An in-depth analysis of the molecular dynamics and structural aspects of IKB proteins. - Shaherin Basith; Sangdun Choi (BCB, 2012)

mAHTPred: a sequence-based meta-predictor for improving the prediction of anti-hypertensive peptides using effective feature representation. - Balachandran Manavalan; Shaherin Basith; Tae Hwan Shin; Leyi Wei; Gwang Lee (Bioinform., 2019)

HLPpred-Fuse: improved and robust prediction of hemolytic peptide and its activity by fusing multiple feature representation. - Md. Mehedi Hasan 002; Nalini Schaduangrat; Shaherin Basith; Gwang Lee; Watshara Shoombuatong; Balachandran Manavalan (Bioinform., 2020)

Integrative machine learning framework for the identification of cell-specific enhancers from the human genome. - Shaherin Basith; Md. Mehedi Hasan 002; Gwang Lee; Leyi Wei; Balachandran Manavalan (Briefings Bioinform., 2021)

Meta-i6mA: an interspecies predictor for identifying DNA N6-methyladenine sites of plant genomes by exploiting informative features in an integrative machine-learning framework. - Md. Mehedi Hasan 002; Shaherin Basith; Mst. Shamima Khatun; Gwang Lee; Balachandran Manavalan; Hiroyuki Kurata (Briefings Bioinform., 2021)

STALLION: a stacking-based ensemble learning framework for prokaryotic lysine acetylation site prediction. - Shaherin Basith; Gwang Lee; Balachandran Manavalan (Briefings Bioinform., 2022)

Comparative analysis of machine learning-based approaches for identifying therapeutic peptides targeting SARS-CoV-2. - Balachandran Manavalan; Shaherin Basith; Gwang Lee (Briefings Bioinform., 2022)

Amyotrophic lateral sclerosis disease-related mutations disrupt the dimerization of superoxide dismutase 1 - A comparative molecular dynamics simulation study. - Shaherin Basith; Balachandran Manavalan; Gwang Lee (Comput. Biol. Medicine, 2022)

ADP-Fuse: A novel two-layer machine learning predictor to identify antidiabetic peptides and diabetes types using multiview information. - Shaherin Basith; Nhat Truong Pham; Minkyung Song; Gwang Lee; Balachandran Manavalan (Comput. Biol. Medicine, 2023)

mHPpred: Accurate identification of peptide hormones using multi-view feature learning. - Shaherin Basith; Vinoth Kumar Sangaraju; Balachandran Manavalan; Gwang Lee (Comput. Biol. Medicine, 2024)

Unveiling local and global conformational changes and allosteric communications in SOD1 systems using molecular dynamics simulation and network analyses. - Shaherin Basith; Balachandran Manavalan; Gwang Lee (Comput. Biol. Medicine, 2024)

CPPpred-En: Ensemble framework integrating a protein language model and conventional features for highly accurate cell-penetrating peptide prediction. - Yongeun Jang; Minjun Kwon; Seok Gi Kim; Nimisha Pradeep George; Ji Su Hwang; Shaherin Basith; Gwang Lee (Comput. Biol. Medicine, 2025)

EnsemPred-ACP: Combining machine and deep learning to improve anticancer peptide prediction. - Minjun Kwon; Yongeun Jang; Ji Su Hwang; Seok Gi Kim; Nimisha Pradeep George; Shaherin Basith; Gwang Lee (Comput. Biol. Medicine, 2025)

Employing Automated Machine Learning (AutoML) Methods to Facilitate the In Silico ADMET Properties Prediction. - Herim Han; Bilal Shaker; Jin Hee Lee; Sunghwan Choi; Sanghee Yoon; Maninder Singh; Shaherin Basith; Minghua Cui; Sunil Ahn; Junyoung An; Soosung Kang; Min Sun Yeom; et al. (J. Chem. Inf. Model., 2025)