Vijay K. Yadav

5.3k total citations · 2 hit papers
55 papers, 3.7k citations indexed

About

Vijay K. Yadav is a scholar working on Molecular Biology, Physiology and Endocrinology, Diabetes and Metabolism. According to data from OpenAlex, Vijay K. Yadav has authored 55 papers receiving a total of 3.7k indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Molecular Biology, 13 papers in Physiology and 11 papers in Endocrinology, Diabetes and Metabolism. Recurrent topics in Vijay K. Yadav's work include Adipose Tissue and Metabolism (11 papers), Growth Hormone and Insulin-like Growth Factors (8 papers) and Regulation of Appetite and Obesity (8 papers). Vijay K. Yadav is often cited by papers focused on Adipose Tissue and Metabolism (11 papers), Growth Hormone and Insulin-like Growth Factors (8 papers) and Regulation of Appetite and Obesity (8 papers). Vijay K. Yadav collaborates with scholars based in United States, India and United Kingdom. Vijay K. Yadav's co-authors include Gérard Karsenty, Patricia Ducy, X. Edward Guo, Nina Suda, Kenji F. Tanaka, René Hen, Jay A. Gingrich, R. Medhamurthy, Franck Oury and Günther Schütz and has published in prestigious journals such as Nature, Cell and Proceedings of the National Academy of Sciences.

In The Last Decade

Vijay K. Yadav

52 papers receiving 3.7k citations

Hit Papers

Lrp5 Controls Bone Formation by Inhibiting Serotonin Synt... 2008 2026 2014 2020 2008 2019 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
Vijay K. Yadav United States 27 1.6k 877 593 514 492 55 3.7k
Charles Vinson United States 17 2.3k 1.4× 652 0.7× 508 0.9× 405 0.8× 490 1.0× 25 3.9k
Franck Oury France 24 1.4k 0.8× 637 0.7× 560 0.9× 387 0.8× 346 0.7× 46 3.2k
Wenhan Chang United States 45 2.2k 1.3× 745 0.8× 278 0.5× 610 1.2× 456 0.9× 127 4.6k
Takeshi Sakata Japan 35 1.7k 1.1× 607 0.7× 538 0.9× 868 1.7× 235 0.5× 121 4.0k
Masanobu Kawai Japan 29 1.3k 0.8× 523 0.6× 386 0.7× 380 0.7× 446 0.9× 116 2.8k
Klara Sjögren Sweden 34 2.5k 1.5× 992 1.1× 609 1.0× 493 1.0× 1.0k 2.1× 74 4.7k
Lingling Zhu China 31 1.7k 1.0× 377 0.4× 264 0.4× 304 0.6× 514 1.0× 115 3.4k
Z. Elizabeth Floyd United States 35 1.8k 1.1× 1.5k 1.7× 198 0.3× 482 0.9× 311 0.6× 83 4.9k
Christopher Cardozo United States 39 3.0k 1.8× 1.0k 1.2× 309 0.5× 584 1.1× 296 0.6× 153 5.0k
Joffrey Zoll France 42 2.0k 1.2× 1.5k 1.7× 276 0.5× 276 0.5× 532 1.1× 95 5.8k

Countries citing papers authored by Vijay K. Yadav

Since Specialization
Citations

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

Fields of papers citing papers by Vijay K. Yadav

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Vijay K. Yadav. 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 Vijay K. Yadav. The network helps show where Vijay K. Yadav may publish in the future.

