Madhavi Tadi

3.2k total citations · 1 hit paper
7 papers, 1.0k citations indexed

About

Madhavi Tadi is a scholar working on Molecular Biology, Oncology and Computational Theory and Mathematics. According to data from OpenAlex, Madhavi Tadi has authored 7 papers receiving a total of 1.0k indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Molecular Biology, 3 papers in Oncology and 2 papers in Computational Theory and Mathematics. Recurrent topics in Madhavi Tadi's work include Computational Drug Discovery Methods (2 papers), Epigenetics and DNA Methylation (2 papers) and T-cell and B-cell Immunology (2 papers). Madhavi Tadi is often cited by papers focused on Computational Drug Discovery Methods (2 papers), Epigenetics and DNA Methylation (2 papers) and T-cell and B-cell Immunology (2 papers). Madhavi Tadi collaborates with scholars based in United States and Russia. Madhavi Tadi's co-authors include Christine A. Pratilas, Ensar Halilovic, Eric W. Joseph, Poulikos I. Poulikakos, Neal Rosen, James A. Fagin, Sarat Chandarlapaty, Taha Merghoub, Elisa de Stanchina and Wai Lin Wong and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Clinical Investigation and The Journal of Immunology.

In The Last Decade

Madhavi Tadi

7 papers receiving 1.0k citations

Hit Papers

Relief of Profound Feedback Inhibition of Mitogenic Signa... 2012 2026 2016 2021 2012 100 200 300 400

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Madhavi Tadi United States 7 849 429 175 138 96 7 1.0k
Allison Marlow United States 3 724 0.9× 447 1.0× 166 0.9× 98 0.7× 44 0.5× 3 946
Carla Milagre United Kingdom 6 1.1k 1.3× 712 1.7× 204 1.2× 224 1.6× 150 1.6× 8 1.4k
Charles Ng United States 10 962 1.1× 658 1.5× 177 1.0× 195 1.4× 151 1.6× 11 1.2k
Jahan Hussain United Kingdom 3 1.0k 1.2× 609 1.4× 203 1.2× 227 1.6× 76 0.8× 3 1.2k
Eric W. Joseph United States 7 964 1.1× 516 1.2× 260 1.5× 179 1.3× 60 0.6× 9 1.2k
Andrew E. Aplin United States 15 604 0.7× 363 0.8× 91 0.5× 104 0.8× 106 1.1× 22 722
Maureen R. Bleam United States 6 862 1.0× 548 1.3× 154 0.9× 166 1.2× 63 0.7× 13 1.1k
Patrícia Volpe United States 4 963 1.1× 639 1.5× 157 0.9× 108 0.8× 156 1.6× 6 1.3k
Tammie C. Yeh United States 11 614 0.7× 503 1.2× 115 0.7× 56 0.4× 116 1.2× 21 1.0k
Kimberly N. Smitheman United States 11 856 1.0× 345 0.8× 112 0.6× 153 1.1× 67 0.7× 11 1.0k

Countries citing papers authored by Madhavi Tadi

Since Specialization
Citations

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

Fields of papers citing papers by Madhavi Tadi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Madhavi Tadi

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

All Works

7 of 7 papers shown
1.
Ge, Cheng, Takashi Asai, Fan Lai, et al.. (2016). Loss of p300 accelerates MDS-associated leukemogenesis. Leukemia. 31(6). 1382–1390. 28 indexed citations
2.
Liu, Fan, Guoyan Cheng, Pierre-Jacques Hamard, et al.. (2015). Arginine methyltransferase PRMT5 is essential for sustaining normal adult hematopoiesis. Journal of Clinical Investigation. 125(9). 3532–3544. 106 indexed citations
3.
Ambrosini, Grazia, Christine A. Pratilas, Li-Xuan Qin, et al.. (2012). Identification of Unique MEK-Dependent Genes in GNAQ Mutant Uveal Melanoma Involved in Cell Growth, Tumor Cell Invasion, and MEK Resistance. Clinical Cancer Research. 18(13). 3552–3561. 78 indexed citations
4.
Lito, Piro, Christine A. Pratilas, Eric W. Joseph, et al.. (2012). Relief of Profound Feedback Inhibition of Mitogenic Signaling by RAF Inhibitors Attenuates Their Activity in BRAFV600E Melanomas. Cancer Cell. 22(5). 668–682. 410 indexed citations breakdown →
5.
Joseph, Eric W., Christine A. Pratilas, Poulikos I. Poulikakos, et al.. (2010). The RAF inhibitor PLX4032 inhibits ERK signaling and tumor cell proliferation in a V600E BRAF-selective manner. Proceedings of the National Academy of Sciences. 107(33). 14903–14908. 349 indexed citations
6.
Kumar, Ashok, Kimberly N. Kremer, Daniel Domínguez, Madhavi Tadi, & Karen E. Hedin. (2010). Gα13 and Rho Mediate Endosomal Trafficking of CXCR4 into Rab11+ Vesicles upon Stromal Cell-Derived Factor-1 Stimulation. The Journal of Immunology. 186(2). 951–958. 47 indexed citations
7.
Eldredge, John, Steven A. Berkowitz, Eric S. Day, et al.. (2006). Stoichiometry of LTβR Binding to LIGHT. Biochemistry. 45(33). 10117–10128. 15 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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