Deepak Sharma

109 papers receiving 2.2k citations

Peers

Deepak Sharma
Comparison fields: 5 of 141
  • Structural Biology 41
  • Infectious Diseases 418
  • Biotechnology 148
  • Molecular Medicine 79
  • Aging 27
Replace Yujia Zhai with:
Yujia Zhai China
Pier Carlo Braga Italy
Lin‐Woo Kang South Korea
Xavier Fernàndez‐Busquets Spain
Menachem Shoham United States
Julian Weghuber Austria
Sylvie Derclaye Belgium
ISRAR AHMAD KHAN China
Kalyan Mitra India
Mauro Sola‐Penna Brazil
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Citations per field
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Citations per year

Countries citing papers authored by Deepak Sharma

Since Specialization
Citations

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

Fields of papers citing papers by Deepak Sharma

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 121 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2005234
2 2006118
3 2009117
4 2004110
5 2007108
6 200792
7 200272
8 200968
9 200865
10 200559
11 201155
12 201148
13 200946
14 201538
15 201337
16 201636
17 200835
18 202433
19 200833
20
Signal transduction systems of mycobacteria with special reference to M. tuberculosis
200432

About Deepak Sharma

Deepak Sharma is a scholar working on Infectious Diseases, Molecular Biology, Cell Biology, Genetics and Neurology, having authored 121 papers that have together received 2.2k indexed citations. Recurring topics across this work include Tuberculosis Research and Epidemiology (15 papers), Protein Structure and Dynamics (15 papers), Heat shock proteins research (13 papers), Force Microscopy Techniques and Applications (9 papers), Mycobacterium research and diagnosis (8 papers), Prion Diseases and Protein Misfolding (7 papers), Genetic and phenotypic traits in livestock (6 papers) and Enzyme Structure and Function (6 papers). The work is most often cited by research in Structural Biology (41 citations), Infectious Diseases (418 citations), Biotechnology (148 citations), Molecular Medicine (79 citations) and Aging (27 citations). Deepak Sharma has collaborated with scholars based in India, United States and Canada. Frequent co-authors include Daniel C. Masison, Jaya Sivaswami Tyagi, Hongbin Li, Amar Jyoti, Yi Cao, Bhupinder Singh Chadha, Harvinder Singh Saini, Swapandeep Singh Chimni, Santosh Chauhan and Balamurali MM. Their work appears in journals such as Proceedings of the National Academy of Sciences, Genetics, Biophysical Chemistry, International Journal of Biological Macromolecules and Biochimica et Biophysica Acta (BBA) - Proteins and Proteomics.

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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