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

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

#	Work	Indexed citations
1	TMB Stab-pred: Predicting the stability of transmembrane β-barrel proteins using their sequence and structural signatures 2025 ·Biochimica et Biophysica Acta (BBA) - Proteins and Proteomics ·(unknown), A. Kulandaisamy, M. Michael Gromiha	0
2	Application of the surface engineered recombinant Escherichia coli to the industrial battery waste solution for lithium recovery 2024 ·Journal of Industrial Microbiology & Biotechnology ·(unknown), Vidhya Selvamani, Murali Kannan Maruthamuthu, A. Kulandaisamy, Soon Ho Hong	2
3	Progress on the development of prediction tools for detecting disease causing mutations in proteins 2024 ·Computers in Biology and Medicine ·M. Michael Gromiha, (unknown), A. Kulandaisamy, Divya Sharma, (unknown)	0
4	TMH Stab-pred: Predicting the stability of α-helical membrane proteins using sequence and structural features 2023 ·Methods ·(unknown), A. Kulandaisamy, M. Michael Gromiha	2
5	TMKit: a Python interface for computational analysis of transmembrane proteins 2023 ·Briefings in Bioinformatics ·Jianfeng Sun, A. Kulandaisamy, Jinlong Ru, M. Michael Gromiha, Adam P. Cribbs	1
6	Machine learning in computational modelling of membrane protein sequences and structures: From methodologies to applications 2023 ·Computational and Structural Biotechnology Journal ·Jianfeng Sun, A. Kulandaisamy, Jacklyn Liu, Kai Hu, M. Michael Gromiha, Yuan Zhang	8
7	Low RNA stability signifies strong expression regulatability of tumor suppressors 2023 ·Nucleic Acids Research ·Xinlei Gao, Yi Yang, Jie Lv, Yanqiang Li, A. Kulandaisamy, Sahana Suresh Babu, Ivone Bruno, Lili Zhang, Qi Cao, Kaifu Chen	4
8	MPAD: A Database for Binding Affinity of Membrane Protein–protein Complexes and their Mutants 2022 ·Journal of Molecular Biology ·(unknown), A. Kulandaisamy, M. Michael Gromiha	7
9	Halogen-Based 17β-HSD1 Inhibitors: Insights from DFT, Docking, and Molecular Dynamics Simulation Studies 2022 ·Molecules ·A. Kulandaisamy, (unknown), Rajadurai Vijay Solomon, Madhavan Jaccob, (unknown), P. Kumaradhas, (unknown), Nagendran Tharmalingam	9
10	ProNAB: database for binding affinities of protein–nucleic acid complexes and their mutants 2021 ·Nucleic Acids Research ·K. Harini, Ambuj Srivastava, A. Kulandaisamy, M. Michael Gromiha	30
11	MPTherm-pred: Analysis and Prediction of Thermal Stability Changes upon Mutations in Transmembrane Proteins 2020 ·Journal of Molecular Biology ·A. Kulandaisamy, Jan Zaucha, Dmitrij Frishman, M. Michael Gromiha	16
12	Mutations in transmembrane proteins: diseases, evolutionary insights, prediction and comparison with globular proteins 2020 ·Briefings in Bioinformatics ·Jan Zaucha, Michael Heinzinger, A. Kulandaisamy, (unknown), (unknown), Petr Popov, Burkhard Rost, M. Michael Gromiha, Boris S. Zhorov, Dmitrij Frishman	16
13	HuVarBase: A human variant database with comprehensive information at gene and protein levels 2019 ·PLoS ONE ·(unknown), A. Kulandaisamy, (unknown), M. Michael Gromiha	31
14	Prediction of disease-associated mutations in the transmembrane regions of proteins with known 3D structure 2019 ·PLoS ONE ·Petr Popov, Ilya V. Bizin, M. Michael Gromiha, A. Kulandaisamy, Dmitrij Frishman	21
15	Homology modeling identified for purported drug targets to the neuroprotective effects of levodopa and asiaticoside-D in degenerated cerebral ganglions of Lumbricus terrestris 2019 ·Indian Journal of Pharmacology ·(unknown), (unknown), A. Kulandaisamy, (unknown)	2
16	MutHTP: mutations in human transmembrane proteins 2018 ·Bioinformatics ·A. Kulandaisamy, (unknown), Ramasamy Sakthivel, S. I. Tarnovskaya, Ilya V. Bizin, Peter Hönigschmid, Dmitrij Frishman, M. Michael Gromiha	28
17	Dissecting and analyzing key residues in protein‐DNA complexes 2017 ·Journal of Molecular Recognition ·A. Kulandaisamy, Ambuj Srivastava, Nagarajan Raju, M. Michael Gromiha	8
18	Development of bisphenol A-removing recombinant Escherichia coli by monomeric and dimeric surface display of bisphenol A-binding peptide 2017 ·Bioprocess and Biosystems Engineering ·Murali Kannan Maruthamuthu, Jiyeon Hong, A. Kulandaisamy, (unknown), (unknown), Woo‐Seok Choe, Ik‐Keun Yoo	11
19	Construction of methanol sensing Escherichia coli by the introduction of novel chimeric MxcQZ/OmpR two-component system from Methylobacterium organophilum XX 2017 ·Korean Journal of Chemical Engineering ·Vidhya Selvamani, Murali Kannan Maruthamuthu, A. Kulandaisamy, Gyeong Tae Eom, Soon Ho Hong	13
20	Important amino acid residues involved in folding and binding of protein–protein complexes 2016 ·International Journal of Biological Macromolecules ·A. Kulandaisamy, (unknown), (unknown), Kumar Yugandhar, M. Michael Gromiha	21

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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