Jeff E. Cobb

1.8k total citations
19 papers, 1.2k citations indexed

About

Jeff E. Cobb is a scholar working on Molecular Biology, Physiology and Organic Chemistry. According to data from OpenAlex, Jeff E. Cobb has authored 19 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Molecular Biology, 8 papers in Physiology and 5 papers in Organic Chemistry. Recurrent topics in Jeff E. Cobb's work include Metabolomics and Mass Spectrometry Studies (6 papers), Liver Disease Diagnosis and Treatment (4 papers) and Diet and metabolism studies (4 papers). Jeff E. Cobb is often cited by papers focused on Metabolomics and Mass Spectrometry Studies (6 papers), Liver Disease Diagnosis and Treatment (4 papers) and Diet and metabolism studies (4 papers). Jeff E. Cobb collaborates with scholars based in United States, Italy and United Kingdom. Jeff E. Cobb's co-authors include Ele Ferrannini, James M. Lenhard, Emily A. Hull-Ryde, Derek J. Parks, Steven G. Blanchard, Jon L. Collins, Kelli D. Plunket, Lisa M. Leesnitzer, Julie B. Stimmel and Randy K. Bledsoe and has published in prestigious journals such as The Journal of Clinical Endocrinology & Metabolism, Diabetes Care and Biochemistry.

In The Last Decade

Jeff E. Cobb

18 papers receiving 1.2k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jeff E. Cobb United States 12 877 336 167 152 147 19 1.2k
Chhabi Biswas United States 11 942 1.1× 455 1.4× 119 0.7× 173 1.1× 126 0.9× 13 1.2k
Lily Jow United States 10 1.3k 1.5× 477 1.4× 162 1.0× 105 0.7× 158 1.1× 10 1.5k
Toru Nishinaka Japan 22 769 0.9× 282 0.8× 106 0.6× 124 0.8× 100 0.7× 62 1.5k
Reeba K. Vikramadithyan United States 18 654 0.7× 237 0.7× 103 0.6× 218 1.4× 95 0.6× 27 1.2k
Teresa Tejerina Spain 25 587 0.7× 288 0.9× 117 0.7× 158 1.0× 118 0.8× 85 1.6k
Stacey Ruiz United States 8 937 1.1× 148 0.4× 125 0.7× 215 1.4× 92 0.6× 12 1.7k
Kazuhiro Sonoda Japan 14 784 0.9× 416 1.2× 252 1.5× 275 1.8× 131 0.9× 17 1.7k
Christopher Ho United States 8 488 0.6× 294 0.9× 180 1.1× 373 2.5× 156 1.1× 8 1.2k
Adriana Zuccollo Argentina 9 585 0.7× 376 1.1× 203 1.2× 299 2.0× 134 0.9× 15 1.3k
Yamei Han China 14 599 0.7× 206 0.6× 361 2.2× 129 0.8× 113 0.8× 37 1.1k

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-authorship network of co-authors of Jeff E. Cobb

