Matthew J. O’Meara

11.0k total citations · 3 hit papers
29 papers, 2.7k citations indexed

About

Matthew J. O’Meara is a scholar working on Molecular Biology, Computational Theory and Mathematics and Infectious Diseases. According to data from OpenAlex, Matthew J. O’Meara has authored 29 papers receiving a total of 2.7k indexed citations (citations by other indexed papers that have themselves been cited), including 24 papers in Molecular Biology, 7 papers in Computational Theory and Mathematics and 6 papers in Infectious Diseases. Recurrent topics in Matthew J. O’Meara's work include Computational Drug Discovery Methods (6 papers), Protein Structure and Dynamics (5 papers) and RNA and protein synthesis mechanisms (4 papers). Matthew J. O’Meara is often cited by papers focused on Computational Drug Discovery Methods (6 papers), Protein Structure and Dynamics (5 papers) and RNA and protein synthesis mechanisms (4 papers). Matthew J. O’Meara collaborates with scholars based in United States, Canada and Ukraine. Matthew J. O’Meara's co-authors include Brian Kuhlman, Tanja Kortemme, David Baker, Andrew Leaver‐Fay, Frank DiMaio, Philip Bradley, Jeffrey J. Gray, Brian K. Shoichet, Bryan L. Roth and Yurii S. Moroz and has published in prestigious journals such as Nature, Nature Communications and PLoS ONE.

In The Last Decade

Matthew J. O’Meara

28 papers receiving 2.7k 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.

The Rosetta All-Atom Energy Function for Macromolecular Modeling and Design

2017 942 citations Rebecca F. Alford, Andrew Leaver‐Fay et al. Journal of Chemical Theory and Computation profile →
Ultra-large library docking for discovering new chemotypes

2019 619 citations Jiankun Lyu, Sheng Wang et al. Nature profile →
A human liver organoid screening platform for DILI risk prediction

2023 108 citations Charles J. Zhang, Matthew J. O’Meara et al. Journal of Hepatology profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Matthew J. O’Meara United States	17	2.0k	656	547	257	240	29	2.7k
Radka Svobodová Vařeková Czechia	19	2.3k 1.2×	423 0.6×	547 1.0×	178 0.7×	260 1.1×	69	3.4k
Alexander Rose Germany	18	2.1k 1.1×	553 0.8×	448 0.8×	124 0.5×	147 0.6×	46	3.0k
Jaime Prilusky Israel	25	3.9k 2.0×	438 0.7×	859 1.6×	291 1.1×	185 0.8×	40	5.0k
Herman van Vlijmen Belgium	38	3.1k 1.6×	1.3k 2.0×	784 1.4×	377 1.5×	207 0.9×	98	4.3k
Sameer Velankar United Kingdom	27	3.6k 1.8×	723 1.1×	845 1.5×	137 0.5×	219 0.9×	69	4.5k
Adrien S. J. Melquiond Netherlands	19	2.4k 1.2×	403 0.6×	381 0.7×	304 1.2×	312 1.3×	23	3.2k
Hao Fan Singapore	29	2.1k 1.1×	478 0.7×	368 0.7×	152 0.6×	133 0.6×	93	3.0k
Irina S. Moreira Portugal	26	2.1k 1.1×	539 0.8×	379 0.7×	302 1.2×	146 0.6×	86	2.7k
Sebastian Kmiecik Poland	29	2.7k 1.4×	512 0.8×	972 1.8×	353 1.4×	185 0.8×	83	3.5k
Robbie P. Joosten Netherlands	23	3.2k 1.6×	377 0.6×	1.2k 2.2×	149 0.6×	166 0.7×	50	4.1k

Countries citing papers authored by Matthew J. O’Meara

Since Specialization

Citations

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

Fields of papers citing papers by Matthew J. O’Meara

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Matthew J. O’Meara. 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 Matthew J. O’Meara. The network helps show where Matthew J. O’Meara may publish in the future.

Co-authorship network of co-authors of Matthew J. O’Meara

This figure shows the co-authorship network connecting the top 25 collaborators of Matthew J. O’Meara. A scholar is included among the top collaborators of Matthew J. O’Meara 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 Matthew J. O’Meara. Matthew J. O’Meara 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

Zhang, Chengxin, et al.. (2025). Predicting the structural impact of human alternative splicing. Genome biology. 26(1). 283–283.

