A step towards a reinforcement learning de novo genome assembler. (arXiv:2102.02649v3 [q-bio.GN] UPDATED)

The use of reinforcement learning has proven to be very promising for solving
complex activities without human supervision during their learning process.
However, their successful applications are predominantly focused on fictional
and entertainment problems - such as games. Based on the above, this work aims
to shed light on the application of reinforcement learning to solve this
relevant real-world problem, the genome assembly. By expanding the only
approach found in the literature that addresses this problem, we carefully
explored the …

arxiv bio genome reinforcement reinforcement learning