Shanu Jain

1.0k citations
27 papers · 780 · h-index 16

Impact in

Papers in

    • Adenosine and Purinergic Signaling 15
    • Adipose Tissue and Metabolism 8
    • Receptor Mechanisms and Signaling 5
    • Pharmacological Receptor Mechanisms and Effects 3
    • Metabolism, Diabetes, and Cancer 2

Shanu Jain

26 papers receiving 770 citations

Peers

Shanu Jain
Comparison fields: 5 of 78
  • Physiology 307
  • Public Health, Environmental and Occupational Health 130
  • Physiology 118
  • Molecular Biology 325
  • Endocrine and Autonomic Systems 29
Replace Julianna D. Zeidler with:
Julianna D. Zeidler Brazil
Mohan E. Tulapurkar United States
Katherine Figarella Germany
Dazhi Zhao United States
Hans P. Baer Canada
Mariana Silva dos Santos United Kingdom
Mônica S. Freitas Brazil
Néstor L. Uzcátegui Venezuela
Yi-Lin Cheng Taiwan
Ing-Cherng Guo Taiwan
Shanu Jain relative to Julianna D. Zeidler Brazil Julianna D. Zeidler's profile →
Citations per field
00.5×3.5×
Julianna D. Zeidler · 1×
Citations per year

Countries citing papers authored by Shanu Jain

Since Specialization
Citations

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

Fields of papers citing papers by Shanu Jain

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 27 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2019156
2 201283
3 201462
4 201951
5 201943
6 202042
7 202039
8 202138
9 201836
10 201432
11 201530
12 202127
13 202121
14 201720
15 202115
16 202015
17 202114
18 201814
19 202012
20 20229

About Shanu Jain

Shanu Jain is a scholar working on Physiology, Molecular Biology, Physiology, Surgery and Organic Chemistry, having authored 27 papers that have together received 780 indexed citations. Recurring topics across this work include Adenosine and Purinergic Signaling (15 papers), Adipose Tissue and Metabolism (8 papers), Pancreatic function and diabetes (6 papers), Receptor Mechanisms and Signaling (5 papers), Pharmacological Receptor Mechanisms and Effects (3 papers), Metabolism, Diabetes, and Cancer (2 papers), Diabetes Treatment and Management (2 papers) and Cannabis and Cannabinoid Research (2 papers). The work is most often cited by research in Physiology (307 citations), Public Health, Environmental and Occupational Health (130 citations), Physiology (118 citations), Molecular Biology (325 citations) and Endocrine and Autonomic Systems (29 citations). Shanu Jain has collaborated with scholars based in United States, India and Germany. Frequent co-authors include Kenneth A. Jacobson, Zhan‐Guo Gao, Dilip K. Tosh, Raj K. Bhatnagar, Sujatha Sunil, Jatin Shrinet, Sai P. Pydi, Jürgen Wess, Luiz F. Barella and Oksana Gavrilova. Their work appears in journals such as Diabetes, Bioorganic & Medicinal Chemistry Letters, Biochemical Pharmacology, Nature Communications and Frontiers in 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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