Piyushkumar A. Mundra

According to our database, Piyushkumar A. Mundra authored at least 18 papers between 2007 and 2021.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2021

PIKE-R2P: Protein-protein interaction network-based knowledge embedding with graph neural network for single-cell RNA to protein prediction.

Xinnan Dai, Fan Xu, Shike Wang, Piyushkumar A. Mundra, Jie Zheng

BMC Bioinform., 2021

2020

Bayesian Data Fusion of Gene Expression and Histone Modification Profiles for Inference of Gene Regulatory Network.

Haifen Chen, D. A. K. Maduranga, Piyushkumar A. Mundra, Jie Zheng

IEEE ACM Trans. Comput. Biol. Bioinform., 2020

2016

Gene and sample selection using T-score with sample selection.

Piyushkumar A. Mundra, Jagath C. Rajapakse

J. Biomed. Informatics, 2016

2014

Highly sensitive inference of time-delayed gene regulation by network deconvolution.

Haifen Chen, Piyushkumar A. Mundra, Li Na Zhao, Feng Lin, Jie Zheng

BMC Syst. Biol., 2014

2013

Multiclass Gene Selection Using Pareto-Fronts.

Jagath C. Rajapakse, Piyushkumar A. Mundra

IEEE ACM Trans. Comput. Biol. Bioinform., 2013

Simultaneous Sample and Gene Selection Using T-score and Approximate Support Vectors.

Piyushkumar A. Mundra, Jagath C. Rajapakse, D. A. K. Maduranga

Proceedings of the Pattern Recognition in Bioinformatics, 2013

Inferring Gene Regulatory Networks from Time-Series Expressions Using Random Forests Ensemble.

D. A. K. Maduranga, Jie Zheng, Piyushkumar A. Mundra, Jagath C. Rajapakse

Proceedings of the Pattern Recognition in Bioinformatics, 2013

Inferring Time-Delayed Gene Regulatory Networks Using Cross-Correlation and Sparse Regression.

Piyushkumar A. Mundra, Jie Zheng, Mahesan Niranjan, Roy E. Welsch, Jagath C. Rajapakse

Proceedings of the Bioinformatics Research and Applications, 9th International Symposium, 2013

Integrating epigenetic prior in dynamic Bayesian network for gene regulatory network inference.

Haifen Chen, D. A. K. Maduranga, Piyushkumar A. Mundra, Jie Zheng

Proceedings of the 2013 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB), 2013

2011

Gene and sample selection for cancer identification

Piyushkumar A. Mundra

PhD thesis, 2011

Stability of building gene regulatory networks with sparse autoregressive models.

Jagath C. Rajapakse, Piyushkumar A. Mundra

BMC Bioinform., 2011

Features for cells and nuclei classification.

Song Liu, Piyushkumar A. Mundra, Jagath C. Rajapakse

Proceedings of the 33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2011

2010

Gene and sample selection for cancer classification with support vectors based t-statistic.

Piyushkumar A. Mundra, Jagath C. Rajapakse

Neurocomputing, 2010

Support vectors based correlation coefficient for gene and sample selection in cancer classification.

Piyushkumar A. Mundra, Jagath C. Rajapakse

Proceedings of the 2010 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, 2010

2009

F-score with Pareto Front Analysis for Multiclass Gene Selection.

Piyushkumar A. Mundra, Jagath C. Rajapakse

Proceedings of the Evolutionary Computation, 2009

2008

Support Vector Based T-Score for Gene Ranking.

Piyushkumar A. Mundra, Jagath C. Rajapakse

Proceedings of the Pattern Recognition in Bioinformatics, 2008

2007

Using pseudo amino acid composition to predict protein subnuclear localization: Approached with PSSM.

Piyushkumar A. Mundra, Madhan Kumar, K. Krishna Kumar, Valadi K. Jayaraman, Bhaskar D. Kulkarni

Pattern Recognit. Lett., 2007

SVM-RFE with Relevancy and Redundancy Criteria for Gene Selection.

Piyushkumar A. Mundra, Jagath C. Rajapakse

Proceedings of the Pattern Recognition in Bioinformatics, 2007