Shaherin A. Basith

Suwon, Republic of Korea

Last Updated: 09/26/2026

Save publications for later

Sign Up

Not sure about your diagnosis?

Check Your Symptoms

Found 63 publications

SSEL-CPP: A SHAP-based feature-selection ensemble learning framework identifies molecular properties of cell-penetrating peptides.

SSEL-CPP: A SHAP-based feature-selection ensemble learning framework identifies molecular properties of cell-penetrating peptides.

Journal: Protein science : a publication of the Protein Society

Published: March 13, 2026

Integrative Peptide Drug Development: Chemical Engineering, AI-Driven Design, and Cell-Penetrating Peptides.

Integrative Peptide Drug Development: Chemical Engineering, AI-Driven Design, and Cell-Penetrating Peptides.

Journal: Pharmaceutics

Published: March 13, 2026

Unraveling the Intricacies of G-Protein-Coupled Receptor Signaling in Cardiovascular Diseases: Novel Perspectives From Regulation to Therapeutic Targeting.

Unraveling the Intricacies of G-Protein-Coupled Receptor Signaling in Cardiovascular Diseases: Novel Perspectives From Regulation to Therapeutic Targeting.

Journal: Medicinal research reviews

Published: January 22, 2026

CONTRA-IL6: an interpretable hybrid convolutional neural network and Transformer framework for accurate prediction of interleukin-6-inducing peptides using protein language models.

CONTRA-IL6: an interpretable hybrid convolutional neural network and Transformer framework for accurate prediction of interleukin-6-inducing peptides using protein language models.

Journal: Briefings in bioinformatics

Published: December 23, 2025

CPPpred-En: Ensemble framework integrating a protein language model and conventional features for highly accurate cell-penetrating peptide prediction.

CPPpred-En: Ensemble framework integrating a protein language model and conventional features for highly accurate cell-penetrating peptide prediction.

Journal: Computers in biology and medicine

Published: April 22, 2025

Employing Automated Machine Learning (AutoML) Methods to Facilitate the In Silico ADMET Properties Prediction.

Employing Automated Machine Learning (AutoML) Methods to Facilitate the In Silico ADMET Properties Prediction.

Journal: Journal of chemical information and modeling

Published: March 14, 2025

EnsemPred-ACP: Combining machine and deep learning to improve anticancer peptide prediction.

EnsemPred-ACP: Combining machine and deep learning to improve anticancer peptide prediction.

Journal: Computers in biology and medicine

Published: February 05, 2025

AntiT2DMP-Pred: Leveraging feature fusion and optimization for superior machine learning prediction of type 2 diabetes mellitus.

AntiT2DMP-Pred: Leveraging feature fusion and optimization for superior machine learning prediction of type 2 diabetes mellitus.

Journal: Methods (San Diego, Calif.)

Published: October 31, 2024

mHPpred: Accurate identification of peptide hormones using multi-view feature learning.

mHPpred: Accurate identification of peptide hormones using multi-view feature learning.

Journal: Computers in biology and medicine

Published: August 20, 2024

SEP-AlgPro: An efficient allergen prediction tool utilizing traditional machine learning and deep learning techniques with protein language model features.

SEP-AlgPro: An efficient allergen prediction tool utilizing traditional machine learning and deep learning techniques with protein language model features.

Journal: International journal of biological macromolecules

Published: November 24, 2023

Unveiling local and global conformational changes and allosteric communications in SOD1 systems using molecular dynamics simulation and network analyses.

Unveiling local and global conformational changes and allosteric communications in SOD1 systems using molecular dynamics simulation and network analyses.

Journal: Computers in biology and medicine

Published: August 29, 2023

ADP-Fuse: A novel two-layer machine learning predictor to identify antidiabetic peptides and diabetes types using multiview information.

ADP-Fuse: A novel two-layer machine learning predictor to identify antidiabetic peptides and diabetes types using multiview information.

Journal: Computers in biology and medicine

Published: June 22, 2023

Showing 1-12 of 63

Last Updated: 09/26/2026