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

All Works

19 of 19 papers shown
1.
Gopalacharyulu, Peddinti, Jeff E. Cobb, Loïc Yengo, et al.. (2017). Early metabolic markers identify potential targets for the prevention of type 2 diabetes. Diabetologia. 60(9). 1740–1750. 99 indexed citations
2.
Hernández‐Álvarez, María Isabel, Angels Díaz‐Ramos, María Berdasco, et al.. (2017). Early-onset and classical forms of type 2 diabetes show impaired expression of genes involved in muscle branched-chain amino acids metabolism. Scientific Reports. 7(1). 13850–13850. 44 indexed citations
3.
Ferrannini, Ele, Giorgio Iervasi, Jeff E. Cobb, Rudina Ndreu, & Monica Nannipieri. (2017). Insulin resistance and normal thyroid hormone levels: prospective study and metabolomic analysis. American Journal of Physiology-Endocrinology and Metabolism. 312(5). E429–E436. 40 indexed citations
4.
Cobb, Jeff E., et al.. (2016). α-Hydroxybutyric Acid Is a Selective Metabolite Biomarker of Impaired Glucose Tolerance. Diabetes Care. 39(6). 988–995. 97 indexed citations
5.
Solini, Anna, Maria Laura Manca, Giuseppe Penno, et al.. (2015). Prediction of Declining Renal Function and Albuminuria in Patients With Type 2 Diabetes by Metabolomics. The Journal of Clinical Endocrinology & Metabolism. 101(2). 696–704. 60 indexed citations
6.
Tripathy, Devjit, Jeff E. Cobb, Walter Gall, et al.. (2015). A Novel Insulin Resistance Index to Monitor Changes in Insulin Sensitivity and Glucose Tolerance: the ACT NOW Study. The Journal of Clinical Endocrinology & Metabolism. 100(5). 1855–1862. 26 indexed citations
7.
Cobb, Jeff E., Andrea D. Eckhart, Régis Périchon, et al.. (2014). A Novel Test for IGT Utilizing Metabolite Markers of Glucose Tolerance. Journal of Diabetes Science and Technology. 9(1). 69–76. 34 indexed citations
8.
Cobb, Jeff E., Walter Gall, Klaus‐Peter Adam, et al.. (2013). A Novel Fasting Blood Test for Insulin Resistance and Prediabetes. Journal of Diabetes Science and Technology. 7(1). 100–110. 64 indexed citations
9.
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11.
Cooper, Joel P., et al.. (2003). Synthesis and Identification of a Novel 6,5,6-Tricyclic Lactam. Heterocycles. 60(3). 607–607.
12.
Leesnitzer, Lisa M., Derek J. Parks, Randy K. Bledsoe, et al.. (2002). Functional Consequences of Cysteine Modification in the Ligand Binding Sites of Peroxisome Proliferator Activated Receptors by GW9662. Biochemistry. 41(21). 6640–6650. 491 indexed citations
13.
Lenhard, James M. & Jeff E. Cobb. (1999). IBC’s 6th International Symposium on Obesity and 3rd International Symposium on Insulin Resistance: March 22-25, 1999, Washington, DC. Expert Opinion on Investigational Drugs. 8(6). 911–916. 2 indexed citations
14.
Cobb, Jeff E., Steven G. Blanchard, Kathleen K. Brown, et al.. (1998). N-(2-Benzoylphenyl)-l-tyrosine PPARγ Agonists. 3. Structure−Activity Relationship and Optimization of the N-Aryl Substituent. Journal of Medicinal Chemistry. 41(25). 5055–5069. 96 indexed citations
15.
Collins, Jon L., Steven G. Blanchard, Paul S. Charifson, et al.. (1998). N-(2-Benzoylphenyl)-l-tyrosine PPARγ Agonists. 2. Structure−Activity Relationship and Optimization of the Phenyl Alkyl Ether Moiety. Journal of Medicinal Chemistry. 41(25). 5037–5054. 68 indexed citations
16.
Chen, Wen-Ji, Susan Armour, James M. Way, et al.. (1997). Expression Cloning and Receptor Pharmacology of Human Calcitonin Receptors from MCF-7 Cells and Their Relationship to Amylin Receptors. Molecular Pharmacology. 52(6). 1164–1175. 58 indexed citations
17.
Cobb, Jeff E. & M. Ross Johnson. (1991). Synthesis of 6-O-(2-aminoethyl)-D,L-MYO- inositol-1,2-cyclic phosphate: a model of a putative insulin second messenger. Tetrahedron. 47(1). 21–30. 10 indexed citations
18.
Baldwin, Jack E., Jeff E. Cobb, & L Sheppard. (1987). Functionalization of the 3β-methyl group of penicillin. Tetrahedron. 43(5). 1003–1012. 5 indexed citations
19.
Cobb, Jeff E., Aurora Bellino, Maria Marino, & Pietro Venturella. (1983). Carbon-13 Nuclear Magnetic Resonance Spectra of 2-Arylidene-3(2H)-benzofuranones. Heterocycles. 20(11). 2203–2203. 1 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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