Shubha Murthy

36 papers receiving 1.7k citations

Peers

Shubha Murthy
Comparison fields: 5 of 107
  • Cell Biology 272
  • Biochemistry 105
  • Pulmonary and Respiratory Medicine 406
  • Immunology 213
  • Molecular Biology 690
Replace Honglei Weng with:
Honglei Weng Germany
Janet S. Kerr United States
Jos van der Velden United States
Baoheng Du United States
Patricia Greenwel United States
Jeong Han Kang South Korea
Naomi Sakashita Japan
Michał Mikuła Poland
Vikas Anathy United States
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Citations per field
00.5×2.6×
Honglei Weng · 1×
Citations per year

Countries citing papers authored by Shubha Murthy

Since Specialization
Citations

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

Fields of papers citing papers by Shubha Murthy

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 37 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2002170
2 1993158
3 2013110
4 2015102
5 201081
6 199378
7 201177
8 201476
9 200968
10 201167
11 199865
12 200263
13 199357
14 201556
15 199051
16 199848
17 201735
18 200133
19 200533
20 200133

About Shubha Murthy

Shubha Murthy is a scholar working on Molecular Biology, Surgery, Pulmonary and Respiratory Medicine, Oncology and Cell Biology, having authored 37 papers that have together received 1.8k indexed citations. Recurring topics across this work include Interstitial Lung Diseases and Idiopathic Pulmonary Fibrosis (11 papers), Cholesterol and Lipid Metabolism (9 papers), Drug Transport and Resistance Mechanisms (7 papers), Occupational and environmental lung diseases (6 papers), Peroxisome Proliferator-Activated Receptors (5 papers), Neonatal Respiratory Health Research (4 papers), Protease and Inhibitor Mechanisms (3 papers) and Pulmonary Hypertension Research and Treatments (3 papers). The work is most often cited by research in Cell Biology (272 citations), Biochemistry (105 citations), Pulmonary and Respiratory Medicine (406 citations), Immunology (213 citations) and Molecular Biology (690 citations). Shubha Murthy has collaborated with scholars based in United States, Canada and Germany. Frequent co-authors include Satya N. Mathur, F. Jeffrey Field, Ella Born, Alan J. Ryan, Chao He, A. Brent Carter, Richard L. Eckert, James F. Crish, Michael B. Yaffe and Jennifer L. Larson‐Casey. Their work appears in journals such as Journal of Biological Chemistry, Journal of Lipid Research, Biochemical Journal, American Journal of Physiology-Lung Cellular and Molecular Physiology and Journal of Investigative Dermatology.

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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