Machine learning and genome annotation: a match meant to be?

By its very nature, genomics produces large, high-dimensional datasets that are well suited to analysis by machine learning approaches. Here, we explain some key aspects of machine learning that make it useful for genome annotation, with illustrative examples from ENCODE.

Detalles Bibliográficos
Autores principales: Yip, Kevin Y, Cheng, Chao, Gerstein, Mark
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2013
Materias:
Review
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4053789/
https://www.ncbi.nlm.nih.gov/pubmed/23731483
http://dx.doi.org/10.1186/gb-2013-14-5-205
Descripción
Sumario:By its very nature, genomics produces large, high-dimensional datasets that are well suited to analysis by machine learning approaches. Here, we explain some key aspects of machine learning that make it useful for genome annotation, with illustrative examples from ENCODE.

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