Deval D. Joshi

405 total citations
9 papers, 340 citations indexed

About

Deval D. Joshi is a scholar working on Cellular and Molecular Neuroscience, Molecular Biology and Oncology. According to data from OpenAlex, Deval D. Joshi has authored 9 papers receiving a total of 340 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Cellular and Molecular Neuroscience, 4 papers in Molecular Biology and 4 papers in Oncology. Recurrent topics in Deval D. Joshi's work include Neuropeptides and Animal Physiology (6 papers), Peptidase Inhibition and Analysis (3 papers) and Platelet Disorders and Treatments (2 papers). Deval D. Joshi is often cited by papers focused on Neuropeptides and Animal Physiology (6 papers), Peptidase Inhibition and Analysis (3 papers) and Platelet Disorders and Treatments (2 papers). Deval D. Joshi collaborates with scholars based in United States and South Korea. Deval D. Joshi's co-authors include Pranela Rameshwar, Pedro Gascón, Jing Qian, Paul Maloof, Anne C. Mosenthal, Meera Hameed, Jonathan S. Harrison, Persis Bandari, Prem N. Yadav and Jing Qian and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Blood and Annals of the New York Academy of Sciences.

In The Last Decade

Deval D. Joshi

9 papers receiving 338 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Deval D. Joshi United States 8 176 166 97 64 45 9 340
Carlo Arduino Italy 11 230 1.3× 79 0.5× 61 0.6× 24 0.4× 17 0.4× 25 490
Maria Piane Italy 14 497 2.8× 165 1.0× 132 1.4× 41 0.6× 25 0.6× 48 719
Glen A. Evans United States 9 314 1.8× 118 0.7× 106 1.1× 38 0.6× 21 0.5× 11 701
Jorge Pinto‐Basto Portugal 11 204 1.2× 115 0.7× 28 0.3× 14 0.2× 37 0.8× 25 414
Pierre Villeneuve Canada 8 139 0.8× 93 0.6× 89 0.9× 20 0.3× 42 0.9× 13 387
Samantha Fernandez-Sauze France 7 200 1.1× 148 0.9× 93 1.0× 83 1.3× 15 0.3× 7 438
Bérengère Fayard Switzerland 6 217 1.2× 90 0.5× 131 1.4× 8 0.1× 37 0.8× 6 445
Christopher A. Kerfoot United States 10 196 1.1× 48 0.3× 120 1.2× 39 0.6× 30 0.7× 16 462
Sofiane Saada France 13 148 0.8× 87 0.5× 163 1.7× 22 0.3× 49 1.1× 21 481
Monika Podkowa Canada 5 299 1.7× 105 0.6× 36 0.4× 42 0.7× 14 0.3× 5 425

Countries citing papers authored by Deval D. Joshi

Since Specialization
Citations

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

Fields of papers citing papers by Deval D. Joshi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Deval D. Joshi. 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 Deval D. Joshi. The network helps show where Deval D. Joshi may publish in the future.

Co-authorship network of co-authors of Deval D. Joshi

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

All Works

9 of 9 papers shown
1.
Bhalla, Sheena, et al.. (2013). Long-term follow-up for efficacy and safety of treatment of retinitis pigmentosa with valproic acid. British Journal of Ophthalmology. 97(7). 895–899. 29 indexed citations
2.
Harrison, Jonathan S., et al.. (2005). Peripheral monocytes and CD4+ cells are potential Sources for increased circulating levels of TGF‐β and substance P in autoimmune myelofibrosis. American Journal of Hematology. 81(1). 51–58. 15 indexed citations
3.
Bandari, Persis, Jing Qian, Ghassan Yehia, et al.. (2003). Hematopoietic growth factor inducible neurokinin-1 type: a transmembrane protein that is similar to neurokinin 1 interacts with substance P. Regulatory Peptides. 111(1-3). 169–178. 47 indexed citations
4.
Rameshwar, Pranela, et al.. (2002). Structural similarity between the bone marrow extracellular matrix protein and neurokinin 1 could be the limiting factor in the hematopoietic effects of substance P. Canadian Journal of Physiology and Pharmacology. 80(5). 475–481. 8 indexed citations
5.
Rameshwar, Pranela, Deval D. Joshi, Prem N. Yadav, et al.. (2001). Mimicry between neurokinin-1 and fibronectin may explain the transport and stability of increased substance P immunoreactivity in patients with bone marrow fibrosis. Blood. 97(10). 3025–3031. 36 indexed citations
6.
Maloof, Paul, et al.. (2001). Induction of preprotachykinin-I and neurokinin-1 by adrenocorticotropin and prolactin. Implication for neuroendocrine-immune-hematopoietic axis. Journal of Neuroimmunology. 112(1-2). 188–196. 15 indexed citations
8.
Gascon, Paula Herrero, et al.. (2000). Effects of Preprotachykinin‐I Peptides on Hematopoietic Homeostasis: A Role for Bone Marrow Endopeptidases. Annals of the New York Academy of Sciences. 917(1). 416–423. 5 indexed citations
9.
Joshi, Deval D., Meera Hameed, Jing Qian, et al.. (2000). Increased expression of preprotachykinin-I and neurokinin receptors in human breast cancer cells: Implications for bone marrow metastasis. Proceedings of the National Academy of Sciences. 97(1). 388–393. 142 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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