Bogdan Paşaniuc

25.9k total citations · 6 hit papers
108 papers, 6.5k citations indexed

About

Bogdan Paşaniuc is a scholar working on Genetics, Molecular Biology and Cancer Research. According to data from OpenAlex, Bogdan Paşaniuc has authored 108 papers receiving a total of 6.5k indexed citations (citations by other indexed papers that have themselves been cited), including 91 papers in Genetics, 48 papers in Molecular Biology and 7 papers in Cancer Research. Recurrent topics in Bogdan Paşaniuc's work include Genetic Associations and Epidemiology (88 papers), Genetic Mapping and Diversity in Plants and Animals (46 papers) and Genetic and phenotypic traits in livestock (41 papers). Bogdan Paşaniuc is often cited by papers focused on Genetic Associations and Epidemiology (88 papers), Genetic Mapping and Diversity in Plants and Animals (46 papers) and Genetic and phenotypic traits in livestock (41 papers). Bogdan Paşaniuc collaborates with scholars based in United States, United Kingdom and Israel. Bogdan Paşaniuc's co-authors include Gleb Kichaev, Alkes L. Price, Huwenbo Shi, Nicholas Mancuso, Noah Zaitlen, Eleazar Eskin, Farhad Hormozdiari, Alexander Gusev, Sriram Sankararaman and Malika Freund and has published in prestigious journals such as Nature, Science and Cell.

In The Last Decade

Bogdan Paşaniuc

104 papers receiving 6.4k citations

Hit Papers

Opportunities and challenges for transcriptome-wide assoc... 2016 2026 2019 2022 2019 2018 2016 2018 2023 100 200 300 400 500
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. Opportunities and challenges for transcriptome-wide association studies
    2019 506 citations Michael Wainberg, Nasa Sinnott-Armstrong et al. Nature Genetics profile →
  2. Leveraging Polygenic Functional Enrichment to Improve GWAS Power
    2018 485 citations Gleb Kichaev, Steven Gazal et al. The American Journal of Human Genetics profile →
  3. Colocalization of GWAS and eQTL Signals Detects Target Genes
    2016 380 citations Farhad Hormozdiari, Sriram Sankararaman et al. The American Journal of Human Genetics profile →
  4. Transcriptome-wide association study of schizophrenia and chromatin activity yields mechanistic disease insights
    2018 293 citations Alexander Gusev, Nicholas Mancuso et al. Nature Genetics profile →
  5. Principles and methods for transferring polygenic risk scores across global populations
    2023 103 citations Linda Kachuri, Nilanjan Chatterjee et al. Nature Reviews Genetics profile →
  6. Polygenic scoring accuracy varies across the genetic ancestry continuum
    2023 90 citations Yi Ding, Kangcheng Hou et al. profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Bogdan Paşaniuc United States 39 4.4k 3.1k 502 337 314 108 6.5k
Heather Junkins United States 8 3.3k 0.8× 3.6k 1.2× 782 1.6× 436 1.3× 355 1.1× 10 6.2k
Jin Yu United States 12 3.0k 0.7× 3.0k 1.0× 748 1.5× 379 1.1× 240 0.8× 17 5.9k
Alexander Gusev United States 33 3.6k 0.8× 2.2k 0.7× 518 1.0× 315 0.9× 306 1.0× 91 5.9k
Joseph Glessner United States 39 3.4k 0.8× 2.2k 0.7× 623 1.2× 478 1.4× 254 0.8× 138 5.5k
Laurent Gil United Kingdom 7 3.0k 0.7× 3.1k 1.0× 1.0k 2.0× 422 1.3× 287 0.9× 7 6.1k
Olivier Delaneau Switzerland 23 4.2k 1.0× 2.6k 0.8× 632 1.3× 509 1.5× 586 1.9× 47 7.8k
Matthew DeFelice United States 5 2.4k 0.5× 2.0k 0.6× 504 1.0× 491 1.5× 403 1.3× 7 5.1k
Giulio Genovese United States 33 1.8k 0.4× 2.6k 0.8× 434 0.9× 526 1.6× 334 1.1× 67 6.8k
Abigail W. Bigham United States 27 3.6k 0.8× 2.6k 0.8× 1.0k 2.0× 321 1.0× 493 1.6× 61 6.2k
Brendan Blumenstiel United States 8 2.4k 0.6× 2.1k 0.7× 628 1.3× 505 1.5× 406 1.3× 12 5.4k

