Brian Hie is a scholar working on Molecular Biology, Immunology and Artificial Intelligence.
According to data from OpenAlex, Brian Hie has authored 24 papers receiving a total of 3.7k indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Molecular Biology, 5 papers in Immunology and 3 papers in Artificial Intelligence. Recurrent topics in Brian Hie's work include RNA and protein synthesis mechanisms (6 papers), Single-cell and spatial transcriptomics (5 papers) and vaccines and immunoinformatics approaches (5 papers). Brian Hie is often cited by papers focused on RNA and protein synthesis mechanisms (6 papers), Single-cell and spatial transcriptomics (5 papers) and vaccines and immunoinformatics approaches (5 papers). Brian Hie collaborates with scholars based in United States, United Kingdom and Slovakia. Brian Hie's co-authors include Bonnie Berger, Bryan D. Bryson, Allan dos Santos Costa, Robert Verkuil, Alexander Rives, Zeming Lin, Zhongkai Zhu, Halil Akin, Ori Kabeli and Salvatore Candido and has published in prestigious journals such as Nature, Science and Cell.
In The Last Decade
Brian Hie
23 papers
receiving
3.6k citations
Hit Papers
What are hit papers?
Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
Evolutionary-scale prediction of atomic-level protein structure with a language model
20232.0k citationsZeming Lin, Halil Akin et al.Scienceprofile →
Efficient integration of heterogeneous single-cell transcriptomes using Scanorama
2019464 citationsBrian Hie, Bryan D. Bryson et al.Nature Biotechnologyprofile →
Efficient evolution of human antibodies from general protein language models
2023205 citationsBrian Hie, Varun R. Shanker et al.Nature Biotechnologyprofile →
Sequence modeling and design from molecular to genome scale with Evo
2024127 citationsMichael Poli, S. B. King et al.Scienceprofile →
Unsupervised evolution of protein and antibody complexes with a structure-informed language model
202453 citationsVarun R. Shanker, Theodora U. J. Bruun et al.Scienceprofile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
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This map shows the geographic impact of Brian Hie's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Brian Hie with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Brian Hie more than expected).
This network shows the impact of papers produced by Brian Hie. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Brian Hie. The network helps show where Brian Hie may publish in the future.
Co-authorship network of co-authors of Brian Hie
This figure shows the co-authorship network connecting the top 25 collaborators of Brian Hie.
A scholar is included among the top collaborators of Brian Hie based on the total number of
citations received by their joint publications. Widths of edges
represent the number of papers authors have co-authored together.
Node borders
signify the number of papers an author published with Brian Hie. Brian Hie is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Ku, Ja‐Lok, David W. Romero, Garyk Brixi, et al.. (2025). Systems and Algorithms for Convolutional Multi-Hybrid Language Models at Scale. ArXiv.org.1 indexed citations
Shanker, Varun R., Theodora U. J. Bruun, Brian Hie, & Peter S. Kim. (2024). Unsupervised evolution of protein and antibody complexes with a structure-informed language model. Science. 385(6704). 46–53.53 indexed citations breakdown →
Hie, Brian, Varun R. Shanker, Duo Xu, et al.. (2023). Efficient evolution of human antibodies from general protein language models. Nature Biotechnology. 42(2). 275–283.205 indexed citations breakdown →
10.
Lin, Zeming, Halil Akin, Roshan Rao, et al.. (2023). Evolutionary-scale prediction of atomic-level protein structure with a language model. Science. 379(6637). 1123–1130.1968 indexed citations breakdown →
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive
bibliographic database. While OpenAlex provides broad and valuable coverage of the global
research landscape, it—like all bibliographic datasets—has inherent limitations. These include
incomplete records, variations in author disambiguation, differences in journal indexing, and
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