Shibu John

1.1k citations
16 papers · 441 · h-index 11

Impact in

Papers in

Shibu John

16 papers receiving 430 citations

Peers

Shibu John
Comparison fields: 5 of 48
  • Cardiology and Cardiovascular Medicine 235
  • Developmental Neuroscience 14
  • Genetics 71
  • Molecular Biology 149
  • Endocrinology, Diabetes and Metabolism 31
Replace Hugo R. Martinez with:
Hugo R. Martinez United States
M Coulon France
Nitin Ghaisas Ireland
Chiara Baggio Italy
Lei Ruan China
Annapaola Cirillo Italy
P. Fain United States
Francesca Giacopelli Italy
Yumiko Ikemoto Japan
H. Pannu United States
Shibu John relative to Hugo R. Martinez United States Hugo R. Martinez's profile →
Citations per field
00.5×2×3.4×
Hugo R. Martinez · 1×
Citations per year

Countries citing papers authored by Shibu John

Since Specialization
Citations

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

Fields of papers citing papers by Shibu John

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

16 of 16 papers shown
#Work
1 2016141
2 201654
3 200849
4 201346
5 200836
6 201228
7 200920
8 201615
9 201014
10 200912
11 201912
12 20105
13 20144
14 20143
15 20171
16 20151

About Shibu John

Shibu John is a scholar working on Cardiology and Cardiovascular Medicine, Molecular Biology, Genetics, Pulmonary and Respiratory Medicine and Epidemiology, having authored 16 papers that have together received 441 indexed citations. Recurring topics across this work include Cardiomyopathy and Myosin Studies (5 papers), RNA and protein synthesis mechanisms (3 papers), Cardiac electrophysiology and arrhythmias (2 papers), Genomics and Rare Diseases (2 papers), Adipokines, Inflammation, and Metabolic Diseases (2 papers), Atherosclerosis and Cardiovascular Diseases (2 papers), Lipid metabolism and disorders (2 papers) and Genetic Associations and Epidemiology (2 papers). The work is most often cited by research in Cardiology and Cardiovascular Medicine (235 citations), Developmental Neuroscience (14 citations), Genetics (71 citations), Molecular Biology (149 citations) and Endocrinology, Diabetes and Metabolism (31 citations). Shibu John has collaborated with scholars based in United Kingdom, Singapore and United States. Frequent co-authors include James S. Ware, Stuart A. Cook, Roddy Walsh, Jayashree Shanker, Paul J.R. Barton, Vijay V. Kakkar, Rachel Buchan, Veena S. Rao, Chee Jian Pua and Alicja Wilk. Their work appears in journals such as Journal of Cardiovascular Translational Research, Thrombosis and Haemostasis, European Heart Journal, Heart and Journal of Cardiovascular Magnetic Resonance.

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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