Salil Ghosh

1.3k total citations
40 papers, 988 citations indexed

About

Salil Ghosh is a scholar working on Molecular Biology, Infectious Diseases and Aging. According to data from OpenAlex, Salil Ghosh has authored 40 papers receiving a total of 988 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Molecular Biology, 11 papers in Infectious Diseases and 6 papers in Aging. Recurrent topics in Salil Ghosh's work include Glycosylation and Glycoproteins Research (7 papers), Leprosy Research and Treatment (7 papers) and Genetics, Aging, and Longevity in Model Organisms (6 papers). Salil Ghosh is often cited by papers focused on Glycosylation and Glycoproteins Research (7 papers), Leprosy Research and Treatment (7 papers) and Genetics, Aging, and Longevity in Model Organisms (6 papers). Salil Ghosh collaborates with scholars based in United States, India and United Kingdom. Salil Ghosh's co-authors include John A. Hanover, Asesh Banerjee, Brian A. Lewis, Stella Maris Ranuncolo, Dona C. Love, Gerald W. Hart, Tapati Chakraborti, Sajal Chakraborti, John R. Michael and Michael Krause and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Biological Chemistry and The Journal of Experimental Medicine.

In The Last Decade

Salil Ghosh

39 papers receiving 967 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Salil Ghosh United States 19 574 182 152 129 110 40 988
Payman Amiri United States 14 734 1.3× 262 1.4× 123 0.8× 83 0.6× 17 0.2× 17 1.4k
Shruthi Sridhar Vembar India 16 1.0k 1.8× 257 1.4× 40 0.3× 57 0.4× 29 0.3× 25 1.7k
Michael P. Housley United States 14 1.9k 3.4× 904 5.0× 816 5.4× 181 1.4× 45 0.4× 17 2.6k
Hinton J. Baker United States 12 573 1.0× 127 0.7× 140 0.9× 95 0.7× 9 0.1× 25 1.2k
Jimmy R. Thériault United States 16 1.0k 1.8× 344 1.9× 19 0.1× 65 0.5× 27 0.2× 21 1.4k
Virendra K. Bajpai India 18 323 0.6× 206 1.1× 28 0.2× 39 0.3× 11 0.1× 25 921
Sylviane Dewaele Belgium 16 674 1.2× 187 1.0× 129 0.8× 55 0.4× 48 0.4× 29 900
Zeljka Smit‐McBride United States 22 1.3k 2.3× 331 1.8× 14 0.1× 118 0.9× 86 0.8× 47 2.0k
John R. Yates United States 15 1.5k 2.5× 61 0.3× 12 0.1× 142 1.1× 51 0.5× 21 1.9k
Vladimir V. Gorn Russia 10 756 1.3× 115 0.6× 53 0.3× 72 0.6× 6 0.1× 28 1.2k

