Joshua Meier

University of Michigan–Ann Arbor — United States

Biochemistry, Genetics and Molecular Biology · Life Sciences

14h-index5.3kcitations24works73.02yr avg
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Research Topics

RNA and protein synthesis mechanisms(8), Machine Learning in Bioinformatics(8), Genomics and Phylogenetic Studies(7), Protein Structure and Dynamics(6), Monoclonal and Polyclonal Antibodies Research(5)

Publications24 total

Drug-like antibody design against challenging targets with atomic precision
2025· 3 citedOpen Access
HuR ablation destabilizes Foxp3 mRNA and impairs regulatory T cell function, contributing to an autoimmune phenotype
Frontiers in Immunology·2025Open Access
Zero-shot antibody design in a 24-well plate
2025· 16 citedOpen Access
Chai-1: Decoding the molecular interactions of life
2024· 273 citedOpen Access
IgDesign: <i>In vitro</i> validated antibody design against multiple therapeutic antigens using inverse folding
2023· 22 citedOpen Access
Deep learning-based codon optimization with large-scale synonymous variant datasets enables generalized tunable protein expression
2023· 17 citedOpen Access
Unlocking <i>de novo</i> antibody design with generative artificial intelligence
2023· 77 citedOpen Access
Antibody optimization enabled by artificial intelligence predictions of binding affinity and naturalness
2022· 65 citedOpen Access
Developing antisense oligonucleotides for a TECPR2 mutation-induced, ultra-rare neurological disorder using patient-derived cellular models
Molecular Therapy — Nucleic Acids·2022· 9 citedOpen Access
MSA Transformer
2021· 9 cited
Language models enable zero-shot prediction of the effects of mutations on protein function
2021· 636 citedOpen Access
Transformer protein language models are unsupervised structure learners
2021· 10 cited
Neural Potts Model
2021· 8 citedOpen Access
Biological structure and function emerge from scaling unsupervised learning to 250 million protein sequences
Proceedings of the National Academy of Sciences·2021· 2.8k citedOpen Access
MSA Transformer
2021· 329 citedOpen Access
Transformer protein language models are unsupervised structure learners
2020· 335 citedOpen Access
Energy-based models for atomic-resolution protein conformations
arXiv (Cornell University)·2020· 13 citedOpen Access
Biological structure and function emerge from scaling unsupervised learning to 250 million protein sequences
2019· 396 citedOpen Access
Evaluating Reinforcement Learning Algorithms in Observational Health Settings
arXiv (Cornell University)·2018· 85 citedOpen Access
CRISPR-Cas9 Screens Reveal Genes Regulating a G0-Like State in Human Neural Progenitors
SSRN Electronic Journal·2018· 3 citedOpen Access
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Frequent Co-authors

Alexander Rives(9), Tom Sercu(8), Jason Liu(6), Roshan Rao(5), Robert Verkuil(4), Jack Dent(4), Matt McPartlon(4), Christa Kohnert(4), Rebecca Consbruck(4), Hayley Carter(4), Shaheed Abdulhaqq(4), Zeming Lin(3), Jerry Ma(3), Rob Fergus(3), George W. Kasun(3), John M. Sutton(3), Cailen M. McCloskey(3), S. G. LEVINE(3), Jahir M. Gutierrez(3), Abigail B. Ventura(3)