Balachandran Manavalan, PhD, Sungkyunkwan University, South Korea
Leyi Wei, PhD, Shandong University, China
M. Michael Gromiha, PhD, Indian Institute of Technology (IIT) Madras, India
Genomics & Informatics is calling for submissions to our Collection on Advancing sequence-based biological function prediction using artificial intelligence.
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Balachandran Manavalan, PhD, Sungkyunkwan University, South Korea
Dr. Balachandran Manavalan is an Assistant Professor at the Department of Integrative Biotechnology, Sungkyunkwan University (SKKU). He earned his PhD in Computational Biology from Ajou University in 2011 and served as a research fellow at Korea Institute for Advanced Study and Ajou University School of Medicine. He established his research group at SKKU in 2022. His research focuses on AI, bioinformatics, machine learning, big data, proteomics, and functional genomics. He has been in the top 2% of highly cited researchers for the past four years, according to Stanford University data.
Leyi Wei, PhD, Shandong University, ChinaDr. Leyi Wei received his B.Sc. in Computing Mathematics in 2010 and his M.E. and Ph.D. in Computer Science from Xiamen University in 2013 and 2016, respectively. He was an Assistant Professor at Tianjin University's College of Intelligence and Computing from 2016 to 2019. He also worked as a project researcher at the University of Tokyo during 2018-2019. Since January 2020, he has been a Professor at Shandong University. Dr. Wei has co-authored over 100 publications and received awards including Highly Cited Researcher (Clarivate, 2021-2023) and the ACM SIGBIO Rising Star Award (2021).
M. Michael Gromiha, PhD , Indian Institute of Technology (IIT) Madras, IndiaDr. M. Michael Gromiha is a Professor at the Department of Biotechnology, Indian Institute of Technology (IIT) Madras, India. His research focuses on sequence and structural analysis, protein folding, stability, and interactions, bioinformatics databases and tools, drug design, and next-generation sequencing. He has published over 350 articles and developed 50 bioinformatics databases/tools. He authored three books: "Protein Bioinformatics" (Elsevier), "Protein Interactions," and "Protein Mutations" (World Scientific).
With the rapid growth of biological sequence data, machine learning has become an essential tool for analyzing these sequences and extracting useful information. There are many different areas of biological sequence classification research, such as understanding the biological functions of DNA (e.g., epigenetic modification sites, replication origin, enhancer, and promoter), RNA (e.g., subcellular localization and post-transcriptional modifications), proteins (e.g., hormone binding proteins, thermophilic/mesophilic), and peptides (e.g., anticancer, antihypertensive, and antimicrobial).
In recent years, the field of bioinformatics or computational biology has made significant progress due to the development of new computational frameworks that combine conventional and deep learning algorithms with rigorous feature optimization methodologies.
This special thematic collection focuses on the application of machine learning, including deep learning, to biological sequence analysis. We are particularly interested in showcasing novel and sophisticated deep learning methodologies that can extract and interpret biological function information from sequence data.
In addition to original research papers, we also welcome review papers that evaluate current AI strategies for sequence-based biological functional studies.
This Collection welcomes submission of research articles and review articles. Should you wish to submit a different article type, please read our submission guidelines to confirm that type is accepted by the journal.
Articles for this Collection should be submitted via our submission system, Snapp. Please, select the appropriate Collection title “Advancing sequence-based biological function prediction using artificial intelligence" under the “Details” tab during the submission stage.
Articles will undergo the journal’s standard peer-review process and are subject to all the journal’s standard policies. Articles will be added to the Collection as they are published.
The Editors have no competing interests with the submissions which they handle through the peer-review process. The peer-review of any submissions for which the Editors have competing interests is handled by another Editorial Board Member who has no competing interests.