William S. DeWitt

2.7k total citations · 1 hit paper
30 papers, 1.3k citations indexed

About

William S. DeWitt is a scholar working on Molecular Biology, Immunology and Genetics. According to data from OpenAlex, William S. DeWitt has authored 30 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Molecular Biology, 11 papers in Immunology and 6 papers in Genetics. Recurrent topics in William S. DeWitt's work include T-cell and B-cell Immunology (11 papers), Genomics and Phylogenetic Studies (9 papers) and Single-cell and spatial transcriptomics (4 papers). William S. DeWitt is often cited by papers focused on T-cell and B-cell Immunology (11 papers), Genomics and Phylogenetic Studies (9 papers) and Single-cell and spatial transcriptomics (4 papers). William S. DeWitt collaborates with scholars based in United States, South Africa and Germany. William S. DeWitt's co-authors include Ryan Emerson, Harlan Robins, Marissa Vignali, John A. Hansen, F. A. Matsen, Christopher S. Carlson, Cindy Desmarais, Delasa Aghamirzaie, Jay Shendure and Darren A. Cusanovich and has published in prestigious journals such as Nature, Cell and Proceedings of the National Academy of Sciences.

In The Last Decade

William S. DeWitt

26 papers receiving 1.3k 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.

A Single-Cell Atlas of In Vivo Mammalian Chromatin Accessibility

2018 474 citations William S. DeWitt et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
William S. DeWitt United States	14	777	589	156	142	142	30	1.3k
Sanjay Srivatsan United States	17	1.3k 1.6×	420 0.7×	135 0.9×	86 0.6×	99 0.7×	27	1.7k
Franziska Hoffmann Germany	17	407 0.5×	438 0.7×	137 0.9×	70 0.5×	46 0.3×	44	1.0k
Michael J. T. Stubbington United Kingdom	15	1.2k 1.6×	908 1.5×	231 1.5×	48 0.3×	162 1.1×	22	1.9k
Judy L. Cannon United States	21	426 0.5×	956 1.6×	233 1.5×	98 0.7×	55 0.4×	46	1.6k
William O’Gorman United States	18	638 0.8×	807 1.4×	411 2.6×	40 0.3×	227 1.6×	29	1.6k
Dhaya Seshasayee United States	18	722 0.9×	1.2k 2.0×	272 1.7×	281 2.0×	181 1.3×	29	2.1k
Kevin S. Kao United States	14	499 0.6×	771 1.3×	283 1.8×	113 0.8×	83 0.6×	26	1.6k
Gerben Bouma United Kingdom	24	509 0.7×	695 1.2×	200 1.3×	37 0.3×	398 2.8×	37	1.4k
Heather J. Melichar Canada	19	302 0.4×	886 1.5×	203 1.3×	45 0.3×	89 0.6×	51	1.3k
Jeffrey C. Nolz United States	23	397 0.5×	1.5k 2.5×	430 2.8×	92 0.6×	69 0.5×	35	2.0k

Countries citing papers authored by William S. DeWitt

Since Specialization

Citations

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

Fields of papers citing papers by William S. DeWitt

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by William S. DeWitt. 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 William S. DeWitt. The network helps show where William S. DeWitt may publish in the future.

Co-authorship network of co-authors of William S. DeWitt

This figure shows the co-authorship network connecting the top 25 collaborators of William S. DeWitt. A scholar is included among the top collaborators of William S. DeWitt 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 William S. DeWitt. William S. DeWitt 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

Haddox, Hugh K., Jared Galloway, Angie S. Hinrichs, et al.. (2025). The mutation rate of SARS-CoV-2 is highly variable between sites and is influenced by sequence context, genomic region, and RNA structure. Nucleic Acids Research. 53(11). 3 indexed citations

Deng, Yun, William S. DeWitt, Yun S. Song, & Rasmus Nielsen. (2025). A general framework for branch length estimation in Ancestral Recombination Graphs. Proceedings of the National Academy of Sciences. 122(48). e2504461122–e2504461122.

