Tushar Vaidya

897 total citations
17 papers, 735 citations indexed

About

Tushar Vaidya is a scholar working on Molecular Biology, Immunology and Public Health, Environmental and Occupational Health. According to data from OpenAlex, Tushar Vaidya has authored 17 papers receiving a total of 735 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Molecular Biology, 8 papers in Immunology and 6 papers in Public Health, Environmental and Occupational Health. Recurrent topics in Tushar Vaidya's work include T-cell and B-cell Immunology (6 papers), Immune Cell Function and Interaction (6 papers) and Research on Leishmaniasis Studies (6 papers). Tushar Vaidya is often cited by papers focused on T-cell and B-cell Immunology (6 papers), Immune Cell Function and Interaction (6 papers) and Research on Leishmaniasis Studies (6 papers). Tushar Vaidya collaborates with scholars based in India, United States and Switzerland. Tushar Vaidya's co-authors include Elizabeth J. Taparowsky, Simon J. Rhodes, Stephen F. Konieczny, Ramakrishnan Nagaraj, Shashi Singh, Satyajit Rath, Vineeta Bal, Anna George, Vineeth Varanasi and Balachandran Ravindran and has published in prestigious journals such as The Journal of Experimental Medicine, The Journal of Cell Biology and The Journal of Immunology.

In The Last Decade

Tushar Vaidya

17 papers receiving 712 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Tushar Vaidya India	11	435	165	159	106	77	17	735
Virginie Martin France	17	379 0.9×	217 1.3×	207 1.3×	135 1.3×	100 1.3×	27	929
Andrew R. Flannery United States	15	540 1.2×	274 1.7×	283 1.8×	85 0.8×	85 1.1×	21	1.1k
Nancy Starobinas Brazil	17	216 0.5×	179 1.1×	230 1.4×	258 2.4×	64 0.8×	57	754
Adel M. Nour United States	9	512 1.2×	75 0.5×	126 0.8×	279 2.6×	43 0.6×	13	779
Thiago Castro‐Gomes Brazil	14	276 0.6×	134 0.8×	135 0.8×	95 0.9×	41 0.5×	29	636
Ling Kong United States	13	381 0.9×	107 0.6×	116 0.7×	53 0.5×	59 0.8×	28	756
Minjun Yu China	15	305 0.7×	45 0.3×	144 0.9×	205 1.9×	33 0.4×	54	749
Yaron Vagima Israel	14	282 0.6×	46 0.3×	102 0.6×	168 1.6×	53 0.7×	35	737
Shinya Hidano Japan	13	243 0.6×	90 0.5×	93 0.6×	185 1.7×	63 0.8×	29	580
Krishna Murari Sinha United States	20	790 1.8×	79 0.5×	233 1.5×	52 0.5×	15 0.2×	32	1.0k

Countries citing papers authored by Tushar Vaidya

Since Specialization

Citations

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

Fields of papers citing papers by Tushar Vaidya

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Tushar Vaidya

This figure shows the co-authorship network connecting the top 25 collaborators of Tushar Vaidya. A scholar is included among the top collaborators of Tushar Vaidya 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 Tushar Vaidya. Tushar Vaidya is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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17 of 17 papers shown

Vaidya, Tushar, et al.. (2022). CD40 signaling-mediated delay in terminal differentiation of B cells enables alternate fate choices during early divisions. Molecular Immunology. 144. 1–15. 2 indexed citations

Vaidya, Tushar, et al.. (2021). Homotypic aggregates contribute to heterogeneity in B cell fates due to an intrinsic gradient of stimulant exposure. Experimental Cell Research. 405(1). 112650–112650. 3 indexed citations

Vaidya, Tushar, et al.. (2020). CD40-miRNA axis controls prospective cell fate determinants during B cell differentiation. Molecular Immunology. 126. 46–55. 17 indexed citations

