Sotabase

Career

· Assistant Professor of Systems Biology, Columbia University2020–
· Departmental Fellow and Fellow in Systems Pharmacology, Harvard Medical School
· Founder, Mobile Computing Startups
· Undergraduate Degrees in Biology, Computer Science, and Mathematics, Santa Clara University
· PhD in Genetics, Stanford University

Publications (42)

Unified rational protein engineering with sequence-based deep representation learning
Nature Methods · 2019
1,005
cited
End-to-end differentiable learning of protein structure
bioRxiv · 2018
346
cited
OpenFold: Retraining AlphaFold2 yields new insights into its learning mechanisms and capacity for generalization
bioRxiv · 2023
336
cited
Single-sequence protein structure prediction using a language model and deep learning
Nature Biotechnology · 2022
325
cited
AlphaFold at CASP13
Bioinform. · 2019
278
cited
ProteinNet: a standardized data set for machine learning of protein structure
BMC Bioinformatics · 2019
155
cited
Machine learning in protein structure prediction.
Current Opinion in Chemical Biology · 2021
141
cited
How to build the virtual cell with artificial intelligence: Priorities and opportunities
Cell · 2024
95
cited
BIOPHYSICAL PREDICTION OF PROTEIN-PEPTIDE INTERACTIONS AND SIGNALING NETWORKS USING MACHINE LEARNING
Nature Methods · 2019
86
cited
Differentiable biology: using deep learning for biophysics-based and data-driven modeling of molecular mechanisms
Nature Methods · 2021
75
cited
A multiscale statistical mechanical framework integrates biophysical and genomic data to assemble cancer networks
Nature Genetics · 2014
61
cited
Single-sequence protein structure prediction using language models from deep learning
bioRxiv · 2021
61
cited
Unified rational protein engineering with sequence-only deep representation learning
bioRxiv · 2019
46
cited
Recombination and lineage-specific mutations linked to the emergence of SARS-CoV-2
Genome Medicine · 2020
44
cited
Protein structure prediction by AlphaFold2: are attention and symmetries all you need?
Acta Crystallographica Section D: Structural Biology · 2021
38
cited
From Mechanistic Interpretability to Mechanistic Biology: Training, Evaluating, and Interpreting Sparse Autoencoders on Protein Language Models
bioRxiv · 2025
31
cited
Mapping variant effects on anti-tumor hallmarks of primary human T cells with base-editing screens
Nature Biotechnology · 2024
24
cited
DeepSpeed4Science Initiative: Enabling Large-Scale Scientific Discovery through Sophisticated AI System Technologies
arXiv.org · 2023
23
cited
OpenProteinSet: Training data for structural biology at scale
Neural Information Processing Systems · 2023
23
cited
High-throughput deep learning variant effect prediction with Sequence UNET
bioRxiv · 2022
21
cited
Sotabase