Subramani Mani

3.3k total citations
36 papers, 1.5k citations indexed

About

Subramani Mani is a scholar working on Artificial Intelligence, Molecular Biology and Management Science and Operations Research. According to data from OpenAlex, Subramani Mani has authored 36 papers receiving a total of 1.5k indexed citations (citations by other indexed papers that have themselves been cited), including 26 papers in Artificial Intelligence, 12 papers in Molecular Biology and 5 papers in Management Science and Operations Research. Recurrent topics in Subramani Mani's work include Bayesian Modeling and Causal Inference (12 papers), Biomedical Text Mining and Ontologies (10 papers) and Machine Learning in Healthcare (5 papers). Subramani Mani is often cited by papers focused on Bayesian Modeling and Causal Inference (12 papers), Biomedical Text Mining and Ontologies (10 papers) and Machine Learning in Healthcare (5 papers). Subramani Mani collaborates with scholars based in United States, Greece and Netherlands. Subramani Mani's co-authors include Constantin Aliferis, Yukun Chen, Alexander Statnikov, Xenofon Koutsoukos, Ioannis Tsamardinos, Suzanne McDermott, Joshua C. Denny, Hua Xu, Gregory F. Cooper and S. Trent Rosenbloom and has published in prestigious journals such as Bioinformatics, BMC Bioinformatics and Journal of the American Medical Informatics Association.

In The Last Decade

Subramani Mani

35 papers receiving 1.4k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Subramani Mani United States 18 783 415 175 160 153 36 1.5k
Serguei Pakhomov United States 28 1.6k 2.1× 1.4k 3.4× 241 1.4× 57 0.4× 357 2.3× 135 3.6k
Qing Zeng‐Treitler United States 26 816 1.0× 470 1.1× 72 0.4× 46 0.3× 228 1.5× 117 2.2k
Lucia Sacchi Italy 26 593 0.8× 587 1.4× 49 0.3× 54 0.3× 455 3.0× 129 2.5k
Henry Lowe United States 18 506 0.6× 590 1.4× 47 0.3× 30 0.2× 329 2.2× 40 1.6k
Rui Zhang United States 20 691 0.9× 488 1.2× 48 0.3× 27 0.2× 94 0.6× 144 1.7k
Marloes H. Maathuis Switzerland 20 832 1.1× 412 1.0× 63 0.4× 25 0.2× 45 0.3× 48 2.0k
Angus Roberts United Kingdom 23 1.2k 1.6× 794 1.9× 312 1.8× 17 0.1× 197 1.3× 89 2.4k
Shyam Visweswaran United States 23 721 0.9× 499 1.2× 60 0.3× 21 0.1× 243 1.6× 129 1.9k
Klaus A. Kuhn Germany 29 534 0.7× 318 0.8× 41 0.2× 44 0.3× 433 2.8× 110 2.1k
Liqin Wang United States 24 224 0.3× 324 0.8× 92 0.5× 52 0.3× 76 0.5× 84 1.5k

