1. Inference of gene regulatory networks with heterogeneous data (Gene expression + SNP + DNA Methylation) : Ongoing and will be submitted to BIBM2014
2. Personalized Medicine and application to pathway inference and biomarker discovery
3. Learning Discriminative Structure of Bayesian Network Classifier via Conditional Likelihood
4. SGRN inference + epistasis
5. Prognosis of psychiatric disorders using SNP, CNV, DNA Methylation, and gene expression : next future work
6. feature selection using iterative adaptive lasso : next future work
[J1] D. Kim, C. Liu, and J. Gao, "Integrative approach for inference of gene regulatory networks using lasso-based random featuring and application to psychiatric disorders," Bioinformatics, under review.
[J2] D. Kim, X. Wang, C. Yang, and J. Gao, "Effects of low dose ionizing radiation in DNA damage-caused pathways inferred by using reverse phase protein array and Bayesian networks," Bioinformatics, under review.
[J3] D. Kim, C. Liu, and J. Gao, "Inference of Gene Regulatory Networks by Integrating Gene Expressions and Genetic Perturbations," BioMed Research International (impact factor: 2.88), 2014, accepted.
[J4] D. Kim, X. Wang, C. Yang, and J. Gao, "Reverse Phase Protein Microarray in signaling pathways: a data integration perspective," Drug Design, Development and Therapy (impact factor: 3.49), 2013, under review.
[J5] D. Kim, X. Wang, C. Yang, and J. Gao, "A framework for personalized medicine: prediction of drug sensitivity in cancer by proteomic profiling," Proteome Science (impact factor: 2.49), 10(Suppl 1):S13, 2012.
[J6] D. Kim, X. Wang, C. Yang, and J. Gao, "Learning Biological Network Using Mutual Information and Conditional Independence," BMC Bioinformatics (impact factor: 3.028), 11(Suppl 3):S9, 2010.
[J7] M. Kang, S. Li, D. Kim, C. Liu and J. Gao, "Regularized eQTL detection via sparse bivariate correlation analysis: a genetics study of psychiatric disorder," Bioinformatics, 2014, under review.
[J8] M. Kang, D. Kim, T. Talamantes, L. Prokai, and J. Gao, "MaxLap: protein quantication strategy in label-free proteomics data based on spectral counting," Rapid communications in Mass spectrometry, 2014, under review.
[J9] DREAM8 consortium,"HPN-DREAM Breast Cancer Network Inference Challenge," to appear in Nature Methods, 2014 (as a participant in DREAM8).
[C1] D. Kim, M. Kang, and J. Gao, "Learning Structure of Bayesian Network Classifier and Application to Personalized Medicine and Biomarker Identification for Lung Cancer," to be submitted in ICDM2014
[C2] D. Kim, C. Liu, and J. Gao, "Inference of Gene Regulatory Networks by Integrating Gene Expressions and Genetic Perturbations," IEEE International Conference on Bioinformatics and Biomedicine 2013 (IEEE BIBM) (regular paper acceptance rate 19.6%), Shanghai, China, Dec 18-21, 2013.
[C3] D. Kim, X. Wang, C. Yang, and J. Gao, "A Framework for Personalized Medicine with Reverse Phase Protein Array and Drug Sensitivity," IEEE International Conference on Bioinformatics & Biomedicine (IEEE BIBM), Atlanta, GA, Nov 12-15, 2011.
[C4] D. Kim, C. Yang, X. Wang, B. Zhang, X. Wu, and J. Gao, "Discovery of Lung Cancer Pathways using Reverse Phase Protein Microarray and Prior-Knowledge based Bayesian Networks," Proceedings of IEEE Engineering in Medicine and Biology Society, Boston, MA, Aug 30-Sept 3, 2011.
[C5] D. Kim, C. Yang, and J. Gao, "Learning Proteomic Network Structure by a New Hill Climbing Algorithm," Proceedings of IEEE Symposium of Bioinformatics and Bioengineering (IEEE BIBE), pp. 191-196, Philadelphia, PA, May 31-Jun 3, 2010.
[C6] M. Kang, S. Li, D. Kim, C. Liu, and J. Gao, "eQTL Mapping Study via Regularized Sparse Canonical Correlation Analysis," 12th International Conference on Machine Learning and Applications (IEEE ICMLA 2013), Miami, FL, Dec. 4-7, 2013.
[C7] M. Kang, D. Kim, and J. Gao, "SF-RPQ: A novel statistical framework for reliable protein quantification in label-free quantitative proteomics," International Conference of the IEEE Engineering in Medicine and Biology Society, pp. 3527-3530, Osaka, Japan, July 3-7, 2013.
[C8] M. Kang, D. Kim, and J. Gao, "A Novel Multivariate Quantification Strategy for Complex Mass Spectrometry Data," International Conference on Bioinformatics and Computational Biology (BICoB 2012), pp. 257-262, Las Vegas, NV, March 12-14, 2012.