Manikanta Murahari

1.6k citations
51 papers · 1.2k indexed · h-index 23

Manikanta Murahari

49 papers receiving 1.2k citations

Peers

Manikanta Murahari
Comparison fields: 5 of 106
  • Pharmaceutical Science 140
  • Computational Theory and Mathematics 270
  • Organic Chemistry 334
  • Pharmacology 94
  • Toxicology 29
Replace Prashant S. Kharkar with:
Prashant S. Kharkar India
Ilza Pajeva Bulgaria
D.N. Prasad India
Sisir Nandi India
Mahmoud A. El Hassab Egypt
Gopal L. Khatik India
Ivanka Tsakovska Bulgaria
Eszter Hazai Hungary
Aakash Deep India
Jubie Selvaraj India
Manikanta Murahari relative to Prashant S. Kharkar India Prashant S. Kharkar's profile →
Citations per field
00.5×2.7×
Prashant S. Kharkar · 1×
Citations per year

Countries citing papers authored by Manikanta Murahari

Since Specialization
Citations

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

Fields of papers citing papers by Manikanta Murahari

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 25 scholars most cited alongside Manikanta Murahari, 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 Manikanta Murahari Line = papers co-authored together Manikanta Murahari links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20251
2 20242
3 20241
4 20238
5 202310
6 20235
7 20239
8 20224
9 20215
10 20218
11 202122
12 202113
13 202015
14 2020122
15 202024
16 2018118
17 201728
18 201782
19 201747
20 201321

About Manikanta Murahari

Manikanta Murahari is a scholar working on Computational Theory and Mathematics, Pharmaceutical Science and Organic Chemistry, having authored 51 papers that have together received 1.2k indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (19 papers), Synthesis and biological activity (11 papers), Cancer therapeutics and mechanisms (9 papers), Drug Solubulity and Delivery Systems (6 papers), Cell death mechanisms and regulation (5 papers), Crystallization and Solubility Studies (5 papers), Tuberculosis Research and Epidemiology (4 papers) and Cholinesterase and Neurodegenerative Diseases (4 papers). The work is most often cited by research in Pharmaceutical Science (140 citations), Computational Theory and Mathematics (270 citations) and Organic Chemistry (334 citations). Manikanta Murahari has collaborated with scholars based in India, Türkiye and Netherlands. Frequent co-authors include Vasanti Suvarna, Vasanti Suvarna, Vivek Chandramohan, Atul P. Sherje, DSNBK Prasanth, A. Lakshmana Rao, Ercan Bursal, Fikret Türkan, Siva Prasad Panda and Mayur C. Yergeri. Their work appears in journals such as Journal of Biomolecular Structure and Dynamics, Journal of Drug Delivery Science and Technology, European Journal of Medicinal Chemistry, Journal of Molecular Graphics and Modelling and Journal of Molecular Liquids.

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.

Explore authors with similar magnitude of impact

Rankless by CCL
2026