Basu, Srijani, et al.. (2016). Constitutive CD40 Signaling Calibrates Differentiation Outcomes in Responding B Cells via Multiple Molecular Pathways. The Journal of Immunology. 197(3). 761–770. 6 indexed citations

Bhattacharyya, Anirban, Mohammad Shadab, Nirupam Das, et al.. (2016). Leishmania donovani Aurora kinase: A promising therapeutic target against visceral leishmaniasis. Biochimica et Biophysica Acta (BBA) - General Subjects. 1860(9). 1973–1988. 18 indexed citations

Rath, Satyajit, et al.. (2014). CD40 Signaling Drives B Lymphocytes Into an Intermediate Memory‐Like State, Poised Between Naïve and Plasma Cells. Journal of Cellular Physiology. 229(10). 1387–1396. 11 indexed citations

Panda, Sujogya Kumar, Sunil Kumar, Tushar Vaidya, et al.. (2012). Chitohexaose Activates Macrophages by Alternate Pathway through TLR4 and Blocks Endotoxemia. PLoS Pathogens. 8(5). e1002717–e1002717. 79 indexed citations

Sankaranarayanan, Rajan, et al.. (2011). Evolutionary and functional insights into Leishmania META1: evidence for lateral gene transfer and a role for META1 in secretion. BMC Evolutionary Biology. 11(1). 334–334. 9 indexed citations

Varanasi, Vineeth, Hamid Mattoo, Abhishek Das, et al.. (2010). A Superantigen Interacts with Leishmanial Infection in Antigen‐Presenting Cells to Regulate Cytokine Commitment of Responding CD4 T Cells. The Journal of Infectious Diseases. 202(8). 1234–1245. 2 indexed citations

10.

Shenoy, Gautam N., et al.. (2010). Inhibition of Terminal Differentiation of B Cells Mediated by CD27 and CD40 Involves Signaling through JNK. The Journal of Immunology. 185(11). 6499–6507. 7 indexed citations

11.

Varanasi, Vineeth, et al.. (2008). Development of a real-time polymerase chain reaction assay for the quantification of Leishmania species and the monitoring of systemic distribution of the pathogen. Diagnostic Microbiology and Infectious Disease. 61(1). 23–30. 49 indexed citations

12.

Singh, Shashi, et al.. (2003). Induction of autophagic cell death in Leishmania donovani by antimicrobial peptides. Molecular and Biochemical Parasitology. 127(1). 23–35. 126 indexed citations

13.

Vaidya, Tushar, Moiz Bakhiet, Kent L. Hill, et al.. (1997). The Gene for a T Lymphocyte Triggering Factor from African Trypanosomes. The Journal of Experimental Medicine. 186(3). 433–438. 49 indexed citations

14.

Vaidya, Tushar, et al.. (1992). Isolation and structural analysis of the rat MyoD gene. Gene. 116(2). 223–230. 18 indexed citations

15.

Vaidya, Tushar, Crystal M. Weyman, Dorothy Teegarden, Curtis L. Ashendel, & Elizabeth J. Taparowsky. (1991). Inhibition of myogenesis by the H-ras oncogene: implication of a role for protein kinase C.. The Journal of Cell Biology. 114(4). 809–820. 46 indexed citations

16.

Vaidya, Tushar, Simon J. Rhodes, Elizabeth J. Taparowsky, & Stephen F. Konieczny. (1989). Fibroblast growth factor and transforming growth factor beta repress transcription of the myogenic regulatory gene MyoD1.. Molecular and Cellular Biology. 9(8). 3576–3579. 102 indexed citations

17.

Vaidya, Tushar, Simon J. Rhodes, Elizabeth J. Taparowsky, & Stephen F. Konieczny. (1989). Fibroblast Growth Factor and Transforming Growth Factor β Repress Transcription of the Myogenic Regulatory Gene MyoD1. Molecular and Cellular Biology. 9(8). 3576–3579. 191 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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