Suman Sirimulla

1.5k citations
23 papers · 1.1k indexed · h-index 16
Topics
Computational Drug Discovery Methods (7 papers)Crystallography and molecular interactions (4 papers)Pharmacogenetics and Drug Metabolism (3 papers)

In The Last Decade

Suman Sirimulla

22 papers receiving 1.1k citations

Peers

Suman Sirimulla
Comparison fields: 5 of 117
  • Molecular Biology 495
  • Computational Theory and Mathematics 251
  • Physical and Theoretical Chemistry 209
  • Organic Chemistry 206
  • Materials Chemistry 125
Replace Zhengdan Zhu with:
Zhengdan Zhu China
Peter W. Kenny United Kingdom
Joachim Diez Switzerland
Scott D. Kahn United States
Andreas H. Göller Germany
Carlos Maurício R. Sant’Anna Brazil
Christopher R. Jones United Kingdom
Zhaoqiang Chen China
Vikas Sharma India
Alexei V. Buevich United States
Suman Sirimulla relative to Zhengdan Zhu China Zhengdan Zhu's profile →
Citations per field
00.5×10×20×30×39×
Zhengdan Zhu · 1×
Citations per year

Countries citing papers authored by Suman Sirimulla

Since Specialization
Citations

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

Fields of papers citing papers by Suman Sirimulla

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Suman Sirimulla

This figure shows the co-authorship network connecting the top 25 collaborators of Suman Sirimulla. A scholar is included among the top collaborators of Suman Sirimulla 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 Suman Sirimulla. Suman Sirimulla 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
#WorkIndexed citations
1 0
2 48
3 8
4 9
5 126
6 63
7 48
8 5
9 16
10 23
11 116
12 42
13 53
14 24
15 207
16 26
17 5
18 28
19 3
20 17

About Suman Sirimulla

Suman Sirimulla is a scholar working on Physical and Theoretical Chemistry, Computational Theory and Mathematics and Pharmacology, having authored 23 papers that have together received 1.1k indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (7 papers), Crystallography and molecular interactions (4 papers) and Pharmacogenetics and Drug Metabolism (3 papers). The work is most often cited by research in Physical and Theoretical Chemistry (209 citations), Computational Theory and Mathematics (251 citations) and Toxicology (37 citations). Suman Sirimulla has collaborated with scholars based in United States, Sweden and Denmark. Frequent co-authors include Mahesh Narayan, Jake Bailey, Rahulsimham Vegesna, Gabriela Henrı́quez, Richard G. Posner, F. Fratev, Tudor I. Oprea, Jeremy J. Yang, Jayme Holmes and Giovanni Bocci. Their work appears in journals such as Nucleic Acids Research, Bioinformatics and Cancer Research.

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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