Nicholas Eriksson

12.1k total citations
25 papers, 2.4k citations indexed

About

Nicholas Eriksson is a scholar working on Genetics, Molecular Biology and Artificial Intelligence. According to data from OpenAlex, Nicholas Eriksson has authored 25 papers receiving a total of 2.4k indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Genetics, 8 papers in Molecular Biology and 3 papers in Artificial Intelligence. Recurrent topics in Nicholas Eriksson's work include Genetic Associations and Epidemiology (5 papers), BRCA gene mutations in cancer (3 papers) and Bayesian Modeling and Causal Inference (2 papers). Nicholas Eriksson is often cited by papers focused on Genetic Associations and Epidemiology (5 papers), BRCA gene mutations in cancer (3 papers) and Bayesian Modeling and Causal Inference (2 papers). Nicholas Eriksson collaborates with scholars based in United States, Switzerland and United Kingdom. Nicholas Eriksson's co-authors include David A. Hinds, Amy K. Kiefer, Joyce Y. Tung, Joanna L. Mountain, Uta Francke, Niko Beerenwinkel, Joyce Y. Tung, Osvaldo Zagordi, Arnab Bhattacharya and Chao Tian and has published in prestigious journals such as Nature Communications, Nature Genetics and Blood.

In The Last Decade

Nicholas Eriksson

25 papers receiving 2.3k citations

Peers

Nicholas Eriksson

GENET

EPIDE

PHYSI

DERMA

Jennifer Gordon United States

Xiangyin Kong China

Sarah Ennis United Kingdom

John V. Pearson Australia

Matt W. Wright United Kingdom

Eric M. Sobel United States

Bertil Lindblom Sweden

Noam Shomron Israel

Jean‐François Zagury France

Hailiang Mei Netherlands

Jennifer Gordon United States

Nicholas Eriksson

477 ×0.7

GENET

1.7k ×2.8

574 ×1.8

EPIDE

243 ×1.1

PHYSI

171 ×0.9

DERMA

Citations per year, relative to Nicholas Eriksson Nicholas Eriksson (= 1×) peers Jennifer Gordon

Countries citing papers authored by Nicholas Eriksson

Since Specialization

Citations

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

Fields of papers citing papers by Nicholas Eriksson

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Nicholas Eriksson

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

All Works

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20 of 20 papers shown

Tian, Chao, Bethann S. Hromatka, Amy K. Kiefer, et al.. (2017). Genome-wide association and HLA region fine-mapping studies identify susceptibility loci for multiple common infections. Nature Communications. 8(1). 599–599. 212 indexed citations

Hinds, David A., Kimberly E. Barnholt, Ruben A. Mesa, et al.. (2016). Germ line variants predispose to both JAK2 V617F clonal hematopoiesis and myeloproliferative neoplasms. Blood. 128(8). 1121–1128. 171 indexed citations

Hu, Youna, et al.. (2016). GWAS of 89,283 individuals identifies genetic variants associated with self-reporting of being a morning person. Nature Communications. 7(1). 10448–10448. 215 indexed citations

Hromatka, Bethann S., et al.. (2015). Genetic variants associated with motion sickness point to roles for inner ear development, neurological processes and glucose homeostasis. Human Molecular Genetics. 24(9). 2700–2708. 63 indexed citations

Chang, Anne Lynn S., Inbar Raber, Jin Xu, et al.. (2015). Assessment of the Genetic Basis of Rosacea by Genome-Wide Association Study. Journal of Investigative Dermatology. 135(6). 1548–1555. 123 indexed citations

Durand, Éric, Nicholas Eriksson, & Cory Y. McLean. (2014). Reducing Pervasive False-Positive Identical-by-Descent Segments Detected by Large-Scale Pedigree Analysis. Molecular Biology and Evolution. 31(8). 2212–2222. 30 indexed citations

Francke, Uta, et al.. (2013). Dealing with the unexpected: consumer responses to direct-access BRCA mutation testing. PeerJ. 1. e8–e8. 57 indexed citations

Hinds, David A., George McMahon, Amy K. Kiefer, et al.. (2013). A genome-wide association meta-analysis of self-reported allergy identifies shared and allergy-specific susceptibility loci. Nature Genetics. 45(8). 907–911. 156 indexed citations

Eriksson, Nicholas, Joyce Y. Tung, Amy K. Kiefer, et al.. (2012). Novel Associations for Hypothyroidism Include Known Autoimmune Risk Loci. PLoS ONE. 7(4). e34442–e34442. 93 indexed citations

10.

Eriksson, Nicholas, Amy K. Kiefer, Joanna L. Mountain, et al.. (2012). Genetic variants associated with breast size also influence breast cancer risk. BMC Medical Genetics. 13(1). 53–53. 55 indexed citations

11.

Hinds, David A., et al.. (2012). Comparison of Family History and SNPs for Predicting Risk of Complex Disease. PLoS Genetics. 8(10). e1002973–e1002973. 82 indexed citations

12.

Barnholt, Kimberly E., David A. Hinds, Amy K. Kiefer, et al.. (2012). Estimation of JAK2 V617F Prevalence by Detection of the Mutation in Saliva Samples From Online MPN and General Population Cohorts. Blood. 120(21). 1737–1737. 3 indexed citations

13.

Malaspinas, Anna‐Sapfo, Nicholas Eriksson, & Peter Huggins. (2011). Parametric Analysis of Alignment and Phylogenetic Uncertainty. Bulletin of Mathematical Biology. 73(4). 795–810. 1 indexed citations

14.

Tung, Joyce Y., David A. Hinds, Amy K. Kiefer, et al.. (2011). Efficient Replication of over 180 Genetic Associations with Self-Reported Medical Data. PLoS ONE. 6(8). e23473–e23473. 81 indexed citations

15.

Zagordi, Osvaldo, Arnab Bhattacharya, Nicholas Eriksson, & Niko Beerenwinkel. (2011). ShoRAH: estimating the genetic diversity of a mixed sample from next-generation sequencing data. BMC Bioinformatics. 12(1). 119–119. 188 indexed citations

16.

Eriksson, Nicholas, J. Michael Macpherson, Joyce Y. Tung, et al.. (2010). Web-Based, Participant-Driven Studies Yield Novel Genetic Associations for Common Traits. PLoS Genetics. 6(6). e1000993–e1000993. 302 indexed citations

17.

Beerenwinkel, Niko, Nicholas Eriksson, & Bernd Sturmfels. (2006). Evolution on distributive lattices. Journal of Theoretical Biology. 242(2). 409–420. 27 indexed citations

18.

Pachter, Lior, Radu Mihaescu, Michael Joswig, et al.. (2005). Algebraic Statistics for Computational Biology. Cambridge University Press eBooks. 245 indexed citations

19.

Eriksson, Nicholas, Stephen E. Fienberg, Alessandro Rinaldo, & Seth Sullivant. (2005). Polyhedral conditions for the nonexistence of the MLE for hierarchical log-linear models. Journal of Symbolic Computation. 41(2). 222–233. 32 indexed citations

20.

Diaconis, Persi & Nicholas Eriksson. (2005). Markov bases for noncommutative Fourier analysis of ranked data. Journal of Symbolic Computation. 41(2). 182–195. 10 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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