Jonathan Terhorst

2.6k total citations · 1 hit paper
26 papers, 1.1k citations indexed

About

Jonathan Terhorst is a scholar working on Genetics, Molecular Biology and Artificial Intelligence. According to data from OpenAlex, Jonathan Terhorst has authored 26 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Genetics, 10 papers in Molecular Biology and 4 papers in Artificial Intelligence. Recurrent topics in Jonathan Terhorst's work include Genetic diversity and population structure (11 papers), Genetic Mapping and Diversity in Plants and Animals (7 papers) and Genetic Associations and Epidemiology (6 papers). Jonathan Terhorst is often cited by papers focused on Genetic diversity and population structure (11 papers), Genetic Mapping and Diversity in Plants and Animals (7 papers) and Genetic Associations and Epidemiology (6 papers). Jonathan Terhorst collaborates with scholars based in United States, United Kingdom and Switzerland. Jonathan Terhorst's co-authors include Yun S. Song, Jack Kamm, Richard Durbin, Christian Schlötterer, Pier Francesco Palamara, Iain Mathieson, Alkes L. Price, Joshua D. Reuther, Martin Sikora and Anna‐Sapfo Malaspinas and has published in prestigious journals such as Nature, Science and Cell.

In The Last Decade

Jonathan Terhorst

23 papers receiving 1.1k citations

Hit Papers

Robust and scalable inference of population history from ... 2016 2026 2019 2022 2016 100 200 300 400
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. Robust and scalable inference of population history from hundreds of unphased whole genomes
    2016 489 citations Jonathan Terhorst, Jack Kamm et al. Nature Genetics profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jonathan Terhorst United States 11 749 325 127 125 117 26 1.1k
Michael DeGiorgio United States 20 865 1.2× 470 1.4× 110 0.9× 141 1.1× 124 1.1× 57 1.2k
Jack Kamm United States 10 630 0.8× 269 0.8× 92 0.7× 116 0.9× 113 1.0× 15 951
Flora Jay France 13 730 1.0× 223 0.7× 99 0.8× 166 1.3× 70 0.6× 23 1.1k
Jerome Kelleher United Kingdom 16 947 1.3× 386 1.2× 52 0.4× 89 0.7× 85 0.7× 31 1.2k
Ilan Gronau Israel 15 1.1k 1.4× 727 2.2× 100 0.8× 283 2.3× 147 1.3× 26 1.6k
Andrea Benazzo Italy 19 562 0.8× 227 0.7× 57 0.4× 205 1.6× 137 1.2× 35 965
Asger Hobolth Denmark 19 820 1.1× 743 2.3× 141 1.1× 81 0.6× 191 1.6× 66 1.4k
Aakrosh Ratan United States 26 627 0.8× 846 2.6× 139 1.1× 288 2.3× 239 2.0× 68 1.8k
Stefano Mona France 22 888 1.2× 298 0.9× 90 0.7× 335 2.7× 88 0.8× 43 1.3k
Alison Etheridge United Kingdom 21 1.1k 1.5× 350 1.1× 47 0.4× 132 1.1× 106 0.9× 55 1.8k

