Vivek Tanavde

3.3k total citations
50 papers, 2.5k citations indexed

About

Vivek Tanavde is a scholar working on Molecular Biology, Genetics and Cancer Research. According to data from OpenAlex, Vivek Tanavde has authored 50 papers receiving a total of 2.5k indexed citations (citations by other indexed papers that have themselves been cited), including 31 papers in Molecular Biology, 14 papers in Genetics and 14 papers in Cancer Research. Recurrent topics in Vivek Tanavde's work include Mesenchymal stem cell research (14 papers), Tissue Engineering and Regenerative Medicine (10 papers) and MicroRNA in disease regulation (9 papers). Vivek Tanavde is often cited by papers focused on Mesenchymal stem cell research (14 papers), Tissue Engineering and Regenerative Medicine (10 papers) and MicroRNA in disease regulation (9 papers). Vivek Tanavde collaborates with scholars based in Singapore, India and United States. Vivek Tanavde's co-authors include Candida Vaz, Uma Lakshmipathy, Mohan C. Vemuri, Mahendra S. Rao, Cleo Choong, Betty Tan, Felicia Ng, Shayne Boucher, Zheng Yang and Lucas G. Chase and has published in prestigious journals such as Nature, Proceedings of the National Academy of Sciences and The Journal of Experimental Medicine.

In The Last Decade

Vivek Tanavde

50 papers receiving 2.4k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Vivek Tanavde Singapore 25 1.3k 583 544 372 254 50 2.5k
Anto De Pol Italy 34 1.3k 1.0× 672 1.2× 229 0.4× 570 1.5× 295 1.2× 90 2.8k
Laura F. Gibson United States 25 989 0.8× 805 1.4× 252 0.5× 341 0.9× 479 1.9× 70 2.6k
Paweł Włodarski Poland 32 1.4k 1.1× 445 0.8× 468 0.9× 311 0.8× 671 2.6× 193 3.2k
María P. De Miguel Spain 31 1.1k 0.9× 597 1.0× 227 0.4× 559 1.5× 250 1.0× 101 3.1k
Trine Fink Denmark 31 869 0.7× 958 1.6× 361 0.7× 653 1.8× 155 0.6× 79 2.3k
Seunghee Lee South Korea 23 1.5k 1.2× 731 1.3× 598 1.1× 391 1.1× 237 0.9× 41 2.6k
Darrell H. Carney United States 36 1.4k 1.1× 467 0.8× 655 1.2× 462 1.2× 457 1.8× 77 3.7k
Christian Ries Germany 29 911 0.7× 543 0.9× 741 1.4× 984 2.6× 512 2.0× 123 3.0k
Il‐Hoan Oh South Korea 28 1.3k 1.0× 904 1.6× 304 0.6× 365 1.0× 536 2.1× 90 2.8k
Bent Brachvogel Germany 29 1.6k 1.3× 281 0.5× 436 0.8× 354 1.0× 258 1.0× 83 3.5k

