Jeff E. Cobb

1.8k citations
19 papers · 1.2k · h-index 12

Impact in

    • Eicosanoids and Hypertension Pharmacology
  • Physiology top 10%
    • Adipose Tissue and Metabolism
    • Diet and metabolism studies

Papers in

    • Metabolomics and Mass Spectrometry Studies 6
    • Peroxisome Proliferator-Activated Receptors 4
    • Metabolism, Diabetes, and Cancer 3
    • Diet and metabolism studies 4
    • Adipose Tissue and Metabolism 3

Jeff E. Cobb

18 papers receiving 1.2k citations

Peers

Jeff E. Cobb
Comparison fields: 5 of 95
  • Biochemistry 105
  • Physiology 336
  • Molecular Biology 877
  • Endocrinology, Diabetes and Metabolism 152
  • Pharmacology 147
Replace Teresa Tejerina with:
Teresa Tejerina Spain
Reeba K. Vikramadithyan United States
Chhabi Biswas United States
Toru Nishinaka Japan
Adriana Zuccollo Argentina
Yue Du China
Olof Breuer Sweden
Christopher Ho United States
Gaia Robino Italy
Susanne Zadelaar Netherlands
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Citations per field
00.5×1.7×
Teresa Tejerina · 1×
Citations per year

Countries citing papers authored by Jeff E. Cobb

Since Specialization
Citations

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

Fields of papers citing papers by Jeff E. Cobb

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Jeff E. Cobb, 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 Jeff E. Cobb Line = papers co-authored together Jeff E. Cobb links everyone, so they are left out of the graph.

All Works

19 of 19 papers shown
#Work
1 2002491
2 201799
3 201697
4 199896
5 199868
6 201364
7 201560
8 199758
9 201744
10 201740
11 201434
12 201526
13 199110
14 19875
15 19992
16 20041
17 19831
18 20041
19 20030

About Jeff E. Cobb

Jeff E. Cobb is a scholar working on Molecular Biology, Physiology, Organic Chemistry, Epidemiology and Endocrinology, Diabetes and Metabolism, having authored 19 papers that have together received 1.2k indexed citations. Recurring topics across this work include Metabolomics and Mass Spectrometry Studies (6 papers), Liver Disease Diagnosis and Treatment (4 papers), Peroxisome Proliferator-Activated Receptors (4 papers), Diet and metabolism studies (4 papers), Metabolism, Diabetes, and Cancer (3 papers), Adipose Tissue and Metabolism (3 papers), Diabetes, Cardiovascular Risks, and Lipoproteins (2 papers) and Asymmetric Synthesis and Catalysis (2 papers). The work is most often cited by research in Biochemistry (105 citations), Physiology (336 citations), Molecular Biology (877 citations), Endocrinology, Diabetes and Metabolism (152 citations) and Pharmacology (147 citations). Jeff E. Cobb has collaborated with scholars based in United States, Italy and United Kingdom. Frequent co-authors include Ele Ferrannini, James M. Lenhard, Jon L. Collins, Emily A. Hull-Ryde, Derek J. Parks, Steven G. Blanchard, Kelli D. Plunket, Lisa M. Leesnitzer, Roderick G. Davis and Julie B. Stimmel. Their work appears in journals such as Journal of Diabetes Science and Technology, Tetrahedron, Journal of Medicinal Chemistry, The Journal of Clinical Endocrinology & Metabolism and Scientific Reports.

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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