Gene Hsiao

849 total citations
9 papers, 710 citations indexed

About

Gene Hsiao is a scholar working on Molecular Biology, Epidemiology and Cancer Research. According to data from OpenAlex, Gene Hsiao has authored 9 papers receiving a total of 710 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Molecular Biology, 4 papers in Epidemiology and 4 papers in Cancer Research. Recurrent topics in Gene Hsiao's work include Adipokines, Inflammation, and Metabolic Diseases (3 papers), Peroxisome Proliferator-Activated Receptors (3 papers) and Adipose Tissue and Metabolism (3 papers). Gene Hsiao is often cited by papers focused on Adipokines, Inflammation, and Metabolic Diseases (3 papers), Peroxisome Proliferator-Activated Receptors (3 papers) and Adipose Tissue and Metabolism (3 papers). Gene Hsiao collaborates with scholars based in United States, France and United Kingdom. Gene Hsiao's co-authors include Shankar Subramaniam, Dorothy D. Sears, Jachelle M. Ofrecio, Jia Yu, Joab Chapman, C. H. Courtney, Albert Hsiao, Robin D. Lester, Annette R. Atkins and Michael C. Nelson and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nature Immunology and PLoS ONE.

In The Last Decade

Gene Hsiao

9 papers receiving 697 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Gene Hsiao United States	7	415	280	211	102	89	9	710
Haritz Moreno Spain	7	214 0.5×	192 0.7×	158 0.7×	190 1.9×	60 0.7×	9	660
Sivakama S. Bharathi United States	14	467 1.1×	251 0.9×	218 1.0×	37 0.4×	143 1.6×	26	854
Dwight D. Dimaculangan United States	5	661 1.6×	340 1.2×	187 0.9×	45 0.4×	102 1.1×	9	846
Wanli Cheng United States	6	425 1.0×	199 0.7×	117 0.6×	118 1.2×	92 1.0×	9	734
Ana Ortega-Molina Spain	11	629 1.5×	290 1.0×	111 0.5×	81 0.8×	164 1.8×	14	937
Karthigayan Shanmugasundaram United States	11	401 1.0×	147 0.5×	87 0.4×	115 1.1×	186 2.1×	22	715
Kamal D. Mehta United States	18	607 1.5×	165 0.6×	141 0.7×	107 1.0×	117 1.3×	45	963
Anne Loft Denmark	17	766 1.8×	471 1.7×	349 1.7×	113 1.1×	144 1.6×	27	1.3k
Sebastian C. Hasenfuss Spain	9	415 1.0×	526 1.9×	286 1.4×	91 0.9×	128 1.4×	10	1.0k

Countries citing papers authored by Gene Hsiao

Since Specialization

Citations

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

Fields of papers citing papers by Gene Hsiao

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Gene Hsiao

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

All Works

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9 of 9 papers shown

Subramaniam, Shankar & Gene Hsiao. (2012). Gene-expression measurement: variance-modeling considerations for robust data analysis. Nature Immunology. 13(3). 199–203. 18 indexed citations

Hsiao, Gene, Justin Chapman, Jachelle M. Ofrecio, et al.. (2010). Multi-tissue, selective PPARγ modulation of insulin sensitivity and metabolic pathways in obese rats. American Journal of Physiology-Endocrinology and Metabolism. 300(1). E164–E174. 68 indexed citations

Markiewski, Maciej M., David A. Buchner, Haiyan Shao, et al.. (2009). Diet-induced hepatocellular carcinoma in genetically predisposed mice. Human Molecular Genetics. 18(16). 2975–2988. 122 indexed citations

Liu, Tiffany, Valérie Montel, Gene Hsiao, et al.. (2009). Chemoattractant Signaling between Tumor Cells and Macrophages Regulates Cancer Cell Migration, Metastasis and Neovascularization. PLoS ONE. 4(8). e6713–e6713. 114 indexed citations

Sears, Dorothy D., Gene Hsiao, Albert Hsiao, et al.. (2009). Mechanisms of human insulin resistance and thiazolidinedione-mediated insulin sensitization. Proceedings of the National Academy of Sciences. 106(44). 18745–18750. 143 indexed citations

Buchner, David A., Maciej M. Markiewski, David DeSantis, et al.. (2009). Diet‐induced hepatocellular carcinoma in genetically‐predisposed mice. The FASEB Journal. 23(S1). 4 indexed citations

Sugii, Shigeki, Peter Olson, Dorothy D. Sears, et al.. (2009). PPARγ activation in adipocytes is sufficient for systemic insulin sensitization. Proceedings of the National Academy of Sciences. 106(52). 22504–22509. 222 indexed citations

Hsiao, Gene, et al.. (2008). Estrogen Deficiency-Induced Alterations of Vascular MMP-2, MT1-MMP, and TIMP-2 in Ovariectomized Rats. American Journal of Hypertension. 22(1). 27–34. 17 indexed citations

Hsiao, Gene, et al.. (2004). A middleware architecture to facilitate distributed programming. Future Generation Computer Systems. 22(1-2). 88–101. 2 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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