Linu M. John

3.3k citations
22 papers · 1.6k · h-index 13

Impact in

Papers in

Linu M. John

21 papers receiving 1.6k citations

Peers

Linu M. John
Comparison fields: 5 of 85
  • Endocrine and Autonomic Systems 104
  • Molecular Biology 891
  • Cell Biology 165
  • Physiology 236
  • Endocrinology, Diabetes and Metabolism 146
Replace Zhongji Liao with:
Zhongji Liao United States
Kim Ravnskjær Denmark
Stephan C. Collins United Kingdom
Mariano Ubeda United States
Hong Jiao Sweden
Rebecca Quinn United States
Lucia Berti Germany
Guida Maria Portela‐Gomes Sweden
Makoto Takenoshita Japan
Michio Nakaya Japan
Linu M. John relative to Zhongji Liao United States Zhongji Liao's profile →
Citations per field
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Citations per year

Countries citing papers authored by Linu M. John

Since Specialization
Citations

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

Fields of papers citing papers by Linu M. John

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 22 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2004483
2 2002481
3 1998177
4 202289
5 202073
6 199847
7 201938
8 200435
9 202029
10 202028
11 202224
12 200124
13 202118
14 202410
15 20248
16 20227
17 20217
18 20237
19
In vitro prediction of in vivo pseudo-allergenic response via MRGPRX2
20213
20
Plasma cortisol level in normal Indian subjects and its variation in disease.
19721

About Linu M. John

Linu M. John is a scholar working on Molecular Biology, Cellular and Molecular Neuroscience, Endocrine and Autonomic Systems, Physiology and Epidemiology, having authored 22 papers that have together received 1.6k indexed citations. Recurring topics across this work include Regulation of Appetite and Obesity (8 papers), Neuropeptides and Animal Physiology (6 papers), Adipose Tissue and Metabolism (4 papers), Diabetes Treatment and Management (3 papers), Fibroblast Growth Factor Research (3 papers), Epigenetics and DNA Methylation (3 papers), Neuroscience and Neuropharmacology Research (2 papers) and Kruppel-like factors research (2 papers). The work is most often cited by research in Endocrine and Autonomic Systems (104 citations), Molecular Biology (891 citations), Cell Biology (165 citations), Physiology (236 citations) and Endocrinology, Diabetes and Metabolism (146 citations). Linu M. John has collaborated with scholars based in Denmark, United States and Switzerland. Frequent co-authors include James D. Lechleiter, Patricia Camacho, Ling Fu, Elizabeth Tomlinson, Mark Renz, Timothy A. Stewart, Xiaojian Huang, Dorothy French, Bruce D. Hultgren and Lyn Powell-Braxton. Their work appears in journals such as Endocrinology, The Journal of Cell Biology, Biophysical Chemistry, Journal of Medicinal Chemistry and Cell Reports.

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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