Jay V. Patankar

1.7k citations
35 papers · 1.1k indexed · 1 hit paper · h-index 18
Topics
Cholesterol and Lipid Metabolism (7 papers)Liver Disease Diagnosis and Treatment (6 papers)Diet, Metabolism, and Disease (5 papers)

In The Last Decade

Jay V. Patankar

34 papers receiving 1.1k citations

Hit Papers

Cell death in the gut epithelium and implications for chr...2020202620222024202050100150200250

Peers

Jay V. Patankar
Comparison fields: 5 of 88
  • Molecular Biology 513
  • Surgery 280
  • Oncology 198
  • Immunology 192
  • Epidemiology 181
Replace Miao Shen with:
Miao Shen China
Chiara Degirolamo Italy
Haruki Kato Japan
Kaili Fu China
Akinori Yanaka Japan
Robert N. Helsley United States
Kun Shi China
Yuhong Luo China
Veerle Bieghs Netherlands
Jay V. Patankar relative to Miao Shen China Miao Shen's profile →
Citations per field
00.5×2.9×
Miao Shen · 1×
Citations per year

Countries citing papers authored by Jay V. Patankar

Since Specialization
Citations

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

Fields of papers citing papers by Jay V. Patankar

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jay V. Patankar. 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 Jay V. Patankar. The network helps show where Jay V. Patankar may publish in the future.

Co-authorship network of co-authors of Jay V. Patankar

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

All Works

20 of 20 papers shown
#WorkIndexed citations
1 8
2 9
3 5
4 15
5 8
6 28
7 7
8
Cell death in the gut epithelium and implications for chronic inflammationbreakdown →
283
9 55
10 19
11 40
12 15
13 100
14 86
15 20
16 42
17 22
18 17
19 11
20 19

About Jay V. Patankar

Jay V. Patankar is a scholar working on Biochemistry, Gastroenterology and Endocrinology, Diabetes and Metabolism, having authored 35 papers that have together received 1.1k indexed citations. Recurring topics across this work include Cholesterol and Lipid Metabolism (7 papers), Liver Disease Diagnosis and Treatment (6 papers) and Diet, Metabolism, and Disease (5 papers). The work is most often cited by research in Biochemistry (89 citations), Immunology (192 citations) and Gastroenterology (47 citations). Jay V. Patankar has collaborated with scholars based in Austria, Germany and United States. Frequent co-authors include Christoph Becker, Dagmar Kratky, Sascha Obrowsky, Sanja Levak‐Frank, Albert K. Groen, Vinay Sachdev, Gerald Höefler, Michael R. Hayden, Prakash G. Chandak and Roshni R. Singaraja. Their work appears in journals such as PLoS ONE, Diabetes and Gut.

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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