Journal article

MCRiceRepGP: a framework for identification of sexual reproduction associated coding and lincRNA genes in rice

Agnieszka Golicz, Prem Bhalla, Mohan Singh

Published : 2018


Sexual reproduction in plants underpins global food production and evolution. It is a complex process, requiring intricate signalling pathways integrating a multitude of internal and external cues. However, key players and especially non-coding genes controlling plant sexual reproduction remain elusive. We report the development of MCRiceRepGP a novel machine learning framework, which integrates genomic, transcriptomic, homology and available phenotypic evidence and employs multi-criteria decision analysis and machine learning to predict coding and non-coding genes involved in rice sexual reproduction. The rice genome was re-annotated using deep sequencing transcriptomic data from reproducti..

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