Prasit Mandi

686 total citations
16 papers, 558 citations indexed

About

Prasit Mandi is a scholar working on Organic Chemistry, Computational Theory and Mathematics and Molecular Biology. According to data from OpenAlex, Prasit Mandi has authored 16 papers receiving a total of 558 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Organic Chemistry, 8 papers in Computational Theory and Mathematics and 7 papers in Molecular Biology. Recurrent topics in Prasit Mandi's work include Synthesis and biological activity (8 papers), Computational Drug Discovery Methods (8 papers) and Click Chemistry and Applications (5 papers). Prasit Mandi is often cited by papers focused on Synthesis and biological activity (8 papers), Computational Drug Discovery Methods (8 papers) and Click Chemistry and Applications (5 papers). Prasit Mandi collaborates with scholars based in Thailand, Sweden and Italy. Prasit Mandi's co-authors include Chanin Nantasenamat, Virapong Prachayasittikul, Supaluk Prachayasittikul, Ratchanok Pingaew, Somsak Ruchirawat, Veda Prachayasittikul, Apilak Worachartcheewan, Chartchalerm Isarankura‐Na‐Ayudhya, Somsak Ruchirawat and Andrey A. Toropov and has published in prestigious journals such as European Journal of Medicinal Chemistry, Bioorganic & Medicinal Chemistry and Chemometrics and Intelligent Laboratory Systems.

In The Last Decade

Prasit Mandi

14 papers receiving 544 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Prasit Mandi Thailand 11 362 160 149 63 59 16 558
Jaime Mella Chile 18 338 0.9× 262 1.6× 144 1.0× 124 2.0× 26 0.4× 56 661
Anja Palusczak Germany 10 236 0.7× 176 1.1× 93 0.6× 86 1.4× 168 2.8× 19 505
Barkın Berk Türkiye 13 251 0.7× 219 1.4× 123 0.8× 92 1.5× 17 0.3× 49 493
Muriel Duflos France 15 501 1.4× 202 1.3× 48 0.3× 96 1.5× 73 1.2× 48 732
Santosh N. Mokale India 15 340 0.9× 195 1.2× 93 0.6× 68 1.1× 18 0.3× 52 622
Naina Sharma India 13 299 0.8× 110 0.7× 34 0.2× 43 0.7× 29 0.5× 27 484
Sanna Niinivehmas Finland 13 123 0.3× 286 1.8× 205 1.4× 74 1.2× 43 0.7× 22 517
Pascal Marchand France 19 731 2.0× 305 1.9× 63 0.4× 92 1.5× 104 1.8× 67 1.1k
Süreyya Ölgen Türkiye 21 532 1.5× 341 2.1× 71 0.5× 90 1.4× 46 0.8× 67 921
María Gálvez-Llompart Spain 14 197 0.5× 224 1.4× 283 1.9× 52 0.8× 25 0.4× 47 517

Countries citing papers authored by Prasit Mandi

Since Specialization
Citations

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

Fields of papers citing papers by Prasit Mandi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Prasit Mandi

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

All Works

16 of 16 papers shown
1.
Prachayasittikul, Veda, Prasit Mandi, Ratchanok Pingaew, et al.. (2025). Substituted 1,4-naphthoquinones for potential anticancer therapeutics: In vitro cytotoxic effects and QSAR-guided design of new analogs. Computational and Structural Biotechnology Journal. 27. 3492–3509. 1 indexed citations
2.
Mahalapbutr, Panupong, Veda Prachayasittikul, Prasit Mandi, et al.. (2025). Design, Synthesis, Biological Evaluation and Molecular Modeling Studies of Novel Naphthoquinone‐Triazole Hybrids as Potential FGFR1 Tyrosine Kinase Inhibitors. Asian Journal of Organic Chemistry. 14(5).
3.
Pingaew, Ratchanok, Prasit Mandi, Veda Prachayasittikul, et al.. (2021). Investigations on Anticancer and Antimalarial Activities of Indole-Sulfonamide Derivatives and In Silico Studies. ACS Omega. 6(47). 31854–31868. 30 indexed citations
4.
Pingaew, Ratchanok, et al.. (2017). Synthesis, molecular docking, and QSAR study of sulfonamide-based indoles as aromatase inhibitors. European Journal of Medicinal Chemistry. 143. 1604–1615. 54 indexed citations
5.
Prachayasittikul, Veda, Prasit Mandi, Supaluk Prachayasittikul, Virapong Prachayasittikul, & Chanin Nantasenamat. (2017). Exploring the Chemical Space of P-Glycoprotein Interacting Compounds. Mini-Reviews in Medicinal Chemistry. 17(14). 1332–1345. 8 indexed citations
6.
Pingaew, Ratchanok, Nujarin Sinthupoom, Prasit Mandi, et al.. (2017). Synthesis, biological evaluation and in silico study of bis-thiourea derivatives as anticancer, antimalarial and antimicrobial agents. Medicinal Chemistry Research. 26(12). 3136–3148. 28 indexed citations
7.
Pingaew, Ratchanok, Veda Prachayasittikul, Prasit Mandi, et al.. (2015). Synthesis and molecular docking of 1,2,3-triazole-based sulfonamides as aromatase inhibitors. Bioorganic & Medicinal Chemistry. 23(13). 3472–3480. 65 indexed citations
8.
Worachartcheewan, Apilak, Prasit Mandi, Virapong Prachayasittikul, et al.. (2014). Large-scale QSAR study of aromatase inhibitors using SMILES-based descriptors. Chemometrics and Intelligent Laboratory Systems. 138. 120–126. 43 indexed citations
9.
Nantasenamat, Chanin, et al.. (2014). Predictive QSAR modeling of aldose reductase inhibitors using Monte Carlo feature selection. European Journal of Medicinal Chemistry. 76. 352–359. 24 indexed citations
10.
Pingaew, Ratchanok, Prasit Mandi, Chanin Nantasenamat, et al.. (2014). Synthesis, biological evaluation and molecular docking of novel chalcone–coumarin hybrids as anticancer and antimalarial agents. European Journal of Medicinal Chemistry. 85. 65–76. 180 indexed citations
11.
Pingaew, Ratchanok, Prasit Mandi, Chanin Nantasenamat, et al.. (2014). Design, synthesis and molecular docking studies of novel N-benzenesulfonyl-1,2,3,4-tetrahydroisoquinoline-based triazoles with potential anticancer activity. European Journal of Medicinal Chemistry. 81. 192–203. 50 indexed citations
12.
Nantasenamat, Chanin, Apilak Worachartcheewan, Likit Preeyanon, et al.. (2014). AutoWeka: Toward an Automated Data Mining Software for QSAR and QSPR Studies. Methods in molecular biology. 1260. 119–147. 20 indexed citations
13.
Mandi, Prasit, Watshara Shoombuatong, Chartchalerm Isarankura‐Na‐Ayudhya, et al.. (2014). Exploring the origins of structure–oxygen affinity relationship of human haemoglobin allosteric effector. Molecular Simulation. 41(15). 1283–1291. 4 indexed citations
14.
Nantasenamat, Chanin, Hao Li, Prasit Mandi, et al.. (2013). Exploring the chemical space of aromatase inhibitors. Molecular Diversity. 17(4). 661–677. 28 indexed citations
15.
Nantasenamat, Chanin, et al.. (2013). QSAR modeling of aromatase inhibition by flavonoids using machine learning approaches. Chemical Papers. 68(5). 10 indexed citations
16.
Mandi, Prasit, et al.. (2012). QSAR study of anti-prion activity of 2-aminothiazoles.. PubMed. 11. 453–67. 13 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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