Karthikeyan Subbiah

492 total citations
35 papers, 318 citations indexed

About

Karthikeyan Subbiah is a scholar working on Molecular Biology, Artificial Intelligence and Information Systems. According to data from OpenAlex, Karthikeyan Subbiah has authored 35 papers receiving a total of 318 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Molecular Biology, 8 papers in Artificial Intelligence and 6 papers in Information Systems. Recurrent topics in Karthikeyan Subbiah's work include Machine Learning in Bioinformatics (10 papers), Remote-Sensing Image Classification (5 papers) and Advanced Proteomics Techniques and Applications (4 papers). Karthikeyan Subbiah is often cited by papers focused on Machine Learning in Bioinformatics (10 papers), Remote-Sensing Image Classification (5 papers) and Advanced Proteomics Techniques and Applications (4 papers). Karthikeyan Subbiah collaborates with scholars based in India, United States and Italy. Karthikeyan Subbiah's co-authors include Abhigyan Nath, Manish Kumar Pandey, Radha Chaube, Anoop Kumar Tiwari, K.K. Shukla, Mamta Mittal, Tanmoy Som, Daniel A.C. Frattarelli, Yvette R. Johnson and Vijendra Singh and has published in prestigious journals such as Journal of Theoretical Biology, Neurocomputing and Neural Computing and Applications.

In The Last Decade

Karthikeyan Subbiah

34 papers receiving 309 citations

Peers

Karthikeyan Subbiah

CTM

Kui Fang China

Songyot Nakariyakul Thailand

Haixia Long China

Tamazouzt Ait Saadi Algeria

José M. Chaves-González Spain

Jamal Uddin Pakistan

Surendra Kumar Shukla India

Xi Yu China

Fang Du China

Yue Yang China

Kui Fang China

Karthikeyan Subbiah

85 ×0.9

73 ×1.2

13 ×0.2

CTM

61 ×1.3

17 ×0.4

Citations per year, relative to Karthikeyan Subbiah Karthikeyan Subbiah (= 1×) peers Kui Fang

Countries citing papers authored by Karthikeyan Subbiah

Since Specialization

Citations

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

Fields of papers citing papers by Karthikeyan Subbiah

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Karthikeyan Subbiah

This figure shows the co-authorship network connecting the top 25 collaborators of Karthikeyan Subbiah. A scholar is included among the top collaborators of Karthikeyan Subbiah 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 Karthikeyan Subbiah. Karthikeyan Subbiah 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

Subbiah, Karthikeyan, et al.. (2025). Wrapper Feature Selection Method for Predicting Student Dropout in Higher Education. 4(1). 58–76.

Pandey, Manish Kumar & Karthikeyan Subbiah. (2023). A Deep Learning Approach for Classification of Medicare Beneficiaries Based on Gender and being Affected with Cancer. Procedia Computer Science. 218. 532–541. 1 indexed citations

Pandey, Manish Kumar, et al.. (2022). Improved Carpooling Experience through Improved GPS Trajectory Classification Using Machine Learning Algorithms. Information. 13(8). 369–369. 2 indexed citations

Pandey, Manish Kumar, et al.. (2021). Enhanced classification of hyperspectral images using improvised oversampling and undersampling techniques. International Journal of Information Technology. 14(1). 389–396. 17 indexed citations

Subbiah, Karthikeyan, et al.. (2020). Artificial Intelligence based Comparative Study of Mortality Prediction. 910–914. 1 indexed citations

Pandey, Manish Kumar, et al.. (2020). An LSTM Based Time Series Forecasting Framework for Web Services Recommendation. Computación y Sistemas. 24(2). 1 indexed citations

Tiwari, Anoop Kumar, et al.. (2018). New approaches to intuitionistic fuzzy-rough attribute reduction. Journal of Intelligent & Fuzzy Systems. 34(5). 3385–3394. 11 indexed citations

Nath, Abhigyan & Karthikeyan Subbiah. (2018). Enhanced prediction of recombination hotspots using input features extracted by class specific autoencoders. Journal of Theoretical Biology. 444. 73–82. 8 indexed citations

Nath, Abhigyan & Karthikeyan Subbiah. (2017). Enhanced identification of β-lactamases and its classes using sequence, physicochemical and evolutionary information with sequence feature characterization of the classes. Computational Biology and Chemistry. 68. 29–38. 5 indexed citations

10.

Tiwari, Anoop Kumar, Abhigyan Nath, Karthikeyan Subbiah, & K.K. Shukla. (2017). Enhanced Prediction for Observed Peptide Count in Protein Mass Spectrometry Data by Optimally Balancing the Training Dataset. International Journal of Pattern Recognition and Artificial Intelligence. 31(12). 1750040–1750040. 4 indexed citations

11.

Nath, Abhigyan & Karthikeyan Subbiah. (2016). Enhanced Prediction and Characterization of CDK Inhibitors Using Optimal Class Distribution. Interdisciplinary Sciences Computational Life Sciences. 9(2). 292–303. 15 indexed citations

12.

Nath, Abhigyan & Karthikeyan Subbiah. (2016). Probing an optimal class distribution for enhancing prediction and feature characterization of plant virus-encoded RNA-silencing suppressors. 3 Biotech. 6(1). 93–93. 8 indexed citations

13.

Nath, Abhigyan & Karthikeyan Subbiah. (2015). Unsupervised learning assisted robust prediction of bioluminescent proteins. Computers in Biology and Medicine. 68. 27–36. 16 indexed citations

14.

Nath, Abhigyan & Karthikeyan Subbiah. (2015). Maximizing lipocalin prediction through balanced and diversified training set and decision fusion. Computational Biology and Chemistry. 59. 101–110. 20 indexed citations

15.

Pandey, Manish Kumar, et al.. (2015). Comparative study on machine learning techniques in predicting the QoS-values for web-services recommendations. 161–167. 6 indexed citations

16.

Nath, Abhigyan & Karthikeyan Subbiah. (2015). Insights into the molecular basis of piezophilic adaptation: Extraction of piezophilic signatures. Journal of Theoretical Biology. 390. 117–126. 13 indexed citations

17.

Pandey, Manish Kumar, et al.. (2015). Missing QoS-values predictions using neural networks for cloud computing environments. 414–419. 10 indexed citations

18.

Nath, Abhigyan & Karthikeyan Subbiah. (2014). Inferring biological basis about psychrophilicity by interpreting the rules generated from the correctly classified input instances by a classifier. Computational Biology and Chemistry. 53. 198–203. 12 indexed citations

19.

Nath, Abhigyan, Radha Chaube, & Karthikeyan Subbiah. (2013). An insight into the molecular basis for convergent evolution in fish antifreeze Proteins. Computers in Biology and Medicine. 43(7). 817–821. 21 indexed citations

20.

Frattarelli, Daniel A.C., et al.. (2006). Altered Prostaglandin E1 Dosage During Extracorporeal Membrane Oxygenation in a Newborn with Ductal-dependent Congenital Heart Disease. Pediatric Cardiology. 27(3). 360–363. 8 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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