Uma Kota

1.0k total citations · 1 hit paper
8 papers, 762 citations indexed

About

Uma Kota is a scholar working on Molecular Biology, Spectroscopy and Plant Science. According to data from OpenAlex, Uma Kota has authored 8 papers receiving a total of 762 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Molecular Biology, 4 papers in Spectroscopy and 3 papers in Plant Science. Recurrent topics in Uma Kota's work include Advanced Proteomics Techniques and Applications (4 papers), Mass Spectrometry Techniques and Applications (4 papers) and Plant Molecular Biology Research (2 papers). Uma Kota is often cited by papers focused on Advanced Proteomics Techniques and Applications (4 papers), Mass Spectrometry Techniques and Applications (4 papers) and Plant Molecular Biology Research (2 papers). Uma Kota collaborates with scholars based in United States. Uma Kota's co-authors include Michael B. Goshe, Xiaofeng Wang, Steven C. Huber, Steven D. Clouse, Kai He, Jia Li, Kevin Blackburn, Man‐Ho Oh, Erik J. Soderblom and Rafaelo M. Galvão and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Biochemical Journal and The Plant Journal.

In The Last Decade

Uma Kota

8 papers receiving 755 citations

Hit Papers

Sequential Transphosphorylation of the BRI1/BAK1 Receptor... 2008 2026 2014 2020 2008 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
Uma Kota United States 7 667 475 41 33 11 8 762
Clayton T. Larue United States 7 556 0.8× 543 1.1× 35 0.9× 33 1.0× 18 1.6× 8 751
Katy M. Christiansen United States 7 357 0.5× 266 0.6× 21 0.5× 56 1.7× 20 1.8× 8 482
Yaxing Li China 11 286 0.4× 410 0.9× 21 0.5× 19 0.6× 12 1.1× 25 542
Mathias Madalinski Austria 6 300 0.4× 206 0.4× 50 1.2× 24 0.7× 4 0.4× 7 392
Carine Alcon France 4 233 0.3× 219 0.5× 48 1.2× 33 1.0× 13 1.2× 4 352
Tian-Cong Lu China 14 500 0.7× 542 1.1× 27 0.7× 14 0.4× 23 2.1× 16 715
Jian‐Xiu Shang China 8 736 1.1× 486 1.0× 10 0.2× 21 0.6× 8 0.7× 16 836
Hilde Stals Belgium 10 585 0.9× 563 1.2× 30 0.7× 123 3.7× 9 0.8× 12 766
Aneta Liwosz United States 6 381 0.6× 372 0.8× 11 0.3× 48 1.5× 6 0.5× 7 546
Angela Dietzmann Germany 7 299 0.4× 490 1.0× 20 0.5× 12 0.4× 33 3.0× 8 553

Countries citing papers authored by Uma Kota

Since Specialization
Citations

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

Fields of papers citing papers by Uma Kota

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Uma Kota

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

All Works

8 of 8 papers shown
1.
Kota, Uma & Mark L. Stolowitz. (2016). Improving Proteome Coverage by Reducing Sample Complexity via Chromatography. Advances in experimental medicine and biology. 919. 83–143. 7 indexed citations
2.
Ven, Stephanie M.W.Y. van de, Kenneth Lau, Ravali Adusumilli, et al.. (2016). Protein biomarkers on tissue as imaged via MALDI mass spectrometry: A systematic approach to study the limits of detection. PROTEOMICS. 16(11-12). 1660–1669. 11 indexed citations
3.
Chen, Ruiqiang, Xiaofeng Wang, Uma Kota, et al.. (2015). An autophosphorylation site database for leucine‐rich repeat receptor‐like kinases in Arabidopsis thaliana. The Plant Journal. 82(6). 1042–1060. 31 indexed citations
4.
Kota, Uma & Michael B. Goshe. (2011). Advances in qualitative and quantitative plant membrane proteomics. Phytochemistry. 72(10). 1040–1060. 27 indexed citations
5.
Oh, Man‐Ho, Xiaofeng Wang, Uma Kota, et al.. (2009). Tyrosine phosphorylation of the BRI1 receptor kinase emerges as a component of brassinosteroid signaling in Arabidopsis. Proceedings of the National Academy of Sciences. 106(2). 658–663. 205 indexed citations
6.
Kota, Uma, et al.. (2009). Isotope-Labeling and Affinity Enrichment of Phosphopeptides for Proteomic Analysis Using Liquid Chromatography-Tandem Mass Spectrometry. Methods in molecular biology. 564. 303–321. 3 indexed citations
7.
Wang, Xiaofeng, Uma Kota, Kai He, et al.. (2008). Sequential Transphosphorylation of the BRI1/BAK1 Receptor Kinase Complex Impacts Early Events in Brassinosteroid Signaling. Developmental Cell. 15(2). 220–235. 443 indexed citations breakdown →
8.
Galvão, Rafaelo M., Uma Kota, Erik J. Soderblom, Michael B. Goshe, & Wendy F. Boss. (2007). Characterization of a new family of protein kinases from Arabidopsis containing phosphoinositide 3/4-kinase and ubiquitin-like domains. Biochemical Journal. 409(1). 117–127. 35 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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