Madhurima Mondal

LinkDTI predicts drug-target interactions using a graph-based framework on a biomedical knowledge graph, outperforming baselines and identifying new interactions.

This paper uses a Boolean Network model to evaluate metabolic and immune inhibitors for colorectal cancer liver metastasis, identifying effective drug combinations and potential improvements in treatment.

This paper introduces SAM-DTI, a spatial attention model for predicting drug-target interactions using SMILES strings and protein sequences, achieving competitive performance against existing methods.

This study uses Boolean networks to identify optimal drug targets in TNBC stem cell pathways, finding that inhibiting STAT3, GLI, and NF-κB can prevent relapse and that drug combinations are more effective.