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Frontiers in Physiology|August 17, 2011
Similar Structures but Different Roles - An Updated Perspective on TLR StructuresBalachandran Manavalan, Shaherin Basith, Sangdun Choi
Methods (San Diego, Calif.)|January 11, 2025
AntiT2DMP-Pred: Leveraging feature fusion and optimization for superior machine learning prediction of type 2 diabetes mellitusShaherin Basith, Balachandran Manavalan, Gwang Lee
Computers in Biology and Medicine|November 29, 2022
Amyotrophic lateral sclerosis disease-related mutations disrupt the dimerization of superoxide dismutase 1 - A comparative molecular dynamics simulation studyShaherin Basith, Balachandran Manavalan, Gwang Lee
Briefings in Bioinformatics|September 17, 2021
STALLION: a stacking-based ensemble learning framework for prokaryotic lysine acetylation site predictionShaherin Basith, Gwang Lee, Balachandran Manavalan
Computers in Biology and Medicine|November 21, 2023
Unveiling local and global conformational changes and allosteric communications in SOD1 systems using molecular dynamics simulation and network analysesShaherin Basith, Balachandran Manavalan, Gwang Lee
Briefings in Bioinformatics|October 1, 2021
Comparative analysis of machine learning-based approaches for identifying therapeutic peptides targeting SARS-CoV-2Balachandran Manavalan, Shaherin Basith, Gwang Lee
Plos One|February 2, 2013
Evolutionary, structural and functional interplay of the IκB family membersShaherin Basith, Balachandran Manavalan, Vijayakumar Gosu, et al.
Medicinal Research Reviews|January 11, 2020
Machine intelligence in peptide therapeutics: A next-generation tool for rapid disease screeningShaherin Basith, Balachandran Manavalan, Tae Hwan Shin, et al.
Molecular Therapy. Nucleic Acids|September 23, 2019
SDM6A: A Web-Based Integrative Machine-Learning Framework for Predicting 6mA Sites in the Rice GenomeShaherin Basith, Balachandran Manavalan, Tae Hwan Shin, et al.
Computational and Structural Biotechnology Journal|November 15, 2018
iGHBP: Computational identification of growth hormone binding proteins from sequences using extremely randomised treeShaherin Basith, Balachandran Manavalan, Tae Hwan Shin, et al.
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