{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"omics_type":["Unknown"],"volume":["2"],"submitter":["Song YJ"],"pubmed_abstract":["<i>Goal:</i> 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 local alignment method to obtain optimal sequence alignment based on reinforcement learning. <i>Methods:</i> There is a DQNalign algorithm that learns and performs sequence alignment through deep reinforcement learning. This paper proposes a DQN x-drop algorithm that performs local alignment without human intervention by combining the x-drop algorithm with this DQNalign algorithm. The proposed algorithm performs local alignment by repeatedly observing the subsequences and selecting the nex"],"journal":["IEEE open journal of engineering in medicine and biology"],"pagination":["170-178"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC8975175"],"repository":["biostudies-literature"],"pubmed_title":["Local Alignment of DNA Sequence Based on Deep Reinforcement Learning."],"pmcid":["PMC8975175"],"pubmed_authors":["Song YJ","Cho DH"],"additional_accession":[]},"is_claimable":false,"name":"Local Alignment of DNA Sequence Based on Deep Reinforcement Learning.","description":"<i>Goal:</i> 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 local alignment method to obtain optimal sequence alignment based on reinforcement learning. <i>Methods:</i> There is a DQNalign algorithm that learns and performs sequence alignment through deep reinforcement learning. This paper proposes a DQN x-drop algorithm that performs local alignment without human intervention by combining the x-drop algorithm with this DQNalign algorithm. The proposed algorithm performs local alignment by repeatedly observing the subsequences and selecting the nex","dates":{"release":"2021-01-01T00:00:00Z","publication":"2021","modification":"2025-04-19T07:48:20.138Z","creation":"2025-04-19T07:48:20.138Z"},"accession":"S-EPMC8975175","cross_references":{"pubmed":["35402982"],"doi":["10.1109/OJEMB.2021.3076156"]}}