Alexander Gusev

24.0k total citations · 3 hit papers
91 papers, 5.9k citations indexed

About

Alexander Gusev is a scholar working on Genetics, Molecular Biology and Cancer Research. According to data from OpenAlex, Alexander Gusev has authored 91 papers receiving a total of 5.9k indexed citations (citations by other indexed papers that have themselves been cited), including 50 papers in Genetics, 34 papers in Molecular Biology and 21 papers in Cancer Research. Recurrent topics in Alexander Gusev's work include Genetic Associations and Epidemiology (43 papers), Genetic Mapping and Diversity in Plants and Animals (18 papers) and Cancer Genomics and Diagnostics (18 papers). Alexander Gusev is often cited by papers focused on Genetic Associations and Epidemiology (43 papers), Genetic Mapping and Diversity in Plants and Animals (18 papers) and Cancer Genomics and Diagnostics (18 papers). Alexander Gusev collaborates with scholars based in United States, United Kingdom and Sweden. Alexander Gusev's co-authors include Alkes L. Price, Hilary K. Finucane, Benjamin M. Neale, Po‐Ru Loh, Brendan Bulik‐Sullivan, Mark J. Daly, Laramie E. Duncan, Elise Robinson, Verneri Anttila and Felix R. Day and has published in prestigious journals such as Science, Cell and Proceedings of the National Academy of Sciences.

In The Last Decade

Alexander Gusev

84 papers receiving 5.9k citations

Hit Papers

An atlas of genetic correlations across human diseases an... 2015 2026 2018 2022 2015 2018 2024 500 1000 1.5k 2.0k

Peers

Alexander Gusev
Holly K. Tabor United States
Brendan Blumenstiel United States
Laurent Gil United Kingdom
Matthew DeFelice United States
Jin Yu United States
Joseph Glessner United States
Giulio Genovese United States
Alexander Gusev
Citations per year, relative to Alexander Gusev Alexander Gusev (= 1×) peers Daníel F. Guðbjartsson

Countries citing papers authored by Alexander Gusev

Since Specialization
Citations

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

Fields of papers citing papers by Alexander Gusev

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Alexander Gusev

This figure shows the co-authorship network connecting the top 25 collaborators of Alexander Gusev. A scholar is included among the top collaborators of Alexander Gusev 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 Alexander Gusev. Alexander Gusev 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.
Groha, Stefan, David King, Robert Tell, et al.. (2024). A comprehensive analysis of clinical and polygenic germline influences on somatic mutational burden. The American Journal of Human Genetics. 111(2). 242–258. 2 indexed citations
2.
Munro, Daniel, et al.. (2024). Multimodal analysis of RNA sequencing data powers discovery of complex trait genetics. Nature Communications. 15(1). 10387–10387.
3.
Tang, Cerise, Michele Waters, Chris Fong, et al.. (2024). Obesity-dependent selection of driver mutations in cancer. Nature Genetics. 56(11). 2318–2321. 6 indexed citations
4.
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
5.
Liu, Yuxi, Alexander Gusev, & Peter Kraft. (2023). Germline Cancer Gene Expression Quantitative Trait Loci Are Associated with Local and Global Tumor Mutations. Cancer Research. 83(8). 1191–1202. 6 indexed citations
6.
Kehl, Kenneth L., Hajime Uno, Alexander Gusev, et al.. (2023). Elucidating Analytic Bias Due to Informative Cohort Entry in Cancer Clinico-genomic Datasets. Cancer Epidemiology Biomarkers & Prevention. 32(3). 344–352. 1 indexed citations
7.
Vasavda, Chirag, Guihong Wan, Mindy D Szeto, et al.. (2023). A Polygenic Risk Score for Predicting Racial and Genetic Susceptibility to Prurigo Nodularis. Journal of Investigative Dermatology. 143(12). 2416–2426.e1. 16 indexed citations
8.
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
9.
Camp, Sabrina Y., Seunghun Han, Erin L. Young, et al.. (2022). Germline predisposition to pediatric Ewing sarcoma is characterized by inherited pathogenic variants in DNA damage repair genes. The American Journal of Human Genetics. 109(6). 1026–1037. 27 indexed citations
10.
Le, Thomas K., Isabelle Brown, Rebecca Goldberg, et al.. (2022). Cutaneous Toxicities Associated with Immune Checkpoint Inhibitors: An Observational, Pharmacovigilance Study. Journal of Investigative Dermatology. 142(11). 2896–2908.e4. 15 indexed citations
11.
Munro, Daniel, Tengfei Wang, Apurva S. Chitre, et al.. (2022). The regulatory landscape of multiple brain regions in outbred heterogeneous stock rats. Nucleic Acids Research. 50(19). 10882–10895. 12 indexed citations
12.
Gomy, Israel, Alexander Gusev, Bruce E. Johnson, et al.. (2021). Germline Testing Data Validate Inferences of Mutational Status for Variants Detected From Tumor-Only Sequencing. JCO Precision Oncology. 5(5). 1749–1757. 9 indexed citations
13.
Kehl, Kenneth L., Stefan Groha, Eva M. Lepisto, et al.. (2021). Clinical Inflection Point Detection on the Basis of EHR Data to Identify Clinical Trial–Ready Patients With Cancer. JCO Clinical Cancer Informatics. 5(5). 622–630. 12 indexed citations
14.
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
15.
Carrot‐Zhang, Jian, Giovanny Soca‐Chafre, Nick Patterson, et al.. (2020). Genetic Ancestry Contributes to Somatic Mutations in Lung Cancers from Admixed Latin American Populations. Cancer Discovery. 11(3). 591–598. 71 indexed citations
16.
Corona, Rosario I., Ji-Heui Seo, Xianzhi Lin, et al.. (2020). Non-coding somatic mutations converge on the PAX8 pathway in ovarian cancer. Nature Communications. 11(1). 2020–2020. 45 indexed citations
17.
Geijn, Bryce van de, Hilary K. Finucane, Steven Gazal, et al.. (2019). Annotations capturing cell type-specific TF binding explain a large fraction of disease heritability. Human Molecular Genetics. 29(7). 1057–1067. 9 indexed citations
18.
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
19.
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 →
20.
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

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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