Jason E. Aten

735 total citations
8 papers, 521 citations indexed

About

Jason E. Aten is a scholar working on Molecular Biology, Genetics and Artificial Intelligence. According to data from OpenAlex, Jason E. Aten has authored 8 papers receiving a total of 521 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Molecular Biology, 3 papers in Genetics and 1 paper in Artificial Intelligence. Recurrent topics in Jason E. Aten's work include Bioinformatics and Genomic Networks (7 papers), Gene Regulatory Network Analysis (2 papers) and Genetic Mapping and Diversity in Plants and Animals (2 papers). Jason E. Aten is often cited by papers focused on Bioinformatics and Genomic Networks (7 papers), Gene Regulatory Network Analysis (2 papers) and Genetic Mapping and Diversity in Plants and Animals (2 papers). Jason E. Aten collaborates with scholars based in United States. Jason E. Aten's co-authors include Steve Horvath, Aldons J. Lusis, Tova F Fuller, Anatole Ghazalpour, Thomas A. Drake, Eric E. Schadt, Atila van Nas, Sudheer Doss, Charles R. Farber and Peter Kraft and has published in prestigious journals such as The American Journal of Human Genetics, Journal of Lipid Research and Journal of Bone and Mineral Research.

In The Last Decade

Jason E. Aten

7 papers receiving 511 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Jason E. Aten United States	7	352	186	57	49	40	8	521
James A. Wingrove United States	12	472 1.3×	241 1.3×	68 1.2×	108 2.2×	125 3.1×	19	879
Marek Tutaj United States	13	416 1.2×	148 0.8×	34 0.6×	29 0.6×	55 1.4×	26	584
Cyrus Afrasiabi United States	7	395 1.1×	137 0.7×	31 0.5×	102 2.1×	96 2.4×	11	599
Laurel A Bastone United States	5	325 0.9×	218 1.2×	28 0.5×	32 0.7×	71 1.8×	6	556
Jennifer E. Embury United States	11	275 0.8×	179 1.0×	30 0.5×	43 0.9×	23 0.6×	16	552
Sampath K. Loganathan Canada	12	278 0.8×	82 0.4×	64 1.1×	44 0.9×	48 1.2×	21	580
Alexey V. Deykin Russia	15	376 1.1×	141 0.8×	78 1.4×	52 1.1×	18 0.5×	61	668
Arbansjit K. Sandhu United States	9	238 0.7×	92 0.5×	85 1.5×	49 1.0×	23 0.6×	13	460
Simon Brent United Kingdom	8	328 0.9×	174 0.9×	17 0.3×	26 0.5×	62 1.6×	9	541

Countries citing papers authored by Jason E. Aten

Since Specialization

Citations

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

Fields of papers citing papers by Jason E. Aten

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jason E. Aten. 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 Jason E. Aten. The network helps show where Jason E. Aten may publish in the future.

Co-authorship network of co-authors of Jason E. Aten

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

All Works

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8 of 8 papers shown

MacLennan, Nicole K., Jun Dong, Jason E. Aten, et al.. (2009). Weighted gene co-expression network analysis identifies biomarkers in glycerol kinase deficient mice. Molecular Genetics and Metabolism. 98(1-2). 203–214. 27 indexed citations

Farber, Charles R., Jason E. Aten, Emily Farber, et al.. (2009). Genetic dissection of a major mouse obesity QTL (Carfhg2): integration of gene expression and causality modeling. Physiological Genomics. 37(3). 294–302. 21 indexed citations

Aten, Jason E., Tova F Fuller, Aldons J. Lusis, & Steve Horvath. (2008). Using genetic markers to orient the edges in quantitative trait networks: The NEO software. BMC Systems Biology. 2(1). 34–34. 97 indexed citations

Farber, Charles R., Atila van Nas, Anatole Ghazalpour, et al.. (2008). An Integrative Genetics Approach to Identify Candidate Genes Regulating BMD: Combining Linkage, Gene Expression, and Association. Journal of Bone and Mineral Research. 24(1). 105–116. 41 indexed citations

Fuller, Tova F, Anatole Ghazalpour, Jason E. Aten, et al.. (2007). Weighted gene coexpression network analysis strategies applied to mouse weight. Mammalian Genome. 18(6-7). 463–472. 279 indexed citations

Aten, Jason E.. (2006). Learning Genetic and Gene Bayesian Networks with Hidden Variables: Bilayer Verification Algorithm.. 483–489. 1 indexed citations

Ghazalpour, Anatole, Sudheer Doss, Xia Yang, et al.. (2004). Thematic review series: The Pathogenesis of Atherosclerosis. Toward a biological network for atherosclerosis. Journal of Lipid Research. 45(10). 1793–1805. 36 indexed citations

Kraft, Peter, Eric E. Schadt, Jason E. Aten, & Steve Horvath. (2003). A Family-Based Test for Correlation between Gene Expression and Trait Values. The American Journal of Human Genetics. 72(5). 1323–1330. 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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