A. Kulandaisamy

774 total citations
33 papers, 448 citations indexed

About

A. Kulandaisamy is a scholar working on Molecular Biology, Genetics and Materials Chemistry. According to data from OpenAlex, A. Kulandaisamy has authored 33 papers receiving a total of 448 indexed citations (citations by other indexed papers that have themselves been cited), including 30 papers in Molecular Biology, 12 papers in Genetics and 5 papers in Materials Chemistry. Recurrent topics in A. Kulandaisamy's work include RNA and protein synthesis mechanisms (16 papers), Machine Learning in Bioinformatics (11 papers) and Protein Structure and Dynamics (11 papers). A. Kulandaisamy is often cited by papers focused on RNA and protein synthesis mechanisms (16 papers), Machine Learning in Bioinformatics (11 papers) and Protein Structure and Dynamics (11 papers). A. Kulandaisamy collaborates with scholars based in India, United States and Japan. A. Kulandaisamy's co-authors include M. Michael Gromiha, K. Harini, Divya Sharma, Dmitrij Frishman, Ramasamy Sakthivel, Jan Zaucha, Ambuj Srivastava, Ilya V. Bizin, Petr Popov and Murali Kannan Maruthamuthu and has published in prestigious journals such as Nucleic Acids Research, Bioinformatics and PLoS ONE.

In The Last Decade

A. Kulandaisamy

29 papers receiving 442 citations

Peers

A. Kulandaisamy

GENET

CTM

Matteo Cagiada Denmark

Judit Ősz France

Marc Hoemberger United States

E. Allen Sickmier United States

L. Bellsolell Spain

Christopher Negron United States

Anders R. Sørensen Denmark

Simran Kaur Aulakh United Kingdom

William F. Waas United States

Matteo Cagiada Denmark

A. Kulandaisamy

275 ×0.7

96 ×1.1

GENET

39 ×0.6

14 ×0.5

12 ×0.5

CTM

Citations per year, relative to A. Kulandaisamy A. Kulandaisamy (= 1×) peers Matteo Cagiada

Countries citing papers authored by A. Kulandaisamy

Since Specialization

Citations

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

Fields of papers citing papers by A. Kulandaisamy

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of A. Kulandaisamy

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

All Works

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20 of 20 papers shown

Kulandaisamy, A., et al.. (2025). TMB Stab-pred: Predicting the stability of transmembrane β-barrel proteins using their sequence and structural signatures. Biochimica et Biophysica Acta (BBA) - Proteins and Proteomics. 1873(4). 141070–141070.

Selvamani, Vidhya, et al.. (2024). Application of the surface engineered recombinant Escherichia coli to the industrial battery waste solution for lithium recovery. Journal of Industrial Microbiology & Biotechnology. 51. 2 indexed citations

Gromiha, M. Michael, et al.. (2024). Progress on the development of prediction tools for detecting disease causing mutations in proteins. Computers in Biology and Medicine. 185. 109510–109510.

Kulandaisamy, A., et al.. (2023). TMH Stab-pred: Predicting the stability of α-helical membrane proteins using sequence and structural features. Methods. 218. 118–124. 2 indexed citations

Sun, Jianfeng, A. Kulandaisamy, Jinlong Ru, M. Michael Gromiha, & Adam P. Cribbs. (2023). TMKit: a Python interface for computational analysis of transmembrane proteins. Briefings in Bioinformatics. 24(5). 1 indexed citations

Sun, Jianfeng, A. Kulandaisamy, Jacklyn Liu, et al.. (2023). Machine learning in computational modelling of membrane protein sequences and structures: From methodologies to applications. Computational and Structural Biotechnology Journal. 21. 1205–1226. 8 indexed citations

Gao, Xinlei, Yi Yang, Jie Lv, et al.. (2023). Low RNA stability signifies strong expression regulatability of tumor suppressors. Nucleic Acids Research. 51(21). 11534–11548. 4 indexed citations

Kulandaisamy, A., et al.. (2022). MPAD: A Database for Binding Affinity of Membrane Protein–protein Complexes and their Mutants. Journal of Molecular Biology. 435(14). 167870–167870. 7 indexed citations

Kulandaisamy, A., et al.. (2022). Halogen-Based 17β-HSD1 Inhibitors: Insights from DFT, Docking, and Molecular Dynamics Simulation Studies. Molecules. 27(12). 3962–3962. 9 indexed citations

10.

Harini, K., Ambuj Srivastava, A. Kulandaisamy, & M. Michael Gromiha. (2021). ProNAB: database for binding affinities of protein–nucleic acid complexes and their mutants. Nucleic Acids Research. 50(D1). D1528–D1534. 30 indexed citations

11.

Kulandaisamy, A., Jan Zaucha, Dmitrij Frishman, & M. Michael Gromiha. (2020). MPTherm-pred: Analysis and Prediction of Thermal Stability Changes upon Mutations in Transmembrane Proteins. Journal of Molecular Biology. 433(11). 166646–166646. 16 indexed citations

12.

Zaucha, Jan, Michael Heinzinger, A. Kulandaisamy, et al.. (2020). Mutations in transmembrane proteins: diseases, evolutionary insights, prediction and comparison with globular proteins. Briefings in Bioinformatics. 22(3). 16 indexed citations

13.

Kulandaisamy, A., et al.. (2019). HuVarBase: A human variant database with comprehensive information at gene and protein levels. PLoS ONE. 14(1). e0210475–e0210475. 31 indexed citations

14.

Popov, Petr, Ilya V. Bizin, M. Michael Gromiha, A. Kulandaisamy, & Dmitrij Frishman. (2019). Prediction of disease-associated mutations in the transmembrane regions of proteins with known 3D structure. PLoS ONE. 14(7). e0219452–e0219452. 21 indexed citations

15.

Kulandaisamy, A., et al.. (2019). Homology modeling identified for purported drug targets to the neuroprotective effects of levodopa and asiaticoside-D in degenerated cerebral ganglions of Lumbricus terrestris. Indian Journal of Pharmacology. 51(1). 31–31. 2 indexed citations

16.

Kulandaisamy, A., Ramasamy Sakthivel, S. I. Tarnovskaya, et al.. (2018). MutHTP: mutations in human transmembrane proteins. Bioinformatics. 34(13). 2325–2326. 28 indexed citations

17.

Kulandaisamy, A., Ambuj Srivastava, Nagarajan Raju, & M. Michael Gromiha. (2017). Dissecting and analyzing key residues in protein‐DNA complexes. Journal of Molecular Recognition. 31(4). 8 indexed citations

18.

Maruthamuthu, Murali Kannan, et al.. (2017). Development of bisphenol A-removing recombinant Escherichia coli by monomeric and dimeric surface display of bisphenol A-binding peptide. Bioprocess and Biosystems Engineering. 41(4). 479–487. 11 indexed citations

19.

Selvamani, Vidhya, Murali Kannan Maruthamuthu, A. Kulandaisamy, Gyeong Tae Eom, & Soon Ho Hong. (2017). Construction of methanol sensing Escherichia coli by the introduction of novel chimeric MxcQZ/OmpR two-component system from Methylobacterium organophilum XX. Korean Journal of Chemical Engineering. 34(6). 1734–1739. 13 indexed citations

20.

Kulandaisamy, A., et al.. (2016). Important amino acid residues involved in folding and binding of protein–protein complexes. International Journal of Biological Macromolecules. 94(Pt A). 438–444. 21 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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