Uma Chandran

1.1k total citations · 1 hit paper
11 papers, 718 citations indexed

About

Uma Chandran is a scholar working on Molecular Biology, Reproductive Medicine and Computational Theory and Mathematics. According to data from OpenAlex, Uma Chandran has authored 11 papers receiving a total of 718 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Molecular Biology, 4 papers in Reproductive Medicine and 3 papers in Computational Theory and Mathematics. Recurrent topics in Uma Chandran's work include Sperm and Testicular Function (4 papers), Genetic and Clinical Aspects of Sex Determination and Chromosomal Abnormalities (3 papers) and Phytochemicals and Medicinal Plants (3 papers). Uma Chandran is often cited by papers focused on Sperm and Testicular Function (4 papers), Genetic and Clinical Aspects of Sex Determination and Chromosomal Abnormalities (3 papers) and Phytochemicals and Medicinal Plants (3 papers). Uma Chandran collaborates with scholars based in India, United States and Argentina. Uma Chandran's co-authors include Bhushan Patwardhan, Robert W. Sobol, Bo Hu, Sung-Hak Kim, Soumya Luthra, Peipei Li, L.T. Smith, Ping Mao, Kaushal Joshi and Jianfeng Li and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Hepatology and Human Reproduction.

In The Last Decade

Uma Chandran

11 papers receiving 709 citations

Hit Papers

Mesenchymal glioma stem cells are maintained by activated... 2013 2026 2017 2021 2013 100 200 300 400 500

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Uma Chandran India 9 347 273 203 184 78 11 718
Sushmita Nandy United States 16 477 1.4× 233 0.9× 60 0.3× 235 1.3× 19 0.2× 24 830
Xu Zheng China 19 516 1.5× 99 0.4× 49 0.2× 166 0.9× 50 0.6× 50 924
Santiago Díaz‐Moralli Spain 10 445 1.3× 222 0.8× 57 0.3× 139 0.8× 15 0.2× 11 679
Ya-Ming Xu United States 13 416 1.2× 64 0.2× 25 0.1× 128 0.7× 77 1.0× 31 623
Yingqiu Zhang China 15 487 1.4× 139 0.5× 27 0.1× 225 1.2× 17 0.2× 31 772
Ying Cheng China 13 346 1.0× 70 0.3× 24 0.1× 127 0.7× 20 0.3× 33 716
Ae Jin Jeong South Korea 10 308 0.9× 106 0.4× 20 0.1× 168 0.9× 26 0.3× 19 586

Countries citing papers authored by Uma Chandran

Since Specialization
Citations

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

Fields of papers citing papers by Uma Chandran

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Uma Chandran

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

All Works

11 of 11 papers shown
1.
2.
Ramaswamy, Suresh, William H. Walker, Gary R. Marshall, et al.. (2017). The testicular transcriptome associated with spermatogonia differentiation initiated by gonadotrophin stimulation in the juvenile rhesus monkey (Macaca mulatta). Human Reproduction. 32(10). 2088–2100. 17 indexed citations
3.
Chandran, Uma & Bhushan Patwardhan. (2016). Network ethnopharmacological evaluation of the immunomodulatory activity of Withania somnifera. Journal of Ethnopharmacology. 197. 250–256. 71 indexed citations
4.
Chandran, Uma, et al.. (2016). Expression of Cnnm1 and Its Association with Stemness, Cell Cycle, and Differentiation in Spermatogenic Cells in Mouse Testis. Biology of Reproduction. 95(1). 7–7. 13 indexed citations
5.
Chandran, Uma. (2015). Network pharmacology: An emerging tool for natural product drug discovery and evidence-based Ayurveda. Revista de Fomento Social. 81(3). 9 indexed citations
6.
Chandran, Uma, et al.. (2015). Network Pharmacology of Ayurveda Formulation <i>Triphala</i> with Special Reference to Anti-Cancer Property. Combinatorial Chemistry & High Throughput Screening. 18(9). 846–854. 62 indexed citations
7.
Patwardhan, Bhushan & Uma Chandran. (2015). Network Ethnopharmacology Approaches for Formulation discovery. 8 indexed citations
8.
Chandran, Uma, et al.. (2014). Aberrant expression of TAR DNA binding protein-43 is associated with spermatogenic disorders in men. Reproduction Fertility and Development. 28(6). 713–722. 10 indexed citations
9.
Mao, Ping, Kaushal Joshi, Jianfeng Li, et al.. (2013). Mesenchymal glioma stem cells are maintained by activated glycolytic metabolism involving aldehyde dehydrogenase 1A3. Proceedings of the National Academy of Sciences. 110(21). 8644–8649. 501 indexed citations breakdown →
10.
Manohar, Rohan, Junji Komori, Donna B. Stolz, et al.. (2011). Identification and expansion of a unique stem cell population from adult mouse gallbladder. Hepatology. 54(5). 1830–1841. 15 indexed citations
11.
Chandran, Uma, Malini Laloraya, & Pradeep G. Kumar. (2007). Identification of Testis-Expressed Cell Cycle Regulating Proteins with Special Reference to Meiosis. 11(1). 45–48. 2 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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