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Nitin K. Singh
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2020 – today
- 2024
- [j3]Nitin K. Singh, Abhisek K. Behera:
Robust state estimation via twisting observer. Autom. 160: 111433 (2024)
2010 – 2019
- 2018
- [j2]Nitin K. Singh, Mehmet Eren Ahsen, Niharika Challapalli, Hyun-Seok Kim, Michael A. White, Mathukumalli Vidyasagar:
Inferring Genome-Wide Interaction Networks Using the Phi-Mixing Coefficient, and Applications to Lung and Breast Cancer. IEEE Trans. Mol. Biol. Multi Scale Commun. 4(3): 123-139 (2018) - 2016
- [j1]Nitin K. Singh, Mathukumalli Vidyasagar:
bLARS: An Algorithm to Infer Gene Regulatory Networks. IEEE ACM Trans. Comput. Biol. Bioinform. 13(2): 301-314 (2016) - [c7]Mehmet Eren Ahsen, Todd P. Boren, Nitin K. Singh, Burook Misganaw, Jayanthi S. Lea, David S. Miller, Michael A. White, Mathukumalli Vidyasagar:
Sparse Feature Selection for Classification and Prediction of Metastasis in Endometrial Cancer: Extended Abstract. BCB 2016: 522-524 - 2015
- [c6]Burook Misganaw, Mehmet Eren Ahsen, Nitin K. Singh, Keith A. Baggerly, Anna Unruh, Michael A. White, Mathukumalli Vidyasagar:
Optimized prediction of extreme treatment outcomes in ovarian cancer. CDC 2015: 1254-1258 - 2014
- [c5]Nitin K. Singh, M. Vidyasagar:
Inferring Gene Regulatory Networks with Sparse Bayesian Learning and phi-mixing coefficient. ECC 2014: 1510-1515 - 2013
- [c4]Nitin K. Singh, Aishwarya Sundaresan, Mathukumalli Vidyasagar:
A sparse Bayesian learning based approach to Inferring Gene Regulatory Networks. GlobalSIP 2013: 113-116 - 2012
- [c3]Nitin K. Singh, Mehmet Eren Ahsen, Shiva Mankala, M. Vidyasagar, Michael A. White:
A novel application of mixing coefficients for reverse-engineering gene interaction networks. Allerton Conference 2012: 1461-1466 - [c2]Mehmet Eren Ahsen, Nitin K. Singh, Todd P. Boren, M. Vidyasagar, Michael A. White:
A new feature selection algorithm for two-class classification problems and application to endometrial cancer. CDC 2012: 2976-2982 - [c1]Nitin K. Singh, Mehmet Eren Ahsen, Shiva Mankala, M. Vidyasagar, Michael A. White:
Inferring weighted and directed gene interaction networks from gene expression data using the phi-mixing coefficient. GENSiPS 2012: 168-171
Coauthor Index
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