using deep learning to associate human genes with age-related diseases

Author(s) -

Fábio Fabris,

Daniel H. Palmer,

Khalid M. Salama,

João Pedro de Magalhães,

Alex A. Freitas

Publication year - 2019

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/btz887

Subject(s) - computer science , classifier (uml) , artificial intelligence , artificial neural network , machine learning , novelty , source code , pattern recognition (psychology) , philosophy , theology , operating system

One way to identify genes possibly associated with ageing is to build a classification model (from the machine learning field) capable of classifying genes as associated with multiple age-related diseases. To build this model, we use a pre-compiled list of human genes associated with age-related diseases and apply a novel Deep Neural Network (DNN) method to find associations between gene descriptors (e.g. Gene Ontology terms, protein-protein interaction data and biological pathway information) and age-related diseases.

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