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2020 – today
- 2021
[j8]Xinnan Dai, Fan Xu, Shike Wang, Piyushkumar A. Mundra, Jie Zheng
:
PIKE-R2P: Protein-protein interaction network-based knowledge embedding with graph neural network for single-cell RNA to protein prediction. BMC Bioinform. 22-S(6): 139 (2021)- 2020
- [j7]Haifen Chen, D. A. K. Maduranga, Piyushkumar A. Mundra, Jie Zheng:
Bayesian Data Fusion of Gene Expression and Histone Modification Profiles for Inference of Gene Regulatory Network. IEEE ACM Trans. Comput. Biol. Bioinform. 17(2): 516-525 (2020)
2010 – 2019
- 2016
- [j6]Piyushkumar A. Mundra, Jagath C. Rajapakse:
Gene and sample selection using T-score with sample selection. J. Biomed. Informatics 59: 31-41 (2016) - 2014
- [j5]Haifen Chen, Piyushkumar A. Mundra, Li Na Zhao, Feng Lin, Jie Zheng:
Highly sensitive inference of time-delayed gene regulation by network deconvolution. BMC Syst. Biol. 8(S-4): S6 (2014) - 2013
- [j4]Jagath C. Rajapakse, Piyushkumar A. Mundra:
Multiclass Gene Selection Using Pareto-Fronts. IEEE ACM Trans. Comput. Biol. Bioinform. 10(1): 87-97 (2013) - [c9]Haifen Chen, D. A. K. Maduranga, Piyushkumar A. Mundra, Jie Zheng:
Integrating epigenetic prior in dynamic Bayesian network for gene regulatory network inference. CIBCB 2013: 76-82 - [c8]Piyushkumar A. Mundra, Jie Zheng, Mahesan Niranjan, Roy E. Welsch, Jagath C. Rajapakse:
Inferring Time-Delayed Gene Regulatory Networks Using Cross-Correlation and Sparse Regression. ISBRA 2013: 64-75 - [c7]D. A. K. Maduranga, Jie Zheng, Piyushkumar A. Mundra, Jagath C. Rajapakse:
Inferring Gene Regulatory Networks from Time-Series Expressions Using Random Forests Ensemble. PRIB 2013: 13-22 - [c6]Piyushkumar A. Mundra, Jagath C. Rajapakse, D. A. K. Maduranga:
Simultaneous Sample and Gene Selection Using T-score and Approximate Support Vectors. PRIB 2013: 79-90 - 2011
- [b1]Piyushkumar A. Mundra:
Gene and sample selection for cancer identification. Nanyang Technological University, Singapore, 2011 - [j3]Jagath C. Rajapakse, Piyushkumar A. Mundra:
Stability of building gene regulatory networks with sparse autoregressive models. BMC Bioinform. 12(S-13): S17 (2011) - [c5]Song Liu, Piyushkumar A. Mundra, Jagath C. Rajapakse:
Features for cells and nuclei classification. EMBC 2011: 6601-6604 - 2010
- [j2]Piyushkumar A. Mundra, Jagath C. Rajapakse:
Gene and sample selection for cancer classification with support vectors based t-statistic. Neurocomputing 73(13-15): 2353-2362 (2010) - [c4]Piyushkumar A. Mundra, Jagath C. Rajapakse:
Support vectors based correlation coefficient for gene and sample selection in cancer classification. CIBCB 2010: 1-7
2000 – 2009
- 2009
- [c3]Piyushkumar A. Mundra, Jagath C. Rajapakse:
F-score with Pareto Front Analysis for Multiclass Gene Selection. EvoBIO 2009: 56-67 - 2008
- [c2]Piyushkumar A. Mundra, Jagath C. Rajapakse:
Support Vector Based T-Score for Gene Ranking. PRIB 2008: 144-153 - 2007
- [j1]Piyushkumar A. Mundra, Madhan Kumar, K. Krishna Kumar, Valadi K. Jayaraman, Bhaskar D. Kulkarni:
Using pseudo amino acid composition to predict protein subnuclear localization: Approached with PSSM. Pattern Recognit. Lett. 28(13): 1610-1615 (2007) - [c1]Piyushkumar A. Mundra, Jagath C. Rajapakse:
SVM-RFE with Relevancy and Redundancy Criteria for Gene Selection. PRIB 2007: 242-252
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