Delower Hossain

MondrianMap provides multi-resolution visualization of gene set enrichment results, revealing directional oppositions and temporal dynamics across biological processes in cancer, aging, and exercise data.

This study benchmarks compact transformer models for de novo antibody design, finding no significant architectural differences in performance at small scales.

LlamaAffinity predicts antibody-antigen binding affinity using a Llama 3 backbone and antibody sequences from the OAS database, achieving high accuracy and efficiency.

This paper develops a neuro-symbolic AI model, NeSyDPP4-QSAR, to predict DPP-4 inhibitor activity, achieving high accuracy in IC50 prediction for drug discovery.

This paper develops a neuro-symbolic AI model using LTN to predict hERG inhibition, outperforming existing models on benchmark datasets.