Pae, Juhee, William S. DeWitt, Juliana Bortolatto, et al.. (2025). Transient silencing of hypermutation preserves B cell affinity during clonal bursting. Nature. 641(8062). 486–494. 7 indexed citations

Ralph, Duncan, et al.. (2025). Leveraging DAGs to improve context-sensitive and abundance-aware tree estimation. Philosophical Transactions of the Royal Society B Biological Sciences. 380(1919). 20230315–20230315. 2 indexed citations

Hsu, Chloe, William S. DeWitt, Jennifer Listgarten, et al.. (2025). Learning antibody sequence constraints from allelic inclusion. Cell Systems. 16(9). 101368–101368.

Chan, Philip A., et al.. (2024). Early adopters of doxycycline as post-exposure prophylaxis to prevent bacterial sexually transmitted infections in a real-world clinical setting. Sexually Transmitted Infections. 100(6). 339–342. 8 indexed citations

Boyle, Gabriel, Katherine A. Sitko, Jared Galloway, et al.. (2024). Deep mutational scanning of CYP2C19 in human cells reveals a substrate specificity-abundance tradeoff. Genetics. 228(3). 5 indexed citations

DeWitt, William S., et al.. (2024). Mean-field interacting multi-type birth–death processes with a view to applications in phylodynamics. Theoretical Population Biology. 159. 1–12.

DeWitt, William S., et al.. (2023). Representing and extending ensembles of parsimonious evolutionary histories with a directed acyclic graph. Journal of Mathematical Biology. 87(5). 75–75. 4 indexed citations

10.

DeWitt, William S., Luke Zhu, Mitchell R. Vollger, et al.. (2023). mutyper: assigning and summarizing mutation types foranalyzing germline mutation spectra. The Journal of Open Source Software. 8(85). 5227–5227. 2 indexed citations

11.

Yu, Timothy C., William W. Hannon, William S. DeWitt, et al.. (2022). A biophysical model of viral escape from polyclonal antibodies. Virus Evolution. 8(2). veac110–veac110. 19 indexed citations

12.

DeWitt, William S., Kameron Decker Harris, Aaron P. Ragsdale, & Kelley Harris. (2021). Nonparametric coalescent inference of mutation spectrum history and demography. Proceedings of the National Academy of Sciences. 118(21). 30 indexed citations

13.

Magee, Andrew F., Sarah K. Hilton, & William S. DeWitt. (2021). Robustness of Phylogenetic Inference to Model Misspecification Caused by Pairwise Epistasis. Molecular Biology and Evolution. 38(10). 4603–4615. 5 indexed citations

14.

Lv, Huibin, Jakub Otwinowski, William S. DeWitt, et al.. (2021). Dynamics of B cell repertoires and emergence of cross-reactive responses in patients with different severities of COVID-19. Cell Reports. 35(8). 109173–109173. 30 indexed citations

15.

Carlson, Jedidiah, William S. DeWitt, & Kelley Harris. (2020). Inferring evolutionary dynamics of mutation rates through the lens of mutation spectrum variation. Current Opinion in Genetics & Development. 62. 50–57. 14 indexed citations

16.

Davidsen, Kristian, William S. DeWitt, Jean Feng, et al.. (2019). Deep generative models for T cell receptor protein sequences. eLife. 8. 47 indexed citations

17.

DeWitt, William S., Krystle K. Q. Yu, Damien B. Wilburn, et al.. (2018). A Diverse Lipid Antigen–Specific TCR Repertoire Is Clonally Expanded during Active Tuberculosis. The Journal of Immunology. 201(3). 888–896. 26 indexed citations

18.

Emerson, Ryan, William S. DeWitt, Marissa Vignali, et al.. (2017). Immunosequencing identifies signatures of cytomegalovirus exposure history and HLA-mediated effects on the T cell repertoire. Nature Genetics. 49(5). 659–665. 287 indexed citations

19.

DeWitt, William S., Paul Lindau, Thomas M. Snyder, et al.. (2016). A Public Database of Memory and Naive B-Cell Receptor Sequences. PLoS ONE. 11(8). e0160853–e0160853. 80 indexed citations

20.

Wu, Junru, et al.. (2003). Nonlinear behaviors of contrast agents relevant to diagnostic and therapeutic applications. Ultrasound in Medicine & Biology. 29(4). 555–562. 20 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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