Countries citing papers authored by Jonathan Terhorst

Since Specialization
Citations

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

Fields of papers citing papers by Jonathan Terhorst

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jonathan Terhorst

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

All Works

20 of 20 papers shown
1.
Castro, Constanza de la Fuente, Arjun Biddanda, David Witonsky, et al.. (2025). Population histories of the Indigenous Adivasi and Sinhalese from Sri Lanka using whole genomes. Current Biology. 35(11). 2554–2566.e7.
2.
Gründler, Michael C., Jonathan Terhorst, & Gideon S. Bradburd. (2025). A geographic history of human genetic ancestry. Science. 387(6741). 1391–1397. 5 indexed citations
3.
Terhorst, Jonathan. (2025). Accelerated Bayesian inference of population size history from recombining sequence data. Nature Genetics. 57(10). 2570–2577.
4.
Terhorst, Jonathan, et al.. (2023). Identifiability and inference of phylogenetic birth–death models. Journal of Theoretical Biology. 568. 111520–111520. 8 indexed citations
5.
Fan, Shaohua, Jeffrey P. Spence, Yuanqing Feng, et al.. (2023). Whole-genome sequencing reveals a complex African population demographic history and signatures of local adaptation. Cell. 186(5). 923–939.e14. 44 indexed citations
6.
Terhorst, Jonathan, et al.. (2023). Exact Decoding of a Sequentially Markov Coalescent Model in Genetics. Journal of the American Statistical Association. 119(547). 2242–2255. 3 indexed citations
7.
Terhorst, Jonathan, et al.. (2022). Variational Phylodynamic Inference Using Pandemic-scale Data. Molecular Biology and Evolution. 39(8). 6 indexed citations
8.
Terhorst, Jonathan, et al.. (2022). Robust detection of natural selection using a probabilistic model of tree imbalance. Genetics. 220(3). 1 indexed citations
9.
Terhorst, Jonathan, et al.. (2022). A class of identifiable phylogenetic birth–death models. Proceedings of the National Academy of Sciences. 119(35). e2119513119–e2119513119. 18 indexed citations
10.
Terhorst, Jonathan, et al.. (2022). Rates of convergence in the two-island and isolation-with-migration models. Theoretical Population Biology. 147. 16–27. 3 indexed citations
11.
Mathieson, Iain & Jonathan Terhorst. (2022). Direct detection of natural selection in Bronze Age Britain. Genome Research. 32(11-12). 2057–2067. 22 indexed citations
12.
Gao, Zheng, Jonathan Terhorst, Cristopher V. Van Hout, & Stilian Stoev. (2019). U-PASS: unified power analysis and forensics for qualitative traits in genetic association studies. Bioinformatics. 36(3). 974–975. 1 indexed citations
13.
Kamm, Jack, Jonathan Terhorst, Richard Durbin, & Yun S. Song. (2019). Efficiently Inferring the Demographic History of Many Populations With Allele Count Data. Journal of the American Statistical Association. 115(531). 1472–1487. 89 indexed citations
14.
Palamara, Pier Francesco, Jonathan Terhorst, Yun S. Song, & Alkes L. Price. (2018). High-throughput inference of pairwise coalescence times identifies signals of selection and enriched disease heritability. Nature Genetics. 50(9). 1311–1317. 42 indexed citations
15.
Moreno-Mayar, J. Víctor, Ben A. Potter, Lasse Vinner, et al.. (2018). Terminal Pleistocene Alaskan genome reveals first founding population of Native Americans. Nature. 553(7687). 203–207. 176 indexed citations
16.
Terhorst, Jonathan, Jack Kamm, & Yun S. Song. (2016). Robust and scalable inference of population history from hundreds of unphased whole genomes. Nature Genetics. 49(2). 303–309. 489 indexed citations breakdown →
17.
Dodson, Anne E., et al.. (2016). Riches of phenotype computationally extracted from microbial colonies. Proceedings of the National Academy of Sciences. 113(20). E2822–31. 5 indexed citations
18.
Terhorst, Jonathan, Christian Schlötterer, & Yun S. Song. (2015). Multi-locus Analysis of Genomic Time Series Data from Experimental Evolution. PLoS Genetics. 11(4). e1005069–e1005069. 45 indexed citations
19.
Talwalkar, Ameet, Christopher Hartl, Jonathan Terhorst, et al.. (2013). SMASH: A Benchmarking Toolkit for Variant Calling. arXiv (Cornell University). 2 indexed citations
20.
Terhorst, Jonathan, et al.. (2010). Effect of coal-fired power generation on visibility in a nearby national park. Atmospheric Environment. 44(21-22). 2524–2531.

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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