Jyoti Shetty

14.2k total citations · 1 hit paper
17 papers, 1.5k citations indexed

About

Jyoti Shetty is a scholar working on Molecular Biology, Cancer Research and Immunology. According to data from OpenAlex, Jyoti Shetty has authored 17 papers receiving a total of 1.5k indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Molecular Biology, 7 papers in Cancer Research and 5 papers in Immunology. Recurrent topics in Jyoti Shetty's work include Immune Cell Function and Interaction (5 papers), Genomics and Phylogenetic Studies (5 papers) and Molecular Biology Techniques and Applications (4 papers). Jyoti Shetty is often cited by papers focused on Immune Cell Function and Interaction (5 papers), Genomics and Phylogenetic Studies (5 papers) and Molecular Biology Techniques and Applications (4 papers). Jyoti Shetty collaborates with scholars based in United States, France and Australia. Jyoti Shetty's co-authors include James F. Kolonay, Fred C. Tenover, Don B. Clewell, Linda M. Weigel, Steven R. Gill, Linda K. McDougal, George Killgore, Nancye C. Clark, Susan E. Flannagan and Bao Tran and has published in prestigious journals such as Science, Proceedings of the National Academy of Sciences and Nature Communications.

In The Last Decade

Jyoti Shetty

16 papers receiving 1.5k citations

Hit Papers

Genetic Analysis of a High-Level Vancomycin-Resistant Iso... 2003 2026 2010 2018 2003 200 400 600

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jyoti Shetty United States 13 856 423 284 208 177 17 1.5k
Long Sun China 19 457 0.5× 303 0.7× 190 0.7× 167 0.8× 114 0.6× 77 1.4k
Vickers Burdett United States 21 1.5k 1.7× 414 1.0× 460 1.6× 188 0.9× 135 0.8× 27 2.4k
Richard A. Winegar United States 20 647 0.8× 195 0.5× 105 0.4× 308 1.5× 191 1.1× 38 1.2k
Jiří Stulík Czechia 30 1.8k 2.1× 338 0.8× 661 2.3× 130 0.6× 79 0.4× 122 2.7k
Frédéric Taïeb France 25 1.8k 2.1× 331 0.8× 469 1.7× 114 0.5× 185 1.0× 40 2.8k
Saleem A. Khan United States 28 1.7k 1.9× 274 0.6× 848 3.0× 414 2.0× 226 1.3× 90 2.5k
Gintaras Deikus United States 26 1.2k 1.4× 273 0.6× 310 1.1× 41 0.2× 354 2.0× 47 1.7k
Ulf Schaefer United Kingdom 16 692 0.8× 121 0.3× 122 0.4× 162 0.8× 47 0.3× 23 1.3k
Hanni Willenbrock Denmark 14 1.2k 1.4× 154 0.4× 424 1.5× 343 1.6× 201 1.1× 22 1.9k
Arthur E. Franke United States 16 762 0.9× 408 1.0× 311 1.1× 49 0.2× 60 0.3× 19 1.4k