Countries citing papers authored by Salil Ghosh

Since Specialization
Citations

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

Fields of papers citing papers by Salil Ghosh

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Salil Ghosh

This figure shows the co-authorship network connecting the top 25 collaborators of Salil Ghosh. A scholar is included among the top collaborators of Salil Ghosh 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 Salil Ghosh. Salil Ghosh 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
1.
2.
Ghosh, Salil, et al.. (2024). Insights of infected Schwann cells extinction and inherited randomness in a stochastic model of leprosy. Mathematical Biosciences. 376. 109281–109281. 2 indexed citations
3.
Ghosh, Salil, et al.. (2023). Implementation of suitable optimal control strategy through introspection of different delay induced mathematical models for leprosy: A comparative study. Optimal Control Applications and Methods. 45(1). 336–361. 7 indexed citations
4.
Ghosh, Salil, et al.. (2023). Critical observation of WHO recommended multidrug therapy on the disease leprosy through mathematical study. Journal of Theoretical Biology. 567. 111496–111496. 4 indexed citations
5.
Eustice, Moriah, Jeff Reece, Salil Ghosh, et al.. (2022). Nutrient sensing pathways regulating adult reproductive diapause in C. elegans. PLoS ONE. 17(9). e0274076–e0274076. 8 indexed citations
6.
Krause, Michael, Dona C. Love, Salil Ghosh, et al.. (2018). Nutrient-Driven O-GlcNAcylation at Promoters Impacts Genome-Wide RNA Pol II Distribution. Frontiers in Endocrinology. 9. 521–521. 12 indexed citations
7.
Parsons, Lisa M., Md Mizanur Rahman, Ewa A. Jankowska, et al.. (2014). Caenorhabditis elegans Bacterial Pathogen Resistant bus-4 Mutants Produce Altered Mucins. PLoS ONE. 9(10). e107250–e107250. 24 indexed citations
8.
Ghosh, Salil, Michelle Bond, Dona C. Love, et al.. (2014). Disruption of O-GlcNAc Cycling in C. elegans Perturbs Nucleotide Sugar Pools and Complex Glycans. Frontiers in Endocrinology. 5. 197–197. 13 indexed citations
9.
Kang, Dong Wook, Michelle Bond, Salil Ghosh, et al.. (2013). Optimizing the selectivity of DIFO-based reagents for intracellular bioorthogonal applications. Carbohydrate Research. 377. 18–27. 25 indexed citations
10.
Ghosh, Salil, et al.. (2012). SRY-positive 46, XY male with vanishing testis syndrome, feminization and gynecomastia.. PubMed. 14(1). 1–4. 1 indexed citations
11.
Ranuncolo, Stella Maris, Salil Ghosh, John A. Hanover, Gerald W. Hart, & Brian A. Lewis. (2012). Evidence of the Involvement of O-GlcNAc-modified Human RNA Polymerase II CTD in Transcription in Vitro and in Vivo. Journal of Biological Chemistry. 287(28). 23549–23561. 124 indexed citations
12.
Mondoux, Michelle A., Dona C. Love, Salil Ghosh, et al.. (2011). O-Linked-N-Acetylglucosamine Cycling and Insulin Signaling Are Required for the Glucose Stress Response inCaenorhabditis elegans. Genetics. 188(2). 369–382. 49 indexed citations
13.
Love, Dona C., Salil Ghosh, Michelle A. Mondoux, et al.. (2010). Dynamic O-GlcNAc cycling at promoters of Caenorhabditis elegans genes regulating longevity, stress, and immunity. Proceedings of the National Academy of Sciences. 107(16). 7413–7418. 119 indexed citations
14.
Ghosh, Salil, et al.. (2004). Pathogenic consequences of Neisseria gonorrhoeae pilin glycan variation. Microbes and Infection. 6(7). 693–701. 9 indexed citations
15.
Hughes, Molly A., Salil Ghosh, Andrew Mills, et al.. (2003). Identification of Entamoeba histolytica thiol-specific antioxidant as a GalNAc lectin-associated protein. Molecular and Biochemical Parasitology. 127(2). 113–120. 30 indexed citations
16.
17.
Banerjee, Asesh & Salil Ghosh. (2003). The role of pilin glycan in neisserial pathogenesis. Molecular and Cellular Biochemistry. 253(1-2). 179–190. 35 indexed citations
18.
Ghosh, Salil, et al.. (2002). ATF-1 Mediates Protease-activated Receptor-1 but Not Receptor Tyrosine Kinase-induced DNA Synthesis in Vascular Smooth Muscle Cells. Journal of Biological Chemistry. 277(24). 21325–21331. 18 indexed citations
19.
Chakraborti, Sajal, et al.. (1998). Targets of oxidative stress in cardiovascular system. Molecular and Cellular Biochemistry. 187(1-2). 1–10. 63 indexed citations
20.
Ghosh, Salil, Tapati Chakraborti, John R. Michael, & Sajal Chakraborti. (1996). Oxidant‐mediated proteolytic activation of Ca2+‐ATPase in microsomes of pulmonary smooth muscle. FEBS Letters. 387(2-3). 171–174. 12 indexed citations

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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