Generative design of novel bacteriophages with genome language models

Samuel King, Claudia Driscoll, David Li, Daniel Guo, Aditi Merchant, Garyk Brixi, Max Wilkinson, and Brian Hie

bioRxiv (2025)

Efficient generation of epitope-targeted de novo antibodies with Germinal

Luis S. Mille-Fragoso*^,†, John Wang*, Claudia Driscoll*, Haoyu Dai*, Talal Widatalla, Xiaowei Zhang, Brian Hie^†, and Xiaojing Gao^†

bioRxiv (2025)

Genome modeling and design across all domains of life with Evo 2

Garyk Brixi*, Matthew Durrant*, Jerome Ku*, Michael Poli*, Greg Brockman, Daniel Chang, Gabriel Gonzalez, Samuel King, David Li, Aditi Merchant, Mohsen Naghipourfar, Eric Nguyen, Chiara Ricci-Tam, David Romero, Gwanggyu Sun, Ali Taghibakshi, Anton Vorontsov, Brandon Yang, et al., Dave Burke, Hani Goodarzi, Patrick Hsu^†, and Brian Hie^†

bioRxiv (2025)

Sidechain conditioning and modeling for full-atom protein sequence design with FAMPNN

Talal Widatalla*, Richard Shuai*, Brian Hie^†, and Possu Huang^†

International Conference on Machine Learning (2025)

Utilizing machine learning to improve neutralization potency of an HIV-1 antibody targeting the gp41 N-heptad repeat

Maria Filsinger Interrante, Shaogeng Tang, Soohyun Kim, Varun Shanker, Brian Hie, Theodora Bruun, Wesley Wu, John Pak, Daniel Fernandez, and Peter Kim

ACS Chemical Biology (2025)

Systems and algorithms for convolutional multi-hybrid language models at scale

Jerome Ku, Eric Nguyen, David Romero, Garyk Brixi, Brandon Yang, Anton Vorontsov, Ali Taghibakhshi, Amy Lu, Dave Burke, Greg Brockman, Stefano Massaroli, Christopher Ré, Patrick Hsu, Brian Hie, Stefano Ermon, and Michael Poli

arXiv (2025)

Semantic mining of functional de novo genes from a genomic language model

Aditi Merchant, Samuel King, Eric Nguyen, and Brian Hie

bioRxiv (2024)

Sequence modeling and design from molecular to genome scale with Evo

Eric Nguyen*, Michael Poli*, Matthew Durrant*, Brian Kang*, Dhruva Katrekar*, David Li*, Liam Bartie, Armin Thomas, Samuel King, Garyk Brixi, Jeremy Sullivan, Madelena Ng, Ashley Lewis, Aaron Lou, Stefano Ermon, Stephen Baccus, Tina Hernandez-Boussard, Christopher Ré, Patrick Hsu^†, and Brian Hie^†

Science (2024)

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, and 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)