Countries citing papers authored by Jyoti Shetty

Since Specialization
Citations

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

Fields of papers citing papers by Jyoti Shetty

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jyoti Shetty

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

All Works

17 of 17 papers shown
1.
Harrington, Brittney S., Soumya Korrapati, Jyoti Shetty, et al.. (2023). NF-κB Signaling Modulates miR-452-5p and miR-335-5p Expression to Functionally Decrease Epithelial Ovarian Cancer Progression in Tumor-Initiating Cells. International Journal of Molecular Sciences. 24(9). 7826–7826. 5 indexed citations
2.
Hebron, Katie E., Yuliya Kriga, Juan Manuel Caravaca, et al.. (2023). Abstract LB_A23: The role of SMARCA1 in Rhabdomyosarcoma and skeletal muscle differentiation. Molecular Cancer Therapeutics. 22(12_Supplement). LB_A23–LB_A23.
3.
Song, Na‐Young, Xin Li, Buyong Ma, et al.. (2022). IKKα-deficient lung adenocarcinomas generate an immunosuppressive microenvironment by overproducing Treg-inducing cytokines. Proceedings of the National Academy of Sciences. 119(6). 13 indexed citations
4.
Harrington, Brittney S., Michelle Ozaki, Lídia Hernandez, et al.. (2020). Drugs Targeting Tumor-Initiating Cells Prolong Survival in a Post-Surgery, Post-Chemotherapy Ovarian Cancer Relapse Model. Cancers. 12(6). 1645–1645. 30 indexed citations
5.
Talsania, Keyur, et al.. (2020). Optimization for Sequencing and Analysis of Degraded FFPE-RNA Samples. Journal of Visualized Experiments. 8 indexed citations
6.
Talsania, Keyur, et al.. (2020). Optimization for Sequencing and Analysis of Degraded FFPE-RNA Samples. Journal of Visualized Experiments. 6 indexed citations
7.
Zhao, Yongmei, Monika Mehta, Ashley Walton, et al.. (2019). Robustness of RNA sequencing on older formalin-fixed paraffin-embedded tissue from high-grade ovarian serous adenocarcinomas. PLoS ONE. 14(5). e0216050–e0216050. 35 indexed citations
8.
Vacchio, Melanie S., Thomas Ciucci, Yayi Gao, et al.. (2019). A Thpok-Directed Transcriptional Circuitry Promotes Bcl6 and Maf Expression to Orchestrate T Follicular Helper Differentiation. Immunity. 51(3). 465–478.e6. 29 indexed citations
9.
Zheng, Hongping, Yotsawat Pomyen, Maria O. Hernandez, et al.. (2018). Single‐cell analysis reveals cancer stem cell heterogeneity in hepatocellular carcinoma. Hepatology. 68(1). 127–140. 267 indexed citations
10.
Carpenter, Andrea C., Laura B. Chopp, Melanie S. Vacchio, et al.. (2017). Control of Regulatory T Cell Differentiation by the Transcription Factors Thpok and LRF. The Journal of Immunology. 199(5). 1716–1728. 16 indexed citations
11.
Manna, Sugata, J. Kim, Catherine Baugé, et al.. (2015). Histone H3 Lysine 27 demethylases Jmjd3 and Utx are required for T-cell differentiation. Nature Communications. 6(1). 8152–8152. 88 indexed citations
12.
Swaminathan, Sanjay, Xiaojun Hu, Yuliya Kriga, et al.. (2013). Interleukin-27 treated human macrophages induce the expression of novel microRNAs which may mediate anti-viral properties. Biochemical and Biophysical Research Communications. 434(2). 228–234. 40 indexed citations
13.
Dalrymple, Brian P., Ewen F. Kirkness, Mikhail Nefedov, et al.. (2007). Using comparative genomics to reorder the human genome sequence into a virtual sheep genome. Genome biology. 8(7). R152–R152. 69 indexed citations
14.
Shedlock, Andrew M., Christopher Botka, Shaying Zhao, et al.. (2007). Phylogenomics of nonavian reptiles and the structure of the ancestral amniote genome. Proceedings of the National Academy of Sciences. 104(8). 2767–2772. 106 indexed citations
15.
Zhao, Shaying, Jyoti Shetty, Lihua Hou, et al.. (2004). Human, Mouse, and Rat Genome Large-Scale Rearrangements: Stability Versus Speciation. Genome Research. 14(10a). 1851–1860. 115 indexed citations
16.
Weigel, Linda M., Don B. Clewell, Steven R. Gill, et al.. (2003). Genetic Analysis of a High-Level Vancomycin-Resistant Isolate of Staphylococcus aureus. Science. 302(5650). 1569–1571. 668 indexed citations breakdown →
17.
Zhao, Shaying, S. Shatsman, Getahun Tsegaye, et al.. (2001). Mouse BAC Ends Quality Assessment and Sequence Analyses. Genome Research. 11(10). 1736–1745. 42 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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