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Machine Learning and Deep Learning Frameworks for Human-Virus Protein-Protein Interaction Prediction: Emerging Architectures, Methods, Benchmarks, and Challenges.

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Bibliographic Details
Title: Machine Learning and Deep Learning Frameworks for Human-Virus Protein-Protein Interaction Prediction: Emerging Architectures, Methods, Benchmarks, and Challenges.
Authors: Basu S; Department of Biotechnology, Amity University, Noida 201313, India., Adhikary D; Department of Biotechnology and Biochemical Engineering, Indian Institute of Technology, Kharagpur 721302, India., Ghosh K; Machine Intelligence Unit, Indian Statistical Institute, Kolkata 700108, India., Chattopadhyay S; School of Computer Science and Engineering, XIM University, Bhubaneswar 751013, India., Deb S; Centre for Neurovascular Research, Manipal Group of Hospitals, Kolkata 700099, India.; Department of Neurology, Manipal Group of Hospitals, Kolkata 700099, India., Mondal R; Centre for Neurovascular Research, Manipal Group of Hospitals, Kolkata 700099, India.; Department of Neurology, Manipal Group of Hospitals, Kolkata 700099, India., Roy J; Centre for Neurovascular Research, Manipal Group of Hospitals, Kolkata 700099, India.; Department of Neurology, Manipal Group of Hospitals, Kolkata 700099, India., Chowdhury A; Department of Computer Science and Engineering, Indian Institute of Technology, Dhanbad 826004, India., Benito-León J; Department of Neurology, 12 de Octubre University Hospital, 28041 Madrid, Spain.; Group of Neurodegenerative Diseases, Hospital Universitario 12 de Octubre Research Institute (Imas12), 28041 Madrid, Spain.; Network Center for Biomedical Research in Neurodegenerative Diseases (CIBERNED), 28031 Madrid, Spain.; Department of Medicine, Faculty of Medicine, Complutense University of Madrid, 28040 Madrid, Spain.
Source: International journal of molecular sciences [Int J Mol Sci] 2026 Jul 05; Vol. 27 (13). Date of Electronic Publication: 2026 Jul 05.
Publication Type: Journal Article; Review
Journal Info: Publisher: MDPI Country of Publication: Switzerland NLM ID: 101092791 Publication Model: Electronic Cited Medium: Internet ISSN: 1422-0067 (Electronic) Linking ISSN: 14220067 NLM ISO Abbreviation: Int J Mol Sci Subsets: MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:1422-0067
DOI:10.3390/ijms27136034