Subhash C. Verma

6.0k total citations · 1 hit paper
113 papers, 4.3k citations indexed

About

Subhash C. Verma is a scholar working on Oncology, Epidemiology and Infectious Diseases. According to data from OpenAlex, Subhash C. Verma has authored 113 papers receiving a total of 4.3k indexed citations (citations by other indexed papers that have themselves been cited), including 69 papers in Oncology, 64 papers in Epidemiology and 38 papers in Infectious Diseases. Recurrent topics in Subhash C. Verma's work include Viral-associated cancers and disorders (64 papers), Cytomegalovirus and herpesvirus research (54 papers) and Herpesvirus Infections and Treatments (28 papers). Subhash C. Verma is often cited by papers focused on Viral-associated cancers and disorders (64 papers), Cytomegalovirus and herpesvirus research (54 papers) and Herpesvirus Infections and Treatments (28 papers). Subhash C. Verma collaborates with scholars based in United States, India and Russia. Subhash C. Verma's co-authors include Erle S. Robertson, Timsy Uppal, Ke Lan, Pravinkumar Purushothaman, Qiliang Cai, Masanao Murakami, Cyprian C. Rossetto, Rajeev Kaul, Svetlana F. Khaiboullina and Andrew Gorzalski and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nucleic Acids Research and SHILAP Revista de lepidopterología.

In The Last Decade

Subhash C. Verma

111 papers receiving 4.3k citations

Hit Papers

Genomic evidence for reinfection with SARS-CoV-2: a case ... 2020 2026 2022 2024 2020 100 200 300 400

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Subhash C. Verma United States 36 2.3k 2.0k 1.5k 837 466 113 4.3k
Harutaka Katano Japan 39 2.2k 0.9× 1.7k 0.8× 1.6k 1.1× 690 0.8× 602 1.3× 194 4.8k
George Sourvinos Greece 36 789 0.3× 1.1k 0.6× 701 0.5× 1.2k 1.5× 314 0.7× 140 4.1k
Gulfaraz Khan United Arab Emirates 28 2.1k 0.9× 887 0.4× 698 0.5× 837 1.0× 1.3k 2.8× 81 3.8k
Gregory J. Babcock United States 29 2.3k 1.0× 1.5k 0.7× 1.6k 1.1× 769 0.9× 886 1.9× 49 4.7k
Maria Lina Tornesello Italy 45 1.5k 0.7× 1.8k 0.9× 757 0.5× 2.2k 2.6× 222 0.5× 184 5.9k
Kenneth M. Kaye United States 30 3.6k 1.6× 2.0k 1.0× 621 0.4× 919 1.1× 1.2k 2.6× 73 4.8k
Luigi Buonaguro Italy 49 2.1k 0.9× 2.4k 1.2× 1.2k 0.8× 3.2k 3.8× 383 0.8× 235 8.5k
Yasuko Mori Japan 36 1.2k 0.5× 3.0k 1.5× 857 0.6× 692 0.8× 93 0.2× 184 4.4k
Davide Gibellini Italy 36 536 0.2× 864 0.4× 1.2k 0.8× 1.3k 1.5× 210 0.5× 204 4.5k
Paolo Monini Italy 36 2.3k 1.0× 1.5k 0.8× 1.0k 0.7× 532 0.6× 639 1.4× 99 3.6k

Countries citing papers authored by Subhash C. Verma

Since Specialization
Citations

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

Fields of papers citing papers by Subhash C. Verma

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Subhash C. Verma. 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 Subhash C. Verma. The network helps show where Subhash C. Verma may publish in the future.