Co-authorship network of co-authors of Vijay K. Yadav

This figure shows the co-authorship network connecting the top 25 collaborators of Vijay K. Yadav. A scholar is included among the top collaborators of Vijay K. Yadav 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 Vijay K. Yadav. Vijay K. Yadav 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.
Singh, Jyoti, et al.. (2024). ROLE OF ARTIFICIAL INTELLIGENCE FOR SUSTAINABLE AGRICULTURE: A REVIEW. PLANT ARCHIVES. 24(SI).
2.
Corvelo, André, Giuseppe Narzisi, Rajeeva Musunuri, et al.. (2024). Osteocalcin of maternal and embryonic origins synergize to establish homeostasis in offspring. EMBO Reports. 25(2). 593–615. 5 indexed citations
3.
Abyadeh, Morteza, Vijay K. Yadav, & Alaattin Kaya. (2023). Common Molecular Signatures Between Coronavirus Infection and Alzheimer’s Disease Reveal Targets for Drug Development. Journal of Alzheimer s Disease. 95(3). 995–1011. 3 indexed citations
4.
Venugopal, Kannan, et al.. (2022). Comparing the efficacy of intralesional triamcinolone acetonide and hyaluronidase with placental extract in oral submucous fibrosis cases: An original research. International Journal of Health Sciences. 278–284. 1 indexed citations
5.
Jain, Manu, et al.. (2022). 287P Long-term yoga enhances the quality of life and symptomatic scale in breast cancer patients undergoing treatment. Annals of Oncology. 33. S1544–S1544. 1 indexed citations
6.
Sawarkar, Sujata & Vijay K. Yadav. (2021). Novel drug delivery strategies and gene therapy regimen as a promising perspective for management of psoriasis. Indian Journal of Dermatology Venereology and Leprology. 87(3). 333–340. 6 indexed citations
7.
Chowdhury, Subrata, Biagio Palmisano, Parminder Singh, et al.. (2020). Muscle-derived interleukin 6 increases exercise capacity by signaling in osteoblasts. Journal of Clinical Investigation. 130(6). 2888–2902. 99 indexed citations
8.
Berger, Julian Meyer, Parminder Singh, Lori Khrimian, et al.. (2019). Mediation of the Acute Stress Response by the Skeleton. Cell Metabolism. 30(5). 890–902.e8. 115 indexed citations
9.
Choi, Wonsuk, Jun Namkung, Hyeongseok Kim, et al.. (2018). Serotonin signals through a gut-liver axis to regulate hepatic steatosis. Nature Communications. 9(1). 4824–4824. 124 indexed citations
10.
Kim, Hyeongseok, Wonsuk Choi, Joon Ho Moon, et al.. (2018). Generation of a highly efficient and tissue-specific tryptophan hydroxylase 1 knockout mouse model. Scientific Reports. 8(1). 17642–17642. 12 indexed citations
11.
Rached, Marie-Therese, Steven J. Millership, Silvia M.A. Pedroni, et al.. (2018). Deletion of myeloid IRS2 enhances adipose tissue sympathetic nerve function and limits obesity. Molecular Metabolism. 20. 38–50. 19 indexed citations
12.
Oh, Chang‐Myung, Jun Namkung, Younghoon Go, et al.. (2015). Regulation of systemic energy homeostasis by serotonin in adipose tissues. Nature Communications. 6(1). 6794–6794. 204 indexed citations
13.
Quirós-González, Isabel & Vijay K. Yadav. (2014). Central genes, pathways and modules that regulate bone mass. Archives of Biochemistry and Biophysics. 561. 130–136. 24 indexed citations
14.
Frost, M., Thomas Levin Andersen, Vijay K. Yadav, et al.. (2010). Patients with high bone mass phenotype due to Lrp5-T253i mutation have low plasma levels of serotonin. Bone. 47. S121–S121. 6 indexed citations
15.
Oury, Franck, Vijay K. Yadav, Ying Wang, et al.. (2010). CREB mediates brain serotonin regulation of bone mass through its expression in ventromedial hypothalamic neurons. Genes & Development. 24(20). 2330–2342. 90 indexed citations
16.
Yadav, Vijay K. & Gérard Karsenty. (2009). Leptin-dependent co-regulation of bone and energy metabolism. Aging. 1(11). 954–956. 21 indexed citations
17.
Yadav, Vijay K., Je-Hwang Ryu, Nina Suda, et al.. (2008). Lrp5 Controls Bone Formation by Inhibiting Serotonin Synthesis in the Duodenum. Cell. 135(5). 825–837. 636 indexed citations breakdown →
18.
Kidd, Grahame J., Vijay K. Yadav, Ping Huang, et al.. (2006). A dual tyrosine‐leucine motif mediates myelin protein P0 targeting in MDCK cells. Glia. 54(2). 135–145. 5 indexed citations
20.
Yadav, Vijay K.. (2004). Identification of novel genes regulated by LH in the primate corpus luteum: insight into their regulation during the late luteal phase. Molecular Human Reproduction. 10(9). 629–639. 27 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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