Lucy J. Colwell

9.8k total citations · 3 hit papers
44 papers, 3.1k citations indexed

About

Lucy J. Colwell is a scholar working on Molecular Biology, Computational Theory and Mathematics and Biomaterials. According to data from OpenAlex, Lucy J. Colwell has authored 44 papers receiving a total of 3.1k indexed citations (citations by other indexed papers that have themselves been cited), including 35 papers in Molecular Biology, 8 papers in Computational Theory and Mathematics and 4 papers in Biomaterials. Recurrent topics in Lucy J. Colwell's work include Protein Structure and Dynamics (17 papers), RNA and protein synthesis mechanisms (13 papers) and Machine Learning in Bioinformatics (12 papers). Lucy J. Colwell is often cited by papers focused on Protein Structure and Dynamics (17 papers), RNA and protein synthesis mechanisms (13 papers) and Machine Learning in Bioinformatics (12 papers). Lucy J. Colwell collaborates with scholars based in United Kingdom, United States and Germany. Lucy J. Colwell's co-authors include Robert P. Sheridan, Thomas A. Hopf, Debora S. Marks, Chris Sander, L. Mitchell, Andrea Pagnani, Riccardo Zecchina, Burkhard Rost, Michael P. Brenner and Maxwell L. Bileschi and has published in prestigious journals such as Nature, Cell and Proceedings of the National Academy of Sciences.

In The Last Decade

Lucy J. Colwell

42 papers receiving 3.0k citations

Hit Papers

align trajectories

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.

Protein 3D Structure Computed from Evolutionary Sequence Variation

2011 762 citations Debora S. Marks, Lucy J. Colwell et al. PLoS ONE profile →
Predicting multiple conformations via sequence clustering and AlphaFold2

2023 233 citations Hannah K. Wayment-Steele, Adedolapo Ojoawo et al. Nature profile →
Using deep learning to annotate the protein universe

2022 164 citations Maxwell L. Bileschi, David Belanger et al. Nature Biotechnology profile →

Peers

Lucy J. Colwell

RNMI

CTM

GENET

Brian Hie United States

Alexander Rives United States

Ivan Anishchenko United States

Vikram Khipple Mulligan United States

Tom Sercu United States

Marc De Maeyer Belgium

Manuela Helmer‐Citterich Italy

P. Douglas Renfrew United States

Maxim V. Shapovalov United States

Jaap Heringa Netherlands

Brian Hie United States

Lucy J. Colwell

2.9k ×1.2

325 ×0.6

297 ×0.8

RNMI

432 ×1.4

CTM

250 ×0.8

GENET

Citations per year, relative to Lucy J. Colwell Lucy J. Colwell (= 1×) peers Brian Hie

Countries citing papers authored by Lucy J. Colwell

Since Specialization

Citations

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

Fields of papers citing papers by Lucy J. Colwell

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Lucy J. Colwell. 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 Lucy J. Colwell. The network helps show where Lucy J. Colwell may publish in the future.

Co-authorship network of co-authors of Lucy J. Colwell

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

All Works

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20 of 20 papers shown

Wayment-Steele, Hannah K., Sergey Ovchinnikov, Lucy J. Colwell, & Dorothee Kern. (2025). Does Sequence Clustering Confound AlphaFold2?. Journal of Molecular Biology. 437(21). 169376–169376.

Paysan‐Lafosse, Typhaine, Antonina Andreeva, Matthias Blum, et al.. (2024). The Pfam protein families database: embracing AI/ML. Nucleic Acids Research. 53(D1). D523–D534. 49 indexed citations

Andreeva, Antonina, et al.. (2024). Investigation of protein family relationships with deep learning. Bioinformatics Advances. 4(1). vbae132–vbae132. 1 indexed citations

Wayment-Steele, Hannah K., Adedolapo Ojoawo, Renee Otten, et al.. (2023). Predicting multiple conformations via sequence clustering and AlphaFold2. Nature. 625(7996). 832–839. 233 indexed citations breakdown →

Sanderson, Theo, Maxwell L. Bileschi, David Belanger, & Lucy J. Colwell. (2023). ProteInfer, deep neural networks for protein functional inference. eLife. 12. 82 indexed citations

Pomberger, Alexander, Asif Iqbal Khan, Connor J. Taylor, et al.. (2022). The effect of chemical representation on active machine learning towards closed-loop optimization. Reaction Chemistry & Engineering. 7(6). 1368–1379. 34 indexed citations

Frenkel, Daan, et al.. (2022). Using sequence data to predict the self-assembly of supramolecular collagen structures. Biophysical Journal. 121(16). 3023–3033. 4 indexed citations

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 →

Angermueller, Christof, et al.. (2020). Model-based reinforcement learning for biological sequence design. International Conference on Learning Representations. 19 indexed citations

10.

Sánchez-Lengeling, Benjamín, Jennifer N. Wei, Brian K. Lee, et al.. (2020). Evaluating Attribution for Graph Neural Networks. Neural Information Processing Systems. 33. 5898–5910. 31 indexed citations

11.

McCloskey, Kevin, Ankur Taly, Federico Monti, Michael P. Brenner, & Lucy J. Colwell. (2019). Using attribution to decode binding mechanism in neural network models for chemistry. Proceedings of the National Academy of Sciences. 116(24). 11624–11629. 60 indexed citations

12.

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

13.

Colwell, Lucy J.. (2018). Statistical and machine learning approaches to predicting protein–ligand interactions. Current Opinion in Structural Biology. 49. 123–128. 40 indexed citations

14.

Chow, Wing Ying, Christopher J. Forman, Dominique Bihan, et al.. (2018). Proline provides site-specific flexibility for in vivo collagen. Scientific Reports. 8(1). 13809–13809. 47 indexed citations

15.

Bitbol, Anne‐Florence, et al.. (2016). Inferring interaction partners from protein sequences. Proceedings of the National Academy of Sciences. 113(43). 12180–12185. 87 indexed citations

16.

Townsend, Philip D., Thomas L. Rodgers, Shane A. Richards, et al.. (2015). The Role of Protein-Ligand Contacts in Allosteric Regulation of the Escherichia coli Catabolite Activator Protein. Journal of Biological Chemistry. 290(36). 22225–22235. 25 indexed citations

17.

Colwell, Lucy J., Qin Yu, Miriam Huntley, Alexander Manta, & Michael P. Brenner. (2014). Feynman-Hellmann Theorem and Signal Identification from Sample Covariance Matrices. Physical Review X. 4(3). 4 indexed citations

18.

Marks, Debora S., Lucy J. Colwell, Robert P. Sheridan, et al.. (2011). Protein 3D Structure Computed from Evolutionary Sequence Variation. PLoS ONE. 6(12). e28766–e28766. 762 indexed citations breakdown →

19.

Colwell, Lucy J. & Michael P. Brenner. (2009). Action Potential Initiation in the Hodgkin-Huxley Model. PLoS Computational Biology. 5(1). e1000265–e1000265. 22 indexed citations

20.

Elliott, Paul, Jane Shipley, Scott Tulloch, et al.. (1988). Correction: Calculating confidence intervals for regression and correlation. BMJ. 297(6644). 328–328.

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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