Countries citing papers authored by Bogdan Paşaniuc

Since Specialization
Citations

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

Fields of papers citing papers by Bogdan Paşaniuc

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Bogdan Paşaniuc

This figure shows the co-authorship network connecting the top 25 collaborators of Bogdan Paşaniuc. A scholar is included among the top collaborators of Bogdan Paşaniuc 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 Bogdan Paşaniuc. Bogdan Paşaniuc 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.
2.
Petter, Ella, Yi Ding, Kangcheng Hou, et al.. (2023). Genotype error due to low-coverage sequencing induces uncertainty in polygenic scoring. The American Journal of Human Genetics. 110(8). 1319–1329. 4 indexed citations
3.
Kachuri, Linda, Nilanjan Chatterjee, Jibril Hirbo, et al.. (2023). Principles and methods for transferring polygenic risk scores across global populations. Nature Reviews Genetics. 25(1). 8–25. 103 indexed citations breakdown →
4.
Bhattacharya, Arjun, Daniel Vo, Connor Jops, et al.. (2023). Isoform-level transcriptome-wide association uncovers genetic risk mechanisms for neuropsychiatric disorders in the human brain. Nature Genetics. 55(12). 2117–2128. 19 indexed citations
5.
Morova, Tunç, Yi Ding, Chia-Chi Flora Huang, et al.. (2022). Optimized high-throughput screening of non-coding variants identified from genome-wide association studies. Nucleic Acids Research. 51(3). e18–e18. 8 indexed citations
6.
Gazal, Steven, Omer Weissbrod, Farhad Hormozdiari, et al.. (2022). Combining SNP-to-gene linking strategies to identify disease genes and assess disease omnigenicity. Nature Genetics. 54(6). 827–836. 73 indexed citations
7.
Burch, Kathryn S., Kangcheng Hou, Yi Ding, et al.. (2022). Partitioning gene-level contributions to complex-trait heritability by allele frequency identifies disease-relevant genes. The American Journal of Human Genetics. 109(4). 692–709. 6 indexed citations
8.
Feng, Helian, Nicholas Mancuso, Alexander Gusev, et al.. (2021). Leveraging expression from multiple tissues using sparse canonical correlation analysis and aggregate tests improves the power of transcriptome-wide association studies. PLoS Genetics. 17(4). e1008973–e1008973. 41 indexed citations
9.
Majumdar, Arunabha, Claudia Giambartolomei, Na Cai, et al.. (2021). Leveraging eQTLs to identify individual-level tissue of interest for a complex trait. PLoS Computational Biology. 17(5). e1008915–e1008915. 3 indexed citations
10.
Majumdar, Arunabha, Kathryn S. Burch, Tanushree Haldar, et al.. (2020). A two-step approach to testing overall effect of gene–environment interaction for multiple phenotypes. Bioinformatics. 36(24). 5640–5648. 8 indexed citations
11.
Wu, Lang, Jifeng Wang, Qiuyin Cai, et al.. (2019). Identification of Novel Susceptibility Loci and Genes for Prostate Cancer Risk: A Transcriptome-Wide Association Study in Over 140,000 European Descendants. Cancer Research. 79(13). 3192–3204. 37 indexed citations
12.
Julienne, Hanna, Huwenbo Shi, Bogdan Paşaniuc, & Hugues Aschard. (2019). RAISS: robust and accurate imputation from summary statistics. Bioinformatics. 35(22). 4837–4839. 14 indexed citations
13.
Wainberg, Michael, Nasa Sinnott-Armstrong, Nicholas Mancuso, et al.. (2019). Opportunities and challenges for transcriptome-wide association studies. Nature Genetics. 51(4). 592–599. 506 indexed citations breakdown →
14.
Hou, Kangcheng, Kathryn S. Burch, Arunabha Majumdar, et al.. (2019). Accurate estimation of SNP-heritability from biobank-scale data irrespective of genetic architecture. Nature Genetics. 51(8). 1244–1251. 59 indexed citations
15.
Gusev, Alexander, Kate Lawrenson, Xianzhi Lin, et al.. (2019). A transcriptome-wide association study of high-grade serous epithelial ovarian cancer identifies new susceptibility genes and splice variants. Nature Genetics. 51(5). 815–823. 66 indexed citations
16.
Johnson, Ruth, Huwenbo Shi, Bogdan Paşaniuc, & Sriram Sankararaman. (2018). A unifying framework for joint trait analysis under a non-infinitesimal model. Bioinformatics. 34(13). i195–i201. 3 indexed citations
17.
Gusev, Alexander, Nicholas Mancuso, Hyejung Won, et al.. (2018). Transcriptome-wide association study of schizophrenia and chromatin activity yields mechanistic disease insights. Nature Genetics. 50(4). 538–548. 293 indexed citations breakdown →
18.
Kichaev, Gleb, Ruth Johnson, Eleazar Eskin, et al.. (2016). Improved methods for multi-trait fine mapping of pleiotropic risk loci. Bioinformatics. 33(2). 248–255. 76 indexed citations
19.
Yang, Wen-Yun, Alexander Platt, Charleston W. K. Chiang, et al.. (2014). Spatial Localization of Recent Ancestors for Admixed Individuals. G3 Genes Genomes Genetics. 4(12). 2505–2518. 12 indexed citations
20.
Paşaniuc, Bogdan & Noah Zaitlen. (2013). Using Extended Genealogy to Estimate Components of Heritability for 23 Quantitative and Dichotomous Traits. eScholarship (California Digital Library). 227 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.

Explore authors with similar magnitude of impact

Breakdown of academic impact, for papers by Heather Junkins Breakdown of academic impact, for papers by Jin Yu Breakdown of academic impact, for papers by Alexander Gusev Breakdown of academic impact, for papers by Joseph Glessner Breakdown of academic impact, for papers by Laurent Gil Breakdown of academic impact, for papers by Olivier Delaneau Breakdown of academic impact, for papers by Matthew DeFelice Breakdown of academic impact, for papers by Giulio Genovese Breakdown of academic impact, for papers by Abigail W. Bigham Breakdown of academic impact, for papers by Brendan Blumenstiel
Rankless by CCL
2026