Gary Hausman

132 papers receiving 4.3k citations

Gary Hausman's Hit Papers

The biology of white adipocyte proliferation 2001 · 516 citations
5160+8+16Years since publication100200300400500

Peers

Gary Hausman
Comparison fields: 5 of 127
  • Physiology 2.2k
  • Genetics 480
  • Endocrine and Autonomic Systems 304
  • Epidemiology 1.4k
  • Animal Science and Zoology 352
Replace Cynthia M. Smas with:
Cynthia M. Smas United States
Danièle Lacasa France
Gary J. Hausman United States
Stéphane Gesta United States
Tim J. Schulz Germany
Yves Giudicelli France
Jae Myoung Suh South Korea
William P. Cawthorn United Kingdom
Tian Lian Huang United States
James C. Lo United States
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Citations per field
00.5×3.9×
Cynthia M. Smas · 1×
Citations per year

Countries citing papers authored by Gary Hausman

Since Specialization
Citations

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

Fields of papers citing papers by Gary Hausman

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Gary Hausman, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Gary Hausman Line = papers co-authored together Gary Hausman links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 136 papers — load more, or switch the sort, to bring in the rest.

#Work
1
The biology of white adipocyte proliferation
Hit paper breakdown →
2001516
2 2004323
3 2008282
4 2010238
5 2009172
6 2007118
7 201187
8 198179
9 200878
10 200476
11 199876
12 197876
13 199873
14 201371
15 198068
16 200459
17 200458
18 200653
19 198653
20 199347

About Gary Hausman

Gary Hausman is a scholar working on Physiology, Epidemiology, Molecular Biology, Pediatrics, Perinatology and Child Health and Cardiology and Cardiovascular Medicine, having authored 136 papers that have together received 4.4k indexed citations. Recurring topics across this work include Adipose Tissue and Metabolism (85 papers), Adipokines, Inflammation, and Metabolic Diseases (54 papers), Birth, Development, and Health (26 papers), Growth Hormone and Insulin-like Growth Factors (17 papers), Cardiovascular Disease and Adiposity (17 papers), Fatty Acid Research and Health (10 papers), Metabolism, Diabetes, and Cancer (7 papers) and Peroxisome Proliferator-Activated Receptors (7 papers). The work is most often cited by research in Physiology (2.2k citations), Genetics (480 citations), Endocrine and Autonomic Systems (304 citations), Epidemiology (1.4k citations) and Animal Science and Zoology (352 citations). Gary Hausman has collaborated with scholars based in United States, Canada and China. Frequent co-authors include Roy J. Martin, R.L. Richardson, Dorothy B. Hausman, Sylvia P. Poulos, Michael V. Dodson, Mario DiGirolamo, Timothy J. Bartness, Melinda E. Fernyhough, Jeremy Wright and D. R. Campion. Their work appears in journals such as Journal of Animal Science, Cells Tissues Organs, Experimental Biology and Medicine, Biochemical and Biophysical Research Communications and Domestic Animal Endocrinology.

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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