Munikumar Reddy Doddareddy

1.1k citations
37 papers · 989 · h-index 22

Impact in

Papers in

Munikumar Reddy Doddareddy

37 papers receiving 947 citations

Peers

Munikumar Reddy Doddareddy
Comparison fields: 5 of 84
  • Computational Theory and Mathematics 219
  • Organic Chemistry 305
  • Molecular Biology 569
  • Pharmacology 69
  • Pharmaceutical Science 50
Replace James R. Tata with:
James R. Tata United States
Éric Therrien Canada
Nam Sook Kang South Korea
Yong Seo Cho South Korea
Danfeng Shi China
Andreas Evers Germany
Christopher Fotsch United States
Susanna Nencetti Italy
Bryan H. Norman United States
Daniela Pizzirani Italy
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Citations per field
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Citations per year

Countries citing papers authored by Munikumar Reddy Doddareddy

Since Specialization
Citations

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

Fields of papers citing papers by Munikumar Reddy Doddareddy

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Munikumar Reddy Doddareddy. 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 Munikumar Reddy Doddareddy. The network helps show where Munikumar Reddy Doddareddy may publish in the future.

Co-authors

The 25 scholars most cited alongside Munikumar Reddy Doddareddy, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Munikumar Reddy Doddareddy Line = papers co-authored together Munikumar Reddy Doddareddy links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 37 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201086
2 201086
3 201155
4 201252
5 200747
6 200437
7 200636
8 201235
9 200634
10 200634
11 200433
12 200432
13 200431
14 200931
15 201629
16 201529
17 200628
18 200628
19 201227
20 201526

About Munikumar Reddy Doddareddy

Munikumar Reddy Doddareddy is a scholar working on Molecular Biology, Computational Theory and Mathematics, Organic Chemistry, Oncology and Spectroscopy, having authored 37 papers that have together received 989 indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (13 papers), Receptor Mechanisms and Signaling (11 papers), Pharmacological Receptor Mechanisms and Effects (6 papers), Nicotinic Acetylcholine Receptors Study (5 papers), Ion channel regulation and function (4 papers), Neuroscience and Neuropharmacology Research (3 papers), Synthesis and biological activity (3 papers) and Cardiac electrophysiology and arrhythmias (2 papers). The work is most often cited by research in Computational Theory and Mathematics (219 citations), Organic Chemistry (305 citations), Molecular Biology (569 citations), Pharmacology (69 citations) and Pharmaceutical Science (50 citations). Munikumar Reddy Doddareddy has collaborated with scholars based in South Korea, Australia and Netherlands. Frequent co-authors include Yong Seo Cho, Ae Nim Pae, Hun Yeong Koh, Adriaan P. IJzerman, David E. Hibbs, Tristan Rawling, Hyunah Choo, Andreas Bender, Rajeshwar Narlawar and Elisabeth Klaasse. Their work appears in journals such as Bioorganic & Medicinal Chemistry, Bioorganic & Medicinal Chemistry Letters, Journal of Medicinal Chemistry, Journal of Chemical Information and Modeling and Journal of Molecular Modeling.

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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