Itsik Pe’er

16.0k total citations · 3 hit papers
99 papers, 6.8k citations indexed

About

Itsik Pe’er is a scholar working on Genetics, Molecular Biology and Artificial Intelligence. According to data from OpenAlex, Itsik Pe’er has authored 99 papers receiving a total of 6.8k indexed citations (citations by other indexed papers that have themselves been cited), including 61 papers in Genetics, 42 papers in Molecular Biology and 11 papers in Artificial Intelligence. Recurrent topics in Itsik Pe’er's work include Genetic Associations and Epidemiology (38 papers), Genomics and Phylogenetic Studies (19 papers) and Genetic Mapping and Diversity in Plants and Animals (12 papers). Itsik Pe’er is often cited by papers focused on Genetic Associations and Epidemiology (38 papers), Genomics and Phylogenetic Studies (19 papers) and Genetic Mapping and Diversity in Plants and Animals (12 papers). Itsik Pe’er collaborates with scholars based in United States, Israel and Switzerland. Itsik Pe’er's co-authors include Mark J. Daly, David Altshuler, Roman Yelensky, Paul I. W. de Bakker, Stacey Gabriel, Snehit Prabhu, Pier Francesco Palamara, Tyler Joseph, Ron Shamir and Ariel Darvasi and has published in prestigious journals such as Science, Cell and Proceedings of the National Academy of Sciences.

In The Last Decade

Itsik Pe’er

96 papers receiving 6.7k citations

Hit Papers

Efficiency and power in genetic association studies 2005 2026 2012 2019 2005 2009 2019 400 800 1.2k

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Itsik Pe’er United States 35 3.1k 2.7k 501 485 410 99 6.8k
Matthew R. Nelson United States 38 2.6k 0.9× 2.7k 1.0× 773 1.5× 608 1.3× 450 1.1× 84 7.4k
Nicole Soranzo United Kingdom 35 2.3k 0.7× 2.5k 0.9× 523 1.0× 283 0.6× 288 0.7× 78 5.8k
John C. Whittaker United Kingdom 48 3.3k 1.1× 2.3k 0.9× 214 0.4× 525 1.1× 613 1.5× 220 8.4k
Antti Sajantila Finland 46 3.8k 1.2× 2.6k 1.0× 734 1.5× 242 0.5× 208 0.5× 198 7.2k
Andrew D. Johnson United States 39 1.9k 0.6× 2.8k 1.0× 202 0.4× 456 0.9× 411 1.0× 127 6.6k
William McLaren United Kingdom 13 2.9k 0.9× 3.2k 1.2× 439 0.9× 410 0.8× 226 0.6× 16 6.4k
Eric R. Gamazon United States 38 2.7k 0.9× 3.7k 1.4× 359 0.7× 369 0.8× 318 0.8× 162 6.6k
Kathryn L. Lunetta United States 44 2.3k 0.7× 2.6k 1.0× 183 0.4× 311 0.6× 395 1.0× 198 7.0k
Sarah Hunt United Kingdom 28 4.1k 1.3× 3.9k 1.4× 380 0.8× 678 1.4× 365 0.9× 55 8.2k
Mark A. DePristo United States 15 4.0k 1.3× 4.5k 1.7× 138 0.3× 525 1.1× 434 1.1× 16 8.2k

Countries citing papers authored by Itsik Pe’er

Since Specialization
Citations

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

Fields of papers citing papers by Itsik Pe’er

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Itsik Pe’er. 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 Itsik Pe’er. The network helps show where Itsik Pe’er may publish in the future.

