ML-GAP: machine learning-enhanced genomic analysis pipeline using autoencoders and data augmentation.

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Bibliographic Details
Title: ML-GAP: machine learning-enhanced genomic analysis pipeline using autoencoders and data augmentation.
Authors: Agraz M; Division of Applied Mathematics, Brown University, Providence, RI, United States.; Department of Statistics, Giresun University, Giresun, Türkiye., Goksuluk D; Department of Biostatistics, Erciyes University, Kayseri, Türkiye., Zhang P; Vascular Research Laboratory, VA Providence Healthcare System, Providence, RI, United States.; Division of Cardiology, Department of Medicine, Alpert Medical School of Brown University, Providence, RI, United States., Choi BR; Division of Cardiology, Department of Medicine, Alpert Medical School of Brown University, Providence, RI, United States.; Cardiovascular Research Center, Rhode Island Hospital, Providence, RI, United States., Clements RT; Vascular Research Laboratory, VA Providence Healthcare System, Providence, RI, United States.; Department of Biomedical and Pharmaceutical Sciences, University of Rhode Island College of Pharmacy, South Kingston, RI, United States., Choudhary G; Vascular Research Laboratory, VA Providence Healthcare System, Providence, RI, United States.; Division of Cardiology, Department of Medicine, Alpert Medical School of Brown University, Providence, RI, United States.; Cardiovascular Research Center, Rhode Island Hospital, Providence, RI, United States., Karniadakis GE; Division of Applied Mathematics, Brown University, Providence, RI, United States.; School of Engineering, Brown University, Providence, RI, United States.
Source: Frontiers in genetics [Front Genet] 2024 Sep 25; Vol. 15, pp. 1442759. Date of Electronic Publication: 2024 Sep 25 (Print Publication: 2024).
Publication Type: Journal Article
Journal Info: Publisher: Frontiers Research Foundation Country of Publication: Switzerland NLM ID: 101560621 Publication Model: eCollection Cited Medium: Print ISSN: 1664-8021 (Print) Linking ISSN: 16648021 NLM ISO Abbreviation: Front Genet Subsets: PubMed not MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:1664-8021
DOI:10.3389/fgene.2024.1442759