Sabyasachi Sen

845 citations
49 papers · 589 indexed · h-index 14

Sabyasachi Sen

44 papers receiving 579 citations

Peers

Sabyasachi Sen
Comparison fields: 5 of 95
  • Endocrinology, Diabetes and Metabolism 166
  • Genetics 75
  • Endocrine and Autonomic Systems 35
  • Physiology 99
  • Cardiology and Cardiovascular Medicine 77
Replace Primož Kotnik with:
Primož Kotnik Slovenia
Jiandong Zhang China
Sinem Kıyıcı Türkiye
Emily K. Anderson‐Baucum United States
A. Scarda Italy
Nathan C. Winn United States
Yoshiyuki Hamamoto Japan
Ilana Koren Israel
Camilla H. Sandholt Denmark
Sabyasachi Sen relative to Primož Kotnik Slovenia Primož Kotnik's profile →
Citations per field
00.5×1.5×
Primož Kotnik · 1×
Citations per year

Countries citing papers authored by Sabyasachi Sen

Since Specialization
Citations

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

Fields of papers citing papers by Sabyasachi Sen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20253
2 20230
3 20231
4 20222
5 20229
6 202135
7 20213
8 20209
9 202021
10 20206
11 201910
12 201937
13 201838
14 20181
15 20179
16 201746
17 201629
18 201511
19
Abstract MP74: Use of Cd34+ Cells as a Cellular Biomarker in Prediabetes Subjects, Post Aerobic Exercise
20150
20 200913

About Sabyasachi Sen

Sabyasachi Sen is a scholar working on Endocrinology, Diabetes and Metabolism, Health Informatics, Endocrine and Autonomic Systems, Cardiology and Cardiovascular Medicine and Sensory Systems, having authored 49 papers that have together received 589 indexed citations. Recurring topics across this work include Angiogenesis and VEGF in Cancer (7 papers), Adipose Tissue and Metabolism (7 papers), Diabetes Treatment and Management (7 papers), Cardiovascular Disease and Adiposity (5 papers), Adipokines, Inflammation, and Metabolic Diseases (5 papers), Pancreatic function and diabetes (5 papers), Diabetes, Cardiovascular Risks, and Lipoproteins (4 papers) and Biochemical Analysis and Sensing Techniques (4 papers). The work is most often cited by research in Endocrinology, Diabetes and Metabolism (166 citations), Genetics (75 citations), Endocrine and Autonomic Systems (35 citations), Physiology (99 citations) and Cardiology and Cardiovascular Medicine (77 citations). Sabyasachi Sen has collaborated with scholars based in United States, Saudi Arabia and Sweden. Frequent co-authors include Cleyton C. Domingues, Madia Ricks, Anne E. Sumner, Richard Amdur, Carol Rouphael, Seshagiri Rao Nandula, Eric Nylén, Harvey Kushner, Kathryn E. Tiller and Costas D. Maranas. Their work appears in journals such as Stem Cell Research & Therapy, Metabolic Syndrome and Related Disorders, Circulation, Journal of the American Heart Association and Cardiovascular Diabetology.

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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