Ruchira S. Datta

1.5k citations
14 papers · 959 indexed · 1 hit paper · h-index 9
Topics
Genomics and Phylogenetic Studies (5 papers)Polynomial and algebraic computation (3 papers)Machine Learning in Bioinformatics (2 papers)

In The Last Decade

Ruchira S. Datta

13 papers receiving 934 citations

Hit Papers

ModBase, a database of annotated comparative protein stru...20102026201520202010200400600

Peers

Ruchira S. Datta
Comparison fields: 5 of 126
  • Molecular Biology 669
  • Computational Theory and Mathematics 110
  • Genetics 107
  • Materials Chemistry 106
  • Cancer Research 69
Replace Mehdi Sadeghi with:
Mehdi Sadeghi Iran
Miguel Ángel Gutiérrez Andrade Mexico
Andrew Krueger United States
Andrzej Kierzek Poland
Brett G. Olivier Netherlands
Vladimir Gligorijević United States
Kumar Selvarajoo Singapore
Sanne Abeln Netherlands
Ginger Tsueng United States
Dongbo Bu China
Ruchira S. Datta relative to Mehdi Sadeghi Iran Mehdi Sadeghi's profile →
Citations per field
00.5×1.5×
Mehdi Sadeghi · 1×
Citations per year

Countries citing papers authored by Ruchira S. Datta

Since Specialization
Citations

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

Fields of papers citing papers by Ruchira S. Datta

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ruchira S. Datta. 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 Ruchira S. Datta. The network helps show where Ruchira S. Datta may publish in the future.

Co-authorship network of co-authors of Ruchira S. Datta

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

All Works

14 of 14 papers shown
#WorkIndexed citations
1 74
2 1
3 32
4 20
5 2
6 3
7 0
8 22
9 5
10
ModBase, a database of annotated comparative protein structure models, and associated resourcesbreakdown →
672
11 53
12 36
13 14
14 25

About Ruchira S. Datta

Ruchira S. Datta is a scholar working on Geometry and Topology, Modeling and Simulation and Computational Theory and Mathematics, having authored 14 papers that have together received 959 indexed citations. Recurring topics across this work include Genomics and Phylogenetic Studies (5 papers), Polynomial and algebraic computation (3 papers) and Machine Learning in Bioinformatics (2 papers). The work is most often cited by research in Molecular Biology (669 citations), Computational Theory and Mathematics (110 citations) and Cancer Research (69 citations). Ruchira S. Datta has collaborated with scholars based in United States, United Kingdom and Germany. Frequent co-authors include Kimmen Sjölander, Ursula Pieper, Thomas E. Ferrin, Benjamin Webb, M. S. Madhusudhan, Avner Schlessinger, David T. Barkan, S.K. Burley, Andrej Săli and P. Sampathkumar. Their work appears in journals such as Nucleic Acids Research, Journal of Medicinal Chemistry and PLoS Computational Biology.

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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