Local Alignment of DNA Sequence Based on Deep Reinforcement Learning

Goal: Over the decades, there have been improvements in the sequence alignment algorithm, with significant advances in various aspects such as complexity and accuracy. However, human-defined algorithms have an explicit limitation in view of developmental completeness. This paper introduces a novel l...

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Veröffentlicht in:	IEEE open journal of engineering in medicine and biology Jg. 2; S. 170 - 178
Hauptverfasser:	Song, Yong-Joon, Cho, Dong-Ho
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	United States IEEE 01.01.2021 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Algorithms Alignment Biomedical engineering Complexity Computer applications Deep learning Deep reinforcement learning E coli Genomics Greedy algorithms Heuristic algorithms local alignment Machine learning meta learning Neural networks Nucleotide sequence Numerical analysis Reinforcement Reinforcement learning sequence alignment sequence comparison Training local alignment Deep reinforcement learning sequence alignment sequence comparison meta learning
ISSN:	2644-1276, 2644-1276
Online-Zugang:	Volltext
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