Jonathan K. Pritchard

127.1k total citations · 30 hit papers
182 papers, 77.5k citations indexed

About

Jonathan K. Pritchard is a scholar working on Genetics, Molecular Biology and Cancer Research. According to data from OpenAlex, Jonathan K. Pritchard has authored 182 papers receiving a total of 77.5k indexed citations (citations by other indexed papers that have themselves been cited), including 107 papers in Genetics, 101 papers in Molecular Biology and 14 papers in Cancer Research. Recurrent topics in Jonathan K. Pritchard's work include Genetic Associations and Epidemiology (56 papers), Genetic Mapping and Diversity in Plants and Animals (35 papers) and Genomics and Chromatin Dynamics (30 papers). Jonathan K. Pritchard is often cited by papers focused on Genetic Associations and Epidemiology (56 papers), Genetic Mapping and Diversity in Plants and Animals (35 papers) and Genomics and Chromatin Dynamics (30 papers). Jonathan K. Pritchard collaborates with scholars based in United States, United Kingdom and Germany. Jonathan K. Pritchard's co-authors include Matthew Stephens, Peter Donnelly, Daniel Falush, Joseph K. Pickrell, Noah A. Rosenberg, Yoav Gilad, Yang Li, Sridhar Kudaravalli, Xiaoquan Wen and Benjamin F. Voight and has published in prestigious journals such as Nature, Science and Cell.

In The Last Decade

Jonathan K. Pritchard

176 papers receiving 75.6k citations

Hit Papers

Inference of Population Structure Using Multilocus Genoty... 1999 2026 2008 2017 2000 2003 2007 2009 2002 5.0k 10.0k 15.0k 20.0k 25.0k

Peers

Jonathan K. Pritchard
Matthew Stephens United States
Peter Donnelly United Kingdom
Laurent Excoffier Switzerland
Michael Lynch United States
Alexei J. Drummond New Zealand
Rasmus Nielsen United States
Marc A. Suchard United States
Matthew Stephens United States
Jonathan K. Pritchard
Citations per year, relative to Jonathan K. Pritchard Jonathan K. Pritchard (= 1×) peers Matthew Stephens

Countries citing papers authored by Jonathan K. Pritchard

Since Specialization
Citations

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

Fields of papers citing papers by Jonathan K. Pritchard

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jonathan K. Pritchard

This figure shows the co-authorship network connecting the top 25 collaborators of Jonathan K. Pritchard. A scholar is included among the top collaborators of Jonathan K. Pritchard 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 K. Pritchard. Jonathan K. Pritchard 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.
Li, Qin, Michael J. Gloudemans, Jonathan M. Geisinger, et al.. (2022). RNA editing underlies genetic risk of common inflammatory diseases. Nature. 608(7923). 569–577. 95 indexed citations
2.
Trevino, Alexandro E., Nasa Sinnott-Armstrong, Jimena Andersen, et al.. (2020). Chromatin accessibility dynamics in a model of human forebrain development. Science. 367(6476). 149 indexed citations
3.
Mostafavi, Hakhamanesh, Arbel Harpak, Ipsita Agarwal, et al.. (2020). Variable prediction accuracy of polygenic scores within an ancestry group. eLife. 9. 225 indexed citations breakdown →
4.
Berg, Jeremy J., Arbel Harpak, Nasa Sinnott-Armstrong, et al.. (2019). Reduced signal for polygenic adaptation of height in UK Biobank. eLife. 8. 209 indexed citations
5.
Knowles, David A., Courtney K. Burrows, John Blischak, et al.. (2018). Determining the genetic basis of anthracycline-cardiotoxicity by molecular response QTL mapping in induced cardiomyocytes. eLife. 7. 71 indexed citations
6.
Harpak, Arbel, Xun Lan, Ziyue Gao, & Jonathan K. Pritchard. (2017). Frequent nonallelic gene conversion on the human lineage and its effect on the divergence of gene duplicates. Proceedings of the National Academy of Sciences. 114(48). 12779–12784. 29 indexed citations
7.
Sharon, Eilon, Hao Shi, Sandhya Kharbanda, et al.. (2017). Quantification of transplant-derived circulating cell-free DNA in absence of a donor genotype. PLoS Computational Biology. 13(8). e1005629–e1005629. 65 indexed citations
8.
Field, Yair, Evan A. Boyle, Natalie Telis, et al.. (2016). Detection of human adaptation during the past 2000 years. Science. 354(6313). 760–764. 233 indexed citations
9.
Kumar, Santosh, et al.. (2016). Whole Genome Sequencing Identifies a Novel Factor Required for Secretory Granule Maturation in Tetrahymena thermophila. G3 Genes Genomes Genetics. 6(8). 2505–2516. 9 indexed citations
10.
Lan, Xun & Jonathan K. Pritchard. (2016). Coregulation of tandem duplicate genes slows evolution of subfunctionalization in mammals. Science. 352(6288). 1009–1013. 123 indexed citations
11.
Li, Yang, Bryce van de Geijn, Anil Raj, et al.. (2016). RNA splicing is a primary link between genetic variation and disease. Science. 352(6285). 600–604. 382 indexed citations breakdown →
12.
Raj, Anil, Sidney H. Wang, Heejung Shim, et al.. (2016). Thousands of novel translated open reading frames in humans inferred by ribosome footprint profiling. eLife. 5. 109 indexed citations
13.
Harpak, Arbel, Anand Bhaskar, & Jonathan K. Pritchard. (2016). Mutation Rate Variation is a Primary Determinant of the Distribution of Allele Frequencies in Humans. PLoS Genetics. 12(12). e1006489–e1006489. 42 indexed citations
14.
Raj, Anil, Matthew Stephens, & Jonathan K. Pritchard. (2014). fastSTRUCTURE: Variational Inference of Population Structure in Large SNP Data Sets. Genetics. 197(2). 573–589. 1149 indexed citations breakdown →
15.
Zhou, Xiang, Carolyn E Cain, Marsha Myrthil, et al.. (2014). Epigenetic modifications are associated with inter-species gene expression variation in primates. Genome biology. 15(12). 547–547. 53 indexed citations
16.
Perry, George H., Páll Melsted, John C. Marioni, et al.. (2011). Comparative RNA sequencing reveals substantial genetic variation in endangered primates. Genome Research. 22(4). 602–610. 102 indexed citations
17.
Hancock, Angela M., David Witonsky, Edvard Ehler, et al.. (2010). Human adaptations to diet, subsistence, and ecoregion are due to subtle shifts in allele frequency. Proceedings of the National Academy of Sciences. 107(supplement_2). 8924–8930. 192 indexed citations
18.
Noonan, James P., Graham Coop, Sridhar Kudaravalli, et al.. (2006). Sequencing and Analysis of Neanderthal Genomic DNA. Science. 314(5802). 1113–1118. 359 indexed citations breakdown →
19.
Zöllner, Sebastian & Jonathan K. Pritchard. (2004). Coalescent-Based Association Mapping and Fine Mapping of Complex Trait Loci. Genetics. 169(2). 1071–1092. 94 indexed citations
20.
Falush, Daniel, Thierry Wirth, Bodo Linz, et al.. (2003). Traces of Human Migrations in Helicobacter pylori Populations. Science. 299(5612). 1582–1585. 742 indexed citations breakdown →

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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