2014.01-2017.05 Ph.D., Statistics, University of Georgia
2011.09-2014.01 Ph.D student in Bioinformatics, University of Georgia (Incomplete)
2007.09-2011.07 B.S., Mathematics, Beijing Normal University
2017.8-now Assistant Professor, School of Medicine, Indiana University, Indianapolis, IN
2011.9-2017.7 Research Assistant, University of Georgia, Athens, GA
410 West 10th Street, Suite 3073
Indianapolis, IN 46202
I am interested in developing and applying statistical, mathematical and computational methods for mining cancer tissue omic data to tackle fundamental and challenging cancer biology questions including the following areas:
- Construction of Bayesian networks to infer the dependencies between micro-environmental stresses, key metabolic changes and explosive growth of post-metastatic cancers
- Bayesian biclustering based derivation of cell type-specific expression modules to digitally dissect mixture tissue expressions into sum of component cell types’ contributions
- Markov Chain Monte Carlo algorithm based metabolic flux estimation for cancer cells with priors on normal cells’ flux and cancer specific kinetic parameters
- Large scale association studies on epigenomic markers in cancers with detected micro-environmental stress markers of various types based on integrated studies of epigenomic and transriptomic data
For full publication, please go to: https://www.researchgate.net/profile/Sha_Cao2.
- Cao S+, Zhou Y+, Wu Y, Song TC, Alsaihati B, Xu Y. Transcription Regulation by DNA Methylation under Stressful Conditions in Human Cancer. Quantitative Biology. (2017) (In revision).
- Cao S+, Zhu X+, Zhang C, Qian H, Schuttler HB, Gong JP, Xu Y. Competition between DNA methylation, nucleotide synthesis and anti-oxidation in cancer versus normal tissues. Cancer Res. (2017) DOI: 10.1158/0008-5472.CAN-17-0262.
- Cao S+, Zhang C+, and Xu Y. Somatic Mutations May Not Be the Primary Drivers of Cancer Formation. International Journal of Cancer. (2015) DOI: 10.1002/ijc.29639.
Manuscripts in Preparation
- Cao S, Yao F, Xu Y. De-convolution of tissue-based gene-expression data to cell type specific contributions and application to cancer tissue gene-expression data analyses, in preparation.
- Cao S, Dong N, Song TC, Xu Y. Two major contributors to cancer tissue-based gene-expression data: biological functions and anti-oxidation, and application to reliable prediction of gene-expression levels of protein complexes, in preparation.
- Cao S, Zhang C, Liu C, Ji F, Szemprich A, Zhang Y, Yuan Y, Teng Q, Wang C, Jiang J, Gu J, Xu Y. Oxidized Cholesterol Plays a Key Role in Driving the Rapid Growth of Metastatic Cancer, in preparation.