Nicholas Bhattacharya
Microsoft (United States)(US)Microsoft Research New England (United States)(US)University of California, Berkeley(US)
Publications by Year
Research Areas
Genomics and Phylogenetic Studies, Machine Learning in Bioinformatics, Protein Structure and Dynamics, RNA and protein synthesis mechanisms, Microbial Natural Products and Biosynthesis
Most-Cited Works
- → Evaluating Protein Transfer Learning with TAPE(2019)676 cited
- → Necrotizing enterocolitis is preceded by increased gut bacterial replication, Klebsiella , and fimbriae-encoding bacteria(2019)187 cited
- → Differences in the path to exit the ribosome across the three domains of life(2019)95 cited
- → Transporter genes in biosynthetic gene clusters predict metabolite characteristics and siderophore activity(2020)67 cited
- → End-to-end learning of multiple sequence alignments with differentiable Smith–Waterman(2022)39 cited
- → Deep self-supervised learning for biosynthetic gene cluster detection and product classification(2023)38 cited
- → Single Layers of Attention Suffice to Predict Protein Contacts