Ankit Gilani

19 papers receiving 379 citations

Peers

Ankit Gilani
Comparison fields: 5 of 61
  • Biochemistry 154
  • Endocrinology, Diabetes and Metabolism 78
  • Physiology 61
  • Pharmacology 20
  • Pathology and Forensic Medicine 36
Replace Frank Fan Zhang with:
Frank Fan Zhang United States
Jessica A. Wray United Kingdom
Larry N Agbor United States
Hon‐Chi Lee United States
Mahesha Gangadhariah United States
Kevin Agostinucci United States
Eduard N. Lavrentyev United States
Noriko Aoi Japan
Jie Fang China
Ankit Gilani relative to Frank Fan Zhang United States Frank Fan Zhang's profile →
Citations per field
00.5×2.9×
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Citations per year

Countries citing papers authored by Ankit Gilani

Since Specialization
Citations

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

Fields of papers citing papers by Ankit Gilani

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 21 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2017140
2 201841
3 202435
4 202033
5 199330
6 202323
7 201419
8 201713
9 202411
10 202211
11 20207
12 20217
13 19933
14 20252
15 20201
16 20221
17 20241
18 20251
19 20191
20 20250

About Ankit Gilani

Ankit Gilani is a scholar working on Physiology, Biochemistry, Epidemiology, Endocrinology, Diabetes and Metabolism and Pathology and Forensic Medicine, having authored 21 papers that have together received 380 indexed citations. Recurring topics across this work include Eicosanoids and Hypertension Pharmacology (8 papers), Adipose Tissue and Metabolism (4 papers), Adipokines, Inflammation, and Metabolic Diseases (4 papers), Hormonal Regulation and Hypertension (3 papers), Nitric Oxide and Endothelin Effects (2 papers), Diabetes and associated disorders (2 papers), Liver Disease Diagnosis and Treatment (2 papers) and Cardiovascular Disease and Adiposity (2 papers). The work is most often cited by research in Biochemistry (154 citations), Endocrinology, Diabetes and Metabolism (78 citations), Physiology (61 citations), Pharmacology (20 citations) and Pathology and Forensic Medicine (36 citations). Ankit Gilani has collaborated with scholars based in United States, China and Japan. Frequent co-authors include Víctor Garcia, Michal L. Schwartzman, John R. Falck, Jorge H. Capdevila, James C. Lo, Kevin Agostinucci, Frank Fan Zhang, Rambabu Dakarapu, Darryl C. Zeldin and Joan P. Graves. Their work appears in journals such as The FASEB Journal, eLife, Comprehensive physiology, American Journal of Physiology-Regulatory, Integrative and Comparative Physiology and Journal of Pharmacology and Experimental Therapeutics.

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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