Arun Durvasula

2.0k total citations · 1 hit paper
17 papers, 808 citations indexed

About

Arun Durvasula is a scholar working on Genetics, Molecular Biology and Anthropology. According to data from OpenAlex, Arun Durvasula has authored 17 papers receiving a total of 808 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Genetics, 6 papers in Molecular Biology and 4 papers in Anthropology. Recurrent topics in Arun Durvasula's work include Genetic diversity and population structure (5 papers), Pleistocene-Era Hominins and Archaeology (4 papers) and Genetic Associations and Epidemiology (4 papers). Arun Durvasula is often cited by papers focused on Genetic diversity and population structure (5 papers), Pleistocene-Era Hominins and Archaeology (4 papers) and Genetic Associations and Epidemiology (4 papers). Arun Durvasula collaborates with scholars based in United States, Denmark and United Kingdom. Arun Durvasula's co-authors include Sriram Sankararaman, Kirk E. Lohmueller, Angela M. Hancock, Peter Andolfatto, Molly Przeworski, John C. Blazier, Chenling Xu, Laurits Skov, Gil G. Rosenthal and Daniel L. Powell and has published in prestigious journals such as Science, Proceedings of the National Academy of Sciences and Nature Communications.

In The Last Decade

Arun Durvasula

17 papers receiving 798 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.

Natural selection interacts with recombination to shape the evolution of hybrid genomes

2018 256 citations Molly Schumer, Chenling Xu et al. Science profile →

Peers

Arun Durvasula

GENET

MB

PS

EEBS

ECOLO

Andrew Tedder United Kingdom

Daniela R. Lacerda Brazil

Daniel L. Powell United States

Colin Groves Australia

Alexandre Gouy Switzerland

Katharine L. Korunes United States

Joel Sharbrough United States

Fedor Sharko Russia

J.-F. Ducroz France

Shaohong Feng China

Andrew Tedder United Kingdom

Arun Durvasula

332 ×0.6

GENET

348 ×1.2

MB

236 ×1.1

PS

258 ×2.5

EEBS

99 ×1.2

ECOLO

Citations per year, relative to Arun Durvasula Arun Durvasula (= 1×) peers Andrew Tedder

Countries citing papers authored by Arun Durvasula

Since Specialization

Citations

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

Fields of papers citing papers by Arun Durvasula

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Arun Durvasula

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

All Works

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17 of 17 papers shown

1.

Durvasula, Arun, et al.. (2025). Insufficient Evidence for a Severe Bottleneck in Humans During the Early to Middle Pleistocene Transition. Molecular Biology and Evolution. 42(2). 1 indexed citations

2.

Durvasula, Arun & Alkes L. Price. (2025). Distinct explanations underlie gene-environment interactions in the UK Biobank. The American Journal of Human Genetics. 112(3). 644–658. 4 indexed citations

3.

Zhang, Xinjun, et al.. (2023). MaLAdapt Reveals Novel Targets of Adaptive Introgression From Neanderthals and Denisovans in Worldwide Human Populations. Molecular Biology and Evolution. 40(1). 18 indexed citations

4.

Zhang, Martin Jinye, Arun Durvasula, Michael Inouye, et al.. (2023). Age-dependent topic modeling of comorbidities in UK Biobank identifies disease subtypes with differential genetic risk. Nature Genetics. 55(11). 1854–1865. 7 indexed citations

5.

Wei, Xinzhu, Andrea Ganna, Alexander Gusev, et al.. (2023). The lingering effects of Neanderthal introgression on human complex traits. eLife. 12. 13 indexed citations

6.

Molloy, Erin K., Arun Durvasula, & Sriram Sankararaman. (2021). Advancing admixture graph estimation via maximum likelihood network orientation. Bioinformatics. 37(Supplement_1). i142–i150. 20 indexed citations

7.

Boocock, James, Meru J. Sadhu, Arun Durvasula, Joshua S. Bloom, & Leonid Kruglyak. (2021). Ancient balancing selection maintains incompatible versions of the galactose pathway in yeast. Science. 371(6527). 415–419. 26 indexed citations

8.

Durvasula, Arun & Kirk E. Lohmueller. (2021). Negative selection on complex traits limits phenotype prediction accuracy between populations. The American Journal of Human Genetics. 108(4). 620–631. 28 indexed citations

9.

Durvasula, Arun & Sriram Sankararaman. (2020). Recovering signals of ghost archaic introgression in African populations. Science Advances. 6(7). eaax5097–eaax5097. 88 indexed citations

10.

Boocock, James & Arun Durvasula. (2020). theboocock/gal_bal: submission. Zenodo (CERN European Organization for Nuclear Research). 1 indexed citations

11.

Durvasula, Arun & Sriram Sankararaman. (2019). A statistical model for reference-free inference of archaic local ancestry. PLoS Genetics. 15(5). e1008175–e1008175. 26 indexed citations

12.

Schumer, Molly, Chenling Xu, Daniel L. Powell, et al.. (2018). Natural selection interacts with recombination to shape the evolution of hybrid genomes. Science. 360(6389). 656–660. 256 indexed citations breakdown →

13.

Huber, Christian D., Arun Durvasula, Angela M. Hancock, & Kirk E. Lohmueller. (2018). Gene expression drives the evolution of dominance. Nature Communications. 9(1). 2750–2750. 69 indexed citations

14.

Schweizer, Rena M., Arun Durvasula, Joel Smith, et al.. (2018). Natural Selection and Origin of a Melanistic Allele in North American Gray Wolves. Molecular Biology and Evolution. 35(5). 1190–1209. 37 indexed citations

15.

Durvasula, Arun, Andrea Fulgione, Rafał M. Gutaker, et al.. (2017). African genomes illuminate the early history and transition to selfing in Arabidopsis thaliana. Proceedings of the National Academy of Sciences. 114(20). 5213–5218. 130 indexed citations

16.

Beissinger, Timothy, Li Wang, Kate Crosby, et al.. (2016). Recent demography drives changes in linked selection across the maize genome. Nature Plants. 2(7). 16084–16084. 72 indexed citations

17.

Durvasula, Arun, Paul Hoffman, Tyler V. Kent, et al.. (2016). angsd‐wrapper: utilities for analysing next‐generation sequencing data. Molecular Ecology Resources. 16(6). 1449–1454. 12 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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