Co-authorship network of co-authors of Itsik Pe’er

This figure shows the co-authorship network connecting the top 25 collaborators of Itsik Pe’er. A scholar is included among the top collaborators of Itsik Pe’er 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 Itsik Pe’er. Itsik Pe’er 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.
Jiménez-Sánchez, Alejandro, Sitara Persad, Akimasa Hayashi, et al.. (2025). Transcriptomic Plasticity is a Hallmark of Metastatic Pancreatic Cancer. Cancer Research.
2.
Pe’er, Itsik, et al.. (2025). Distributional bias compromises leave-one-out cross-validation. Science Advances. 11(48). eadx6976–eadx6976. 1 indexed citations
3.
Kav, Aya Brown, Heekuk Park, Jana Biermann, et al.. (2025). Processing-bias correction with DEBIAS-M improves cross-study generalization of microbiome-based prediction models. Nature Microbiology. 10(4). 897–911. 2 indexed citations
4.
Saxena, A., Qi Yan, Ronald J. Wapner, et al.. (2024). Diving into CDC pregnancy data in the United States: longitudinal study and interactive application. JAMIA Open. 7(1). ooae024–ooae024. 1 indexed citations
5.
Yan, Qi, David M. Haas, Ronald J. Wapner, et al.. (2024). A comprehensive and bias-free machine learning approach for risk prediction of preeclampsia with severe features in a nulliparous study cohort. BMC Pregnancy and Childbirth. 24(1). 853–853. 1 indexed citations
6.
Pe’er, Itsik, et al.. (2020). SICaRiO: short indel call filtering with boosting. Briefings in Bioinformatics. 22(4). 1 indexed citations
7.
Joseph, Tyler, Liat Shenhav, João B. Xavier, Eran Halperin, & Itsik Pe’er. (2020). Compositional Lotka-Volterra describes microbial dynamics in the simplex. PLoS Computational Biology. 16(5). e1007917–e1007917. 40 indexed citations
8.
Pe’er, Itsik, et al.. (2019). Smoothing Nonlinear Variational Objectives with Sequential Monte Carlo. International Conference on Learning Representations. 1 indexed citations
9.
Lencz, Todd, Jin Yu, Cameron D. Palmer, et al.. (2018). High-depth whole genome sequencing of an Ashkenazi Jewish reference panel: enhancing sensitivity, accuracy, and imputation. Human Genetics. 137(4). 343–355. 15 indexed citations
10.
Agarwal, Ipsita, et al.. (2017). 2-Way k -Means as a Model for Microbiome Samples. Journal of Healthcare Engineering. 2017. 1–7. 1 indexed citations
11.
Palmer, Cameron D. & Itsik Pe’er. (2017). Statistical correction of the Winner’s Curse explains replication variability in quantitative trait genome-wide association studies. PLoS Genetics. 13(7). e1006916–e1006916. 65 indexed citations
12.
Campbell, Christopher, Pier Francesco Palamara, Maya Dubrovsky, et al.. (2012). North African Jewish and non-Jewish populations form distinctive, orthogonal clusters. Proceedings of the National Academy of Sciences. 109(34). 13865–13870. 43 indexed citations
13.
Prabhu, Snehit & Itsik Pe’er. (2012). Ultrafast genome-wide scan for SNP–SNP interactions in common complex disease. Genome Research. 22(11). 2230–2240. 83 indexed citations
14.
Setty, Manu, Alexander Gusev, & Itsik Pe’er. (2011). HLA Type Inference via Haplotypes Identical by Descent. Journal of Computational Biology. 18(3). 483–493. 13 indexed citations
15.
Shen, Yufeng, et al.. (2011). A Hidden Markov Model for Copy Number Variant prediction from whole genome resequencing data. BMC Bioinformatics. 12(S6). S4–S4. 11 indexed citations
16.
Kenny, Eimear E., Alexander Gusev, Jennifer K. Lowe, et al.. (2010). Increased power of mixed models facilitates association mapping of 10 loci for metabolic traits in an isolated population. Human Molecular Genetics. 20(4). 827–839. 19 indexed citations
17.
Gusev, Alexander, Jennifer K. Lowe, Markus Stoffel, et al.. (2008). Whole population, genome-wide mapping of hidden relatedness. Genome Research. 19(2). 318–326. 301 indexed citations
18.
Sarin, Sumeet, Snehit Prabhu, M O’Meara, Itsik Pe’er, & Oliver Hobert. (2008). Caenorhabditis elegans mutant allele identification by whole-genome sequencing. Nature Methods. 5(10). 865–867. 185 indexed citations
19.
Pe’er, Itsik & Ron Shamir. (1998). The median problems for breakpoints are NP-complete. Electronic colloquium on computational complexity. 5. 66 indexed citations
20.
Pe’er, Itsik & Ron Shamir. (1997). Satisfiability problems on intervals and unit intervals. Theoretical Computer Science. 175(2). 349–372. 11 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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