Drew Bryant

965 total citations · 1 hit paper
16 papers, 320 citations indexed

About

Drew Bryant is a scholar working on Molecular Biology, Materials Chemistry and Computational Theory and Mathematics. According to data from OpenAlex, Drew Bryant has authored 16 papers receiving a total of 320 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Molecular Biology, 7 papers in Materials Chemistry and 2 papers in Computational Theory and Mathematics. Recurrent topics in Drew Bryant's work include Protein Structure and Dynamics (10 papers), Machine Learning in Bioinformatics (5 papers) and Enzyme Structure and Function (5 papers). Drew Bryant is often cited by papers focused on Protein Structure and Dynamics (10 papers), Machine Learning in Bioinformatics (5 papers) and Enzyme Structure and Function (5 papers). Drew Bryant collaborates with scholars based in United States, United Kingdom and Russia. Drew Bryant's co-authors include Lydia E. Kavraki, Lucy J. Colwell, Maxwell L. Bileschi, Brandon Carter, Theo Sanderson, Mark A. DePristo, David Belanger, Alex Bateman, D. Sculley and Mark Moll and has published in prestigious journals such as Blood, Nature Biotechnology and Bioinformatics.

In The Last Decade

Drew Bryant

15 papers receiving 315 citations

Hit Papers

Using deep learning to annotate the protein universe 2022 2026 2023 2024 2022 50 100 150
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.

  1. Using deep learning to annotate the protein universe
    2022 164 citations Maxwell L. Bileschi, David Belanger et al. Nature Biotechnology profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Drew Bryant United States 9 267 76 69 19 17 16 320
Diego Javier Zea Argentina 12 359 1.3× 111 1.5× 79 1.1× 23 1.2× 12 0.7× 23 400
Prashant K. Khade United States 10 261 1.0× 94 1.2× 79 1.1× 11 0.6× 12 0.7× 18 435
R. Rajgaria United States 6 290 1.1× 129 1.7× 62 0.9× 16 0.8× 19 1.1× 8 329
Wensi Zhu Sweden 4 326 1.2× 90 1.2× 42 0.6× 27 1.4× 20 1.2× 4 359
M. John United Kingdom 2 224 0.8× 87 1.1× 49 0.7× 23 1.2× 9 0.5× 2 264
Chen‐hsiung Chan Taiwan 11 271 1.0× 62 0.8× 68 1.0× 16 0.8× 7 0.4× 13 336
S. R. McAllister United States 5 265 1.0× 124 1.6× 57 0.8× 14 0.7× 16 0.9× 7 302
Maria Littmann Germany 11 417 1.6× 55 0.7× 56 0.8× 19 1.0× 15 0.9× 15 483
Brian Y. Chen United States 12 319 1.2× 127 1.7× 138 2.0× 24 1.3× 22 1.3× 43 407
Khalid Kunji Qatar 8 304 1.1× 77 1.0× 63 0.9× 12 0.6× 28 1.6× 23 396

Countries citing papers authored by Drew Bryant

Since Specialization
Citations

This map shows the geographic impact of Drew Bryant'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 Drew Bryant with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Drew Bryant more than expected).

Fields of papers citing papers by Drew Bryant

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Drew Bryant. 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 Drew Bryant. The network helps show where Drew Bryant may publish in the future.

Co-authorship network of co-authors of Drew Bryant

This figure shows the co-authorship network connecting the top 25 collaborators of Drew Bryant. A scholar is included among the top collaborators of Drew Bryant 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 Drew Bryant. Drew Bryant is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

16 of 16 papers shown
1.
Bryant, Drew, Xiaoyu Qu, Avinava Dubey, et al.. (2024). Karyotype AI for Precision Oncology. Blood. 144(Supplement 1). 1544–1544.
2.
Fang, Min, Drew Bryant, Xiaoyu Qu, et al.. (2023). 42. Automated deep aberration detection from chromosome karyotype images. Cancer Genetics. 278-279. 13–13. 1 indexed citations
3.
Ahadi, Sara, Kenneth A. Wilson, Boris Babenko, et al.. (2023). Longitudinal fundus imaging and its genome-wide association analysis provide evidence for a human retinal aging clock. eLife. 12. 26 indexed citations
4.
Bileschi, Maxwell L., David Belanger, Drew Bryant, et al.. (2022). Using deep learning to annotate the protein universe. Nature Biotechnology. 40(6). 932–937. 164 indexed citations breakdown →
5.
Carter, Brandon, Maxwell L. Bileschi, Jamie Smith, et al.. (2019). Critiquing Protein Family Classification Models Using Sufficient Input Subsets. Journal of Computational Biology. 27(8). 1219–1231. 6 indexed citations
6.
Platt, John, et al.. (2017). Analyzing Energy Technologies and Policies Using DOSCOE. SSRN Electronic Journal. 1 indexed citations
7.
Bryant, Drew, Mark Moll, Paul W. Finn, & Lydia E. Kavraki. (2013). Combinatorial Clustering of Residue Position Subsets Predicts Inhibitor Affinity across the Human Kinome. PLoS Computational Biology. 9(6). e1003087–e1003087. 10 indexed citations
8.
Moll, Mark, Drew Bryant, & Lydia E. Kavraki. (2011). The LabelHash Server and Tools for substructure-based functional annotation. Bioinformatics. 27(15). 2161–2162. 4 indexed citations
9.
Moll, Mark, Drew Bryant, & Lydia E. Kavraki. (2010). The LabelHash algorithm for substructure matching. BMC Bioinformatics. 11(1). 555–555. 26 indexed citations
10.
Bryant, Drew, Mark Moll, Brian Y. Chen, Viacheslav Y. Fofanov, & Lydia E. Kavraki. (2010). Analysis of substructural variation in families of enzymatic proteins with applications to protein function prediction. BMC Bioinformatics. 11(1). 242–242. 12 indexed citations
11.
Fofanov, Viacheslav Y., Drew Bryant, Mark Moll, et al.. (2008). A statistical model to correct systematic bias introduced by algorithmic thresholds in protein structural comparison algorithms. 1–8. 9 indexed citations
12.
Chen, Brian Y., Drew Bryant, Viacheslav Y. Fofanov, et al.. (2007). COMPOSITE MOTIFS INTEGRATING MULTIPLE PROTEIN STRUCTURES INCREASE SENSITIVITY FOR FUNCTION PREDICTION. PubMed. 6. 343–355. 5 indexed citations
13.
Chen, Brian Y., Viacheslav Y. Fofanov, Drew Bryant, et al.. (2007). The MASH Pipeline for Protein Function Prediction and an Algorithm for the Geometric Refinement of 3D Motifs. Journal of Computational Biology. 14(6). 791–816. 31 indexed citations
14.
Chen, Brian Y., Drew Bryant, Viacheslav Y. Fofanov, et al.. (2007). CAVITY SCALING: AUTOMATED REFINEMENT OF CAVITY-AWARE MOTIFS IN PROTEIN FUNCTION PREDICTION. Journal of Bioinformatics and Computational Biology. 5(02a). 353–382. 11 indexed citations
15.
Chen, Brian Y., Drew Bryant, Viacheslav Y. Fofanov, et al.. (2006). CAVITY-AWARE MOTIFS REDUCE FALSE POSITIVES IN PROTEIN FUNCTION PREDICTION. PubMed. 311–323. 13 indexed citations
16.
Chen, Brian Y., Drew Bryant, Viacheslav Y. Fofanov, et al.. (2006). CAVITY-AWARE MOTIFS REDUCE FALSE POSITIVES IN PROTEIN FUNCTION PREDICTION. 1 indexed citations

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 delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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