Countries citing papers authored by Vivek Tanavde

Since Specialization
Citations

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

Fields of papers citing papers by Vivek Tanavde

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Vivek Tanavde

This figure shows the co-authorship network connecting the top 25 collaborators of Vivek Tanavde. A scholar is included among the top collaborators of Vivek Tanavde 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 Vivek Tanavde. Vivek Tanavde 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.
Patel, Shanaya, et al.. (2024). Unravelling the role of Silibinin in targeting CD44+ cancer stem cells: Therapeutic implications, effective strategies and approaches. Phytotherapy Research. 38(4). 1830–1837. 3 indexed citations
2.
Patel, Shanaya, et al.. (2024). Combination of paclitaxel with rosiglitazone induces synergistic cytotoxic effects in ovarian cancer cells. Scientific Reports. 14(1). 30672–30672. 2 indexed citations
3.
Patel, Shanaya, et al.. (2022). Saliva Based Liquid Biopsies in Head and Neck Cancer: How Far Are We From the Clinic?. Frontiers in Oncology. 12. 828434–828434. 45 indexed citations
4.
5.
Taye, Biruhalem, Candida Vaz, Vivek Tanavde, et al.. (2017). Benchmarking selected computational gene network growing tools in context of virus-host interactions. Scientific Reports. 7(1). 11 indexed citations
6.
Sundaram, Gopinath M., Mohsin Bashir, Manish Muhuri, et al.. (2017). EGF hijacks miR-198/FSTL1 wound-healing switch and steers a two-pronged pathway toward metastasis. The Journal of Experimental Medicine. 214(10). 2889–2900. 53 indexed citations
7.
8.
Tan, Nguan Soon, et al.. (2016). Comparative study of adipose-derived stem cells and bone marrow-derived stem cells in similar microenvironmental conditions. Experimental Cell Research. 348(2). 155–164. 26 indexed citations
9.
Vaz, Candida, et al.. (2015). Deep sequencing of small RNA facilitates tissue and sex associated microRNA discovery in zebrafish. BMC Genomics. 16(1). 950–950. 22 indexed citations
10.
Tanavde, Vivek, Candida Vaz, Mahendra S. Rao, Mohan C. Vemuri, & Radhika Pochampally. (2015). Research using Mesenchymal Stem/Stromal Cells: quality metric towards developing a reference material. Cytotherapy. 17(9). 1169–1177. 32 indexed citations
11.
Sundaram, Gopinath M., John Common, Declan P. Lunny, et al.. (2013). ‘See-saw’ expression of microRNA-198 and FSTL1 from a single transcript in wound healing. Nature. 495(7439). 103–106. 171 indexed citations
12.
Nama, Srikanth, Pamela Rizk, Srinivas Ramasamy, et al.. (2012). Targeting Glioma Stem Cells by Functional Inhibition of a Prosurvival OncomiR-138 in Malignant Gliomas. Cell Reports. 2(3). 591–602. 84 indexed citations
13.
Zhou, Lei, Shao Zhao, Siew Kwan Koh, et al.. (2012). In-depth analysis of the human tear proteome. Journal of Proteomics. 75(13). 3877–3885. 269 indexed citations
14.
Lai, Ruenn Chai, Fatih Arslan, Soon Sim Tan, et al.. (2010). Derivation and characterization of human fetal MSCs: An alternative cell source for large-scale production of cardioprotective microparticles. Journal of Molecular and Cellular Cardiology. 48(6). 1215–1224. 119 indexed citations
15.
Zimmer, Bastian, Andreas Genewsky, Vivek Tanavde, et al.. (2010). Coordinated waves of gene expression during neuronal differentiation of embryonic stem cells as basis for novel approaches to developmental neurotoxicity testing. Cell Death and Differentiation. 18(3). 383–395. 81 indexed citations
16.
Saleh, Amyza, Rosnah Binti Zain, Haizal Mohd Hussaini, et al.. (2010). Transcriptional profiling of oral squamous cell carcinoma using formalin-fixed paraffin-embedded samples. Oral Oncology. 46(5). 379–386. 29 indexed citations
17.
Tanavde, Vivek, et al.. (2007). Towards A Serum-Free Medium: Growth Receptors And Signaling Pathways That Regulate Multipotency In Human Mesenchymal Stem Cells. World Congress on Engineering. 1460–1465. 1 indexed citations
18.
Shetty, Prasanna Kumar, et al.. (2006). Human umbilical cord blood serum can replace fetal bovine serum in the culture of mesenchymal stem cells. Cell Biology International. 31(3). 293–298. 76 indexed citations
19.
Tanavde, Vivek, Matthew Malehorn, Zhigang Gao, et al.. (2002). Human stem-progenitor cells from neonatal cord blood have greater hematopoietic expansion capacity than those from mobilized adult blood. Experimental Hematology. 30(7). 816–823. 65 indexed citations
20.
Rao, S., et al.. (1996). AN ICAM‐1 LIKE CELL ADHESION MOLECULE IS RESPONSIBLE FOR CD34 POSITIVE HAEMOPOIETIC STEM CELLS ADHESION TO BONE‐MARROW STROMA. Cell Biology International. 20(4). 255–259. 11 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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