Sequence modeling and design from molecular to genome scale with Evo

Eric Nguyen, Michael Poli, Matthew Durrant, Armin Thomas, Brian Kang, Jeremy Sullivan, Madelena Ng, Ashley Lewis, Aman Patel, Aaron Lou, Stefano Ermon, Stephen Baccus, Tina Hernandez-Boussard, Christopher Ré, Patrick Hsu^†, and Brian Hie^†

bioRxiv (2024), Science (in press)

Unsupervised evolution of protein and antibody complexes with a structure-informed language model

Varun Shanker, Theodora Bruun, Brian Hie^†, and Peter Kim^†

Science (2024)

Scanorama: Integrating large and diverse single-cell transcriptomic datasets

Brian Hie*^,†, Soochi Kim*, Thomas Rando, Bryan Bryson^†, and Bonnie Berger^†

Nature Protocols (2024)

Mechanistic design and scaling of hybrid architectures

Michael Poli, Armin Thomas, Eric Nguyen, Pragaash Ponnusamy, Björn Deiseroth, Kristian Kersting, Taiji Suzuki, Brian Hie, Stefano Ermon, Christopher Ré, Ce Zhang, Stefano Massaroli

International Conference on Machine Learning (2024)

BHLHE40 regulates myeloid cell polarization through IL-10-dependent and -independent mechanisms

Skyler Hendrix, Yassin Mreyoud, Michael McNehlan, Asya Smirnov, Sthefany Chavez, Brian Hie, Megan Chamberland, Tara Bradstreet, Ashlee Webber, Darren Kreamalmeyer, Reshma Taneja, Bryan Bryson, Brian Edelson, and Christina Stallings

Journal of Immunology (2024)

Generative artificial intelligence for de novo protein design

Adam Winnifrith, Carlos Outeiral^†, and Brian Hie^†

Current Opinion in Structural Biology (2024)

Efficient evolution of human antibodies from general protein language models

Brian Hie^†, Varun Shanker, Duo Xu, Theodora Bruun, Payton Weidenbacher, Shaogeng Tang, Wesley Wu, John Pak, and Peter Kim^†

Nature Biotechnology (2023)

Evolutionary-scale prediction of atomic-level protein structure with a language model

Zeming Lin*, Halil Akin*, Roshan Rao*, Brian Hie*, Zhongkai Zhu, Wenting Lu, Nikita Smetanin, Robert Verkuil, Ori Kabeli, Yaniv Shmueli, Allan dos Santos Costa, Maryam Fazel-Zarandi, Tom Sercu, Salvatore Candido, and Alexander Rives

Science (2023)

Machine learning for protein engineering

Kadina Johnston*, Clara Fannjiang*, Bruce Witmann*, Brian Hie*, Kevin Yang*, and Zachary Wu*

Machine Learning in Molecular Sciences (2023)

A high-level programming language for generative protein design

Brian Hie*, Salvatore Candido*, Zeming Lin, Ori Kabeli, Roshan Rao, Nikita Smetanin, Tom Sercu, and Alexander Rives

bioRxiv (2022)

Evolutionary velocity with protein language models predicts evolutionary dynamics of diverse proteins

Brian Hie^†, Kevin Yang, and Peter Kim^†

Cell Systems (2022)

Learning inverse folding from millions of predicted structures

Chloe Hsu, Robert Verkuil, Jason Liu, Zeming Lin, Brian Hie, Tom Sercu, Adam Lerer, and Alexander Rives

International Conference on Machine Learning (2022)

Predicting the mutational drivers of future SARS-CoV-2 variants of concern

M. Cyrus Maher, Istvan Bartha, Steven Weaver, Julia di Iulio, Elena Ferri, Leah Soriaga, Florian Lempp, Brian Hie, Bryan Bryson, Bonnie Berger, David Robertson, Gyorgy Snell, Herbert Virgin, Sergei Kosakovsky Pond, and Amalio Telenti

Science Translational Medicine (2022)

Adaptive machine learning for protein engineering

Brian Hie and Kevin Yang

Current Opinion in Structural Biology (2022)

Algorithms for understanding and fighting infectious disease

Brian Hie

Massachusetts Institute of Technology, Doctoral Thesis (2021)

Schema: Metric learning enables interpretable synthesis of heterogeneous single-cell modalities

Rohit Singh*, Brian Hie*, Ashwin Narayan, and Bonnie Berger

Genome Biology (2021)

Learning the language of viral evolution and escape

Brian Hie, Ellen Zhong, Bonnie Berger, and Bryan Bryson

Science (2021)

Leveraging uncertainty in machine learning accelerates biological discovery and design

Brian Hie, Bryan Bryson, and Bonnie Berger

Cell Systems (2020)

Computational methods for single-cell RNA sequencing

Brian Hie*, Josh Peters*, Sarah Nyquist*, Alex Shalek, Bonnie Berger, and Bryan Bryson

Annual Review of Biomedical Data Science (2020)

Geometric sketching compactly summarizes the single-cell transcriptomic landscape

Brian Hie*, Hyunghoon Cho*, Benjamin DeMeo, Bryan Bryson, and Bonnie Berger

Cell Systems (2019)

Efficient integration of heterogeneous single-cell transcriptomes using Scanorama

Brian Hie, Bryan Bryson, and Bonnie Berger

Nature Biotechnology (2019)

Fine-mapping cis-regulatory variants in diverse human populations

Ashley Tehranchi, Brian Hie, Michael Dacre, Irene Kaplow, Kade Pettie, Peter Combs, and Hunter Fraser

eLife (2019)

Realizing private and practical pharmacological collaboration

Brian Hie*, Hyunghoon Cho*, and Bonnie Berger

Science (2018)

Pooled ChIP-seq links variation in transcription factor binding to complex disease risk

Ashley Tehranchi, Marsha Myrthil, Trevor Martin, Brian Hie, David Golan, and Hunter Fraser

Cell (2016)