Rakesh Verma

1.9k total citations
25 papers, 1.4k citations indexed

About

Rakesh Verma is a scholar working on Molecular Biology, Hematology and Oncology. According to data from OpenAlex, Rakesh Verma has authored 25 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Molecular Biology, 13 papers in Hematology and 7 papers in Oncology. Recurrent topics in Rakesh Verma's work include Multiple Myeloma Research and Treatments (10 papers), Protein Degradation and Inhibitors (8 papers) and Immune Cell Function and Interaction (6 papers). Rakesh Verma is often cited by papers focused on Multiple Myeloma Research and Treatments (10 papers), Protein Degradation and Inhibitors (8 papers) and Immune Cell Function and Interaction (6 papers). Rakesh Verma collaborates with scholars based in United States, Switzerland and Ireland. Rakesh Verma's co-authors include Chandra Sekhar Boddupalli, Madhav V. Dhodapkar, Rituparna Das, Kavita M. Dhodapkar, Lawrence B. Holzman, Harry Holthöfer, Iulia A. Kovari, Patricia L. St. John, Harriet M. Kluger and Mario Sznol and has published in prestigious journals such as Journal of Biological Chemistry, Journal of Clinical Investigation and Nature Medicine.

In The Last Decade

Rakesh Verma

24 papers receiving 1.4k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Rakesh Verma United States 10 549 522 514 445 213 25 1.4k
Miyuki Bohgaki Japan 19 191 0.3× 557 1.1× 296 0.6× 78 0.2× 219 1.0× 28 1.1k
Piernicola Boccuni United States 18 195 0.4× 1.0k 1.9× 389 0.8× 146 0.3× 602 2.8× 24 1.6k
Abel Suárez‐Fueyo United States 16 210 0.4× 334 0.6× 891 1.7× 75 0.2× 56 0.3× 21 1.4k
Geert Harms Netherlands 19 216 0.4× 1.0k 2.0× 358 0.7× 108 0.2× 36 0.2× 25 1.6k
Kirsten Neubert Germany 10 177 0.3× 414 0.8× 483 0.9× 75 0.2× 230 1.1× 13 1.0k
Consuelo Anzilotti United Kingdom 17 258 0.5× 455 0.9× 389 0.8× 38 0.1× 60 0.3× 24 1.1k
Chieko Kyogoku Japan 18 169 0.3× 410 0.8× 1.0k 2.0× 46 0.1× 67 0.3× 24 1.5k
Makoto Kawakita Japan 14 182 0.3× 360 0.7× 295 0.6× 114 0.3× 800 3.8× 30 1.3k
Adrian A. Lobito United States 13 177 0.3× 925 1.8× 876 1.7× 49 0.1× 163 0.8× 16 1.4k
Tammy Price-Troska United States 17 544 1.0× 835 1.6× 374 0.7× 53 0.1× 637 3.0× 34 1.6k

