Kuan Pern Tan

565 total citations
8 papers, 402 citations indexed

About

Kuan Pern Tan is a scholar working on Molecular Biology, Materials Chemistry and Oncology. According to data from OpenAlex, Kuan Pern Tan has authored 8 papers receiving a total of 402 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Molecular Biology, 4 papers in Materials Chemistry and 1 paper in Oncology. Recurrent topics in Kuan Pern Tan's work include Protein Structure and Dynamics (7 papers), Enzyme Structure and Function (4 papers) and RNA and protein synthesis mechanisms (3 papers). Kuan Pern Tan is often cited by papers focused on Protein Structure and Dynamics (7 papers), Enzyme Structure and Function (4 papers) and RNA and protein synthesis mechanisms (3 papers). Kuan Pern Tan collaborates with scholars based in Singapore, India and Australia. Kuan Pern Tan's co-authors include M. S. Madhusudhan, Raghavan Varadarajan, Minh N. Nguyen, Thanh Nguyen, Siddharth Patel, Anirban Hazra, Khushboo Singh, Raghavan Varadarajan, Shruti Khare and Neeladri Sen and has published in prestigious journals such as Nucleic Acids Research, SHILAP Revista de lepidopterología and Biochemical Pharmacology.

In The Last Decade

Kuan Pern Tan

8 papers receiving 397 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Kuan Pern Tan Singapore	7	307	66	65	31	30	8	402
Thomas Evangelidis Greece	10	360 1.2×	68 1.0×	94 1.4×	41 1.3×	32 1.1×	14	475
Carlos P. Modenutti Argentina	13	374 1.2×	66 1.0×	118 1.8×	26 0.8×	59 2.0×	27	523
Susanne Eyrisch Germany	8	418 1.4×	66 1.0×	123 1.9×	24 0.8×	40 1.3×	10	507
Jesse Woo United States	2	318 1.0×	63 1.0×	87 1.3×	15 0.5×	48 1.6×	3	423
Efrat Ben‐Zeev Israel	13	325 1.1×	51 0.8×	87 1.3×	33 1.1×	35 1.2×	24	439
Juan Pablo Arcon Argentina	10	329 1.1×	52 0.8×	106 1.6×	28 0.9×	39 1.3×	15	407
Martin Kulke Germany	10	211 0.7×	42 0.6×	46 0.7×	24 0.8×	22 0.7×	25	358
T.L. Arakaki United States	13	304 1.0×	50 0.8×	46 0.7×	18 0.6×	58 1.9×	18	613
Jukka V. Lehtonen Finland	9	353 1.1×	130 2.0×	61 0.9×	15 0.5×	49 1.6×	15	483
João M. Martins Portugal	10	286 0.9×	67 1.0×	62 1.0×	10 0.3×	19 0.6×	16	347

Countries citing papers authored by Kuan Pern Tan

Since Specialization

Citations

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

Fields of papers citing papers by Kuan Pern Tan

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Kuan Pern Tan. 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 Kuan Pern Tan. The network helps show where Kuan Pern Tan may publish in the future.

Co-authorship network of co-authors of Kuan Pern Tan

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

All Works

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8 of 8 papers shown

Tan, Kuan Pern, et al.. (2021). Packpred: Predicting the Functional Effect of Missense Mutations. Frontiers in Molecular Biosciences. 8. 646288–646288. 5 indexed citations

Tan, Kuan Pern, Khushboo Singh, Anirban Hazra, & M. S. Madhusudhan. (2020). Peptide bond planarity constrains hydrogen bond geometry and influences secondary structure conformations. SHILAP Revista de lepidopterología. 3. 1–8. 41 indexed citations

Sen, Neeladri, et al.. (2017). Depth dependent amino acid substitution matrices and their use in predicting deleterious mutations. Progress in Biophysics and Molecular Biology. 128. 14–23. 8 indexed citations

Tan, Kuan Pern, Shruti Khare, Raghavan Varadarajan, & M. S. Madhusudhan. (2014). TSpred: a web server for the rational design of temperature-sensitive mutants. Nucleic Acids Research. 42(W1). W277–W284. 10 indexed citations

Tan, Kuan Pern, Thanh Nguyen, Siddharth Patel, Raghavan Varadarajan, & M. S. Madhusudhan. (2013). Depth: a web server to compute depth, cavity sizes, detect potential small-molecule ligand-binding cavities and predict the pKa of ionizable residues in proteins. Nucleic Acids Research. 41(W1). W314–W321. 145 indexed citations

Nguyen, Minh N., Kuan Pern Tan, & M. S. Madhusudhan. (2011). CLICK—topology-independent comparison of biomolecular 3D structures. Nucleic Acids Research. 39(suppl_2). W24–W28. 102 indexed citations

Murray, Michael, Kuan Pern Tan, Vishwaroop Mulay, et al.. (2011). Functional analysis of pharmacogenetic variants of human organic cation/carnitine transporter 2 (hOCTN2) identified in Singaporean populations. Biochemical Pharmacology. 82(11). 1692–1699. 13 indexed citations

Tan, Kuan Pern, Raghavan Varadarajan, & M. S. Madhusudhan. (2011). DEPTH: a web server to compute depth and predict small-molecule binding cavities in proteins. Nucleic Acids Research. 39(suppl_2). W242–W248. 78 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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