Countries citing papers authored by Subramani Mani

Since Specialization
Citations

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

Fields of papers citing papers by Subramani Mani

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Subramani Mani

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

All Works

20 of 20 papers shown
1.
Mani, Subramani, Daniel C. Cannon, Robin K. Ohls, et al.. (2017). Protein biomarker druggability profiling. Journal of Biomedical Informatics. 66. 241–247. 2 indexed citations
2.
Nelson, Stuart J., Tudor I. Oprea, Oleg Ursu, et al.. (2017). Formalizing drug indications on the road to therapeutic intent. Journal of the American Medical Informatics Association. 24(6). 1169–1172. 6 indexed citations
3.
Mani, Subramani, Yukun Chen, Xia Li, et al.. (2013). Machine learning for predicting the response of breast cancer to neoadjuvant chemotherapy. Journal of the American Medical Informatics Association. 20(4). 688–695. 40 indexed citations
4.
Mani, Subramani, Asli Özdaş, Constantin Aliferis, et al.. (2013). Medical decision support using machine learning for early detection of late-onset neonatal sepsis. Journal of the American Medical Informatics Association. 21(2). 326–336. 140 indexed citations
5.
Jiang, Min, Yukun Chen, Mei Liu, et al.. (2011). A study of machine-learning-based approaches to extract clinical entities and their assertions from discharge summaries. Journal of the American Medical Informatics Association. 18(5). 601–606. 214 indexed citations
6.
Chen, Yukun & Subramani Mani. (2011). Active Learning for Unbalanced Data in the Challenge with Multiple Models and Biasing. 113–126. 8 indexed citations
7.
Chen, Yukun, Subramani Mani, & Hua Xu. (2011). Applying active learning to assertion classification of concepts in clinical text. Journal of Biomedical Informatics. 45(2). 265–272. 33 indexed citations
8.
Aliferis, Constantin, Alexander Statnikov, Ioannis Tsamardinos, Subramani Mani, & Xenofon Koutsoukos. (2010). Local Causal and Markov Blanket Induction for Causal Discovery and Feature Selection for Classification Part I: Algorithms and Empirical Evaluation. Journal of Machine Learning Research. 11(7). 171–234. 309 indexed citations
9.
Aliferis, Constantin, Alexander Statnikov, Ioannis Tsamardinos, Subramani Mani, & Xenofon Koutsoukos. (2010). Local Causal and Markov Blanket Induction for Causal Discovery and Feature Selection for Classification Part II: Analysis and Extensions. Journal of Machine Learning Research. 11(8). 235–284. 106 indexed citations
10.
Varol, Hüseyin Atakan, Subramani Mani, Donald L. Compton, & Lynn S. Fuchs. (2009). Early prediction of reading disability using machine learning.. PubMed Central. 6 indexed citations
11.
Mani, Subramani, Constantin Aliferis, & Alexander Statnikov. (2008). Bayesian Algorithms for Causal Data Mining. Neural Information Processing Systems. 121–136. 6 indexed citations
12.
Mani, Subramani, Peter Spirtes, & Gregory F. Cooper. (2006). A theoretical study of Y structures for causal discovery. arXiv (Cornell University). 314–323. 24 indexed citations
13.
Mani, Subramani & Gregory F. Cooper. (2001). A Simulation Study of Three Related Causal Data Mining Algorithms. International Conference on Artificial Intelligence and Statistics. 184–191. 8 indexed citations
14.
Mani, Subramani & Gregory F. Cooper. (2000). Causal discovery from medical textual data.. PubMed. 542–6. 16 indexed citations
15.
Mani, Subramani, William R. Shankle, Malcolm Dick, & Michael J. Pazzani. (1999). Two-Stage Machine Learning model for guideline development. Artificial Intelligence in Medicine. 16(1). 51–71. 13 indexed citations
16.
Sproull, Lee, Subramani Mani, Sara Kiesler, Janet Walker, & Keith Waters. (1997). When the interface is a face. 163–190. 6 indexed citations
17.
Pazzani, Michael J., Subramani Mani, & William R. Shankle. (1997). Beyond concise and colorful: learning intelligible rules. Knowledge Discovery and Data Mining. 235–238. 31 indexed citations
18.
Mani, Subramani, William R. Shankle, Michael J. Pazzani, Padhraic Smyth, & Malcolm Dick. (1997). Differential Diagnosis of Dementia: A Knowledge Discovery and Data Mining (KDD) Approach. Europe PMC (PubMed Central). 875–875. 7 indexed citations
19.
Mani, Subramani. (1997). MENTOR: A bayesian model for prediction of mental retardation in newborns. Research in Developmental Disabilities. 18(5). 303–318. 17 indexed citations
20.
McDermott, Suzanne, et al.. (1996). A Population-Based Analysis of Behavior Problems in Children with Cerebral Palsy. Journal of Pediatric Psychology. 21(3). 447–463. 75 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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