Co-authorship network of co-authors of Subhash C. Verma

This figure shows the co-authorship network connecting the top 25 collaborators of Subhash C. Verma. A scholar is included among the top collaborators of Subhash C. Verma 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 Subhash C. Verma. Subhash C. Verma 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.
Verma, Subhash C., et al.. (2025). Recent Advancements and Innovations in Post-harvest Handling, Storage, and Technology for Vegetables: A Review. Archives of Current Research International. 25(2). 161–180. 2 indexed citations
2.
Verma, Subhash C., et al.. (2025). Neutralizing antibody responses to SARS-CoV-2 variants after COVID-19 vaccination and boosters. Vaccine X. 24. 100664–100664.
3.
Verma, Subhash C., et al.. (2024). Core Competencies of a Veterinary Graduate. 2 indexed citations
5.
Gorzalski, Andrew, et al.. (2023). Analysis of SARS-CoV-2 variants from patient specimens in Nevada from October 2020 to August 2021. Infection Genetics and Evolution. 111. 105434–105434. 1 indexed citations
6.
Uppal, Timsy, et al.. (2022). Screening of SARS-CoV-2 antivirals through a cell-based RNA-dependent RNA polymerase (RdRp) reporter assay. SHILAP Revista de lepidopterología. 1(4). 100046–100046. 12 indexed citations
7.
Gorzalski, Andrew, Subhash C. Verma, Joel Sevinsky, et al.. (2022). Rapid repeat infection of SARS-CoV-2 by two highly distinct delta-lineage viruses. Diagnostic Microbiology and Infectious Disease. 104(1). 115747–115747. 3 indexed citations
8.
Martynova, Ekaterina, Vinay Kumar, Т И Хайбуллин, et al.. (2020). Serum and Cerebrospinal Fluid Cytokine Biomarkers for Diagnosis of Multiple Sclerosis. Mediators of Inflammation. 2020. 1–10. 17 indexed citations
9.
Khaiboullina, Svetlana F., Timsy Uppal, Rupa Sarkar, et al.. (2017). Zika Virus Infection Activates Proinflammatory Cytokines and Triggers Monocyte Differentiation. Blood. 130. 2290. 1 indexed citations
10.
Purushothaman, Pravinkumar, et al.. (2016). KSHV Genome Replication and Maintenance. Frontiers in Microbiology. 7. 54–54. 69 indexed citations
11.
Zhu, Caixia, Fang Wei, Jie Lu, et al.. (2014). Inhibition of KAP1 Enhances Hypoxia-Induced Kaposi's Sarcoma-Associated Herpesvirus Reactivation through RBP-Jκ. Journal of Virology. 88(12). 6873–6884. 46 indexed citations
13.
Rossetto, Cyprian C., et al.. (2013). Regulation of Viral and Cellular Gene Expression by Kaposi's Sarcoma-Associated Herpesvirus Polyadenylated Nuclear RNA. Journal of Virology. 87(10). 5540–5553. 101 indexed citations
14.
Kumar, Ashutosh, Suchitra Mohanty, Amit Kumar, et al.. (2013). Epstein–Barr virus nuclear antigen 3C interact with p73: Interplay between a viral oncoprotein and cellular tumor suppressor. Virology. 448. 333–343. 6 indexed citations
15.
Lu, Jie, Masanao Murakami, Subhash C. Verma, et al.. (2010). Epstein–Barr Virus nuclear antigen 1 (EBNA1) confers resistance to apoptosis in EBV-positive B-lymphoma cells through up-regulation of survivin. Virology. 410(1). 64–75. 79 indexed citations
16.
Bajaj, Bharat, Masanao Murakami, Qiliang Cai, et al.. (2008). Epstein-Barr Virus Nuclear Antigen 3C Interacts with and Enhances the Stability of the c-Myc Oncoprotein. Journal of Virology. 82(8). 4082–4090. 57 indexed citations
17.
Lan, Ke, Subhash C. Verma, Masanao Murakami, et al.. (2007). Kaposi's sarcoma herpesvirus-encoded latency-associated nuclear antigen stabilizes intracellular activated Notch by targeting the Sel10 protein. Proceedings of the National Academy of Sciences. 104(41). 16287–16292. 52 indexed citations
18.
Verma, Subhash C., Ke Lan, & Erle S. Robertson. (2006). Structure and Function of Latency-Associated Nuclear Antigen. Current topics in microbiology and immunology. 312. 101–136. 108 indexed citations
19.
Verma, Subhash C., et al.. (2000). Infection of Brucella melitensis in guinea pig (Cavia porcellus). The Indian Journal of Animal Sciences. 70(3). 1 indexed citations
20.
Katoch, Rajan, et al.. (2000). Investigation on the bacterial etiology of papilloma like growth on carps.. The Indian Veterinary Journal. 77(8). 721–722. 1 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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