A step toward a reinforcement learning de novo genome assembler

arXiv:2102.02649v4 Announce Type: replace-cross
Abstract: De novo genome assembly is a relevant but computationally complex task in genomics. Although de novo assemblers have been used successfully in several genomics projects, there is still no 'best assembler', and the choice and setup of assemblers still rely on bioinformatics experts. Thus, as with other computationally complex problems, machine learning may emerge as an alternative (or complementary) way for developing more accurate and automated assemblers. Reinforcement learning has proven promising for solving complex …

abstract arxiv assembly bioinformatics cs.ai cs.lg experts genome genomics projects q-bio.gn reinforcement reinforcement learning setup type