Countries citing papers authored by Rakesh Verma

Since Specialization
Citations

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

Fields of papers citing papers by Rakesh Verma

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Rakesh Verma

This figure shows the co-authorship network connecting the top 25 collaborators of Rakesh Verma. A scholar is included among the top collaborators of Rakesh 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 Rakesh Verma. Rakesh 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, Rakesh, et al.. (2023). 1535 DECOSTARTM, a novel platform for TNF receptor superfamily agonism. SHILAP Revista de lepidopterología. A1758–A1758. 1 indexed citations
2.
Verma, Rakesh, Andrew R. Branagan, Mina L. Xu, et al.. (2021). Role of MBD3-SOX2 axis in residual myeloma following pomalidomide. Leukemia. 35(11). 3319–3323. 1 indexed citations
3.
Mori, Tomoaki, Rakesh Verma, Rie Nakamoto-Matsubara, et al.. (2021). Low NCOR2 levels in multiple myeloma patients drive multidrug resistance via MYC upregulation. Blood Cancer Journal. 11(12). 194–194. 9 indexed citations
4.
Nakamoto-Matsubara, Rie, Valentina Nardi, Cristina Panaroni, et al.. (2021). Molecular Features and Clinical Outcomes of Extramedullary Plasmacytomas. Blood. 138(Supplement 1). 398–398. 2 indexed citations
5.
Branagan, Andrew R., Eamon Duffy, Geliang Gan, et al.. (2021). Tandem high-dose influenza vaccination is associated with more durable serologic immunity in patients with plasma cell dyscrasias. Blood Advances. 5(5). 1535–1539. 13 indexed citations
6.
Branagan, Andrew R., Eamon Duffy, Connor Foster, et al.. (2017). Two Dose Series of High-Dose Influenza Vaccine Is Associated with Longer Duration of Serologic Immunity in Patients with Plasma Cell Disorders. Blood. 130. 438–438. 4 indexed citations
7.
Dhodapkar, Kavita M., Chandra Sekhar Boddupalli, Noffar Bar, et al.. (2017). Distinct dominant T-cell receptors with a tissue resident memory phenotype in individual melanoma metastases.. Journal of Clinical Oncology. 35(7_suppl). 3–3. 1 indexed citations
8.
Branagan, Andrew R., Eamon Duffy, Randy A. Albrecht, et al.. (2017). Clinical and Serologic Responses After a Two-dose Series of High-dose Influenza Vaccine in Plasma Cell Disorders: A Prospective, Single-arm Trial. Clinical Lymphoma Myeloma & Leukemia. 17(5). 296–304.e2. 35 indexed citations
9.
Boddupalli, Chandra Sekhar, Noffar Bar, Krishna Kadaveru, et al.. (2016). Interlesional diversity of T cell receptors in melanoma with immune checkpoints enriched in tissue-resident memory T cells. JCI Insight. 1(21). 111 indexed citations
10.
Das, Rituparna, Till Strowig, Rakesh Verma, et al.. (2016). Microenvironment-dependent growth of preneoplastic and malignant plasma cells in humanized mice. Nature Medicine. 22(11). 1351–1357. 116 indexed citations
11.
12.
Sehgal, Kartik, Rituparna Das, Lin Zhang, et al.. (2015). Clinical and pharmacodynamic analysis of pomalidomide dosing strategies in myeloma: impact of immune activation and cereblon targets. Blood. 125(26). 4042–4051. 91 indexed citations
13.
Das, Rituparna, Till Strowig, Rakesh Verma, et al.. (2015). Niche-Dependent Growth of Malignant and Pre-Neoplastic Plasma Cells in Humanized Mice. Blood. 126(23). 120–120. 1 indexed citations
14.
Das, Rituparna, Rakesh Verma, Mario Sznol, et al.. (2014). Combination Therapy with Anti–CTLA-4 and Anti–PD-1 Leads to Distinct Immunologic Changes In Vivo. The Journal of Immunology. 194(3). 950–959. 322 indexed citations
15.
Nair, Shiny, Chandra Sekhar Boddupalli, Rakesh Verma, et al.. (2014). Type II NKT-TFH Cells Against Gaucher Lipids Regulate B Cell Immunity and Inflammation. Blood. 124(21). 755–755. 1 indexed citations
16.
17.
Sehgal, Kartik, Mehmet H. Kocoglu, Yanhong Deng, et al.. (2013). Comparison Of Intermittent and Continuous Dosing Regimens Of Pomalidomide In Relapsed/Refractory Myeloma: Results Of A Phase II Randomized Trial. Blood. 122(21). 3205–3205. 1 indexed citations
18.
Verma, Rakesh. (2006). Nephrin ectodomain engagement results in Src kinase activation, nephrin phosphorylation, Nck recruitment, and actin polymerization. Journal of Clinical Investigation. 116(5). 1346–1359. 261 indexed citations
19.
Verma, Rakesh, Bryan L. Wharram, Iulia A. Kovari, et al.. (2005). Fyn binds to and phosphorylates the kidney slit diaphragm component Nephrin. Vol. 278 (2003) 20716-20723. Journal of Biological Chemistry. 280(28). 26640–26640. 1 indexed citations
20.
Holzman, Lawrence B., et al.. (1999). Nephrin localizes to the slit pore of the glomerular epithelial cell. Kidney International. 56(4). 1481–1491. 256 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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