O’Meara, Matthew J., Connie B. Nichols, Christina Alexandre, et al.. (2024). CryptoCEN: A Co-Expression Network for Cryptococcus neoformans reveals novel proteins involved in DNA damage repair. PLoS Genetics. 20(2). e1011158–e1011158. 4 indexed citations

Visser, Noelle D., Kevin R. Amses, Andrea Hodgins-Davis, et al.. (2023). Candida albicans selection for human commensalism results in substantial within-host diversity without decreasing fitness for invasive disease. PLoS Biology. 21(5). e3001822–e3001822. 30 indexed citations

Zhang, Charles J., Matthew J. O’Meara, Sha Huang, et al.. (2023). A human liver organoid screening platform for DILI risk prediction. Journal of Hepatology. 78(5). 998–1006. 108 indexed citations breakdown →

Zhang, Jeffrey, et al.. (2023). Multiple ParA/MinD ATPases coordinate the positioning of disparate cargos in a bacterial cell. Nature Communications. 14(1). 3255–3255. 12 indexed citations

O’Meara, Matthew J., et al.. (2023). Imaging-Based Screening Identifies Modulators of the eIF3 Translation Initiation Factor Complex in Candida albicans. Antimicrobial Agents and Chemotherapy. 67(7). e0050323–e0050323. 3 indexed citations

Wotring, Jesse W., Charles J. Zhang, Carmen Mirabelli, et al.. (2022). In Vitro Evaluation and Mitigation of Niclosamide’s Liabilities as a COVID-19 Treatment. Vaccines. 10(8). 1284–1284. 3 indexed citations

Ponzoni, Luca, Jessica L. McKinley, Matthew J. O’Meara, et al.. (2022). Prioritizing Virtual Screening with Interpretable Interaction Fingerprints. Journal of Chemical Information and Modeling. 62(18). 4300–4318. 22 indexed citations

Alon, Assaf, Jiankun Lyu, João M. Bráz, et al.. (2021). Structures of the σ2 receptor enable docking for bioactive ligand discovery. Nature. 600(7890). 759–764. 135 indexed citations

10.

Kalinin, Alexandr A., Alex Ade, Walter Meixner, et al.. (2021). Valproic acid-induced changes of 4D nuclear morphology in astrocyte cells. Molecular Biology of the Cell. 32(18). 1624–1633. 9 indexed citations

11.

Jankowiak, Martin, et al.. (2020). A Unified Stochastic Gradient Approach to Designing Bayesian-Optimal Experiments.. International Conference on Artificial Intelligence and Statistics. 2959–2969. 1 indexed citations

12.

O’Meara, Teresa R., Matthew J. O’Meara, Elizabeth J. Polvi, et al.. (2019). Global proteomic analyses define an environmentally contingent Hsp90 interactome and reveal chaperone-dependent regulation of stress granule proteins and the R2TP complex in a fungal pathogen. PLoS Biology. 17(7). e3000358–e3000358. 36 indexed citations

13.

Lyu, Jiankun, Sheng Wang, Trent E. Balius, et al.. (2019). Ultra-large library docking for discovering new chemotypes. Nature. 566(7743). 224–229. 619 indexed citations breakdown →

14.

Hettiaratchi, Marian H., et al.. (2019). Local delivery of stabilized chondroitinase ABC degrades chondroitin sulfate proteoglycans in stroke-injured rat brains. Journal of Controlled Release. 297. 14–25. 43 indexed citations

15.

O’Meara, Teresa R., Michelle E. Maxson, Ryan G. Gaudet, et al.. (2018). High-Throughput Screening Identifies Genes Required for Candida albicans Induction of Macrophage Pyroptosis. mBio. 9(4). 53 indexed citations

16.

Calhoun, Sara, Magdalena Korczynska, Brian San Francisco, et al.. (2018). Prediction of enzymatic pathways by integrative pathway mapping. eLife. 7. 30 indexed citations

17.

Alford, Rebecca F., Andrew Leaver‐Fay, Jeliazko R. Jeliazkov, et al.. (2017). The Rosetta All-Atom Energy Function for Macromolecular Modeling and Design. Journal of Chemical Theory and Computation. 13(6). 3031–3048. 942 indexed citations breakdown →

18.

O’Meara, Matthew J., Sara Ballouz, Brian K. Shoichet, & Jesse Gillis. (2016). Ligand Similarity Complements Sequence, Physical Interaction, and Co-Expression for Gene Function Prediction. PLoS ONE. 11(7). e0160098–e0160098. 12 indexed citations

19.

Harrison, Joseph S., et al.. (2013). Role of Electrostatic Repulsion in Controlling pH-Dependent Conformational Changes of Viral Fusion Proteins. Structure. 21(7). 1085–1096. 49 indexed citations

20.

Leaver‐Fay, Andrew, Matthew J. O’Meara, Mike Tyka, et al.. (2013). Scientific Benchmarks for Guiding Macromolecular Energy Function Improvement. Methods in enzymology on CD-ROM/Methods in enzymology. 523. 109–143. 163 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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