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Research interests:
- Statistical integrative analysis of multiple expression profiles
- Meta-analysis of multiple microarray studies.
- Inter-platform and inter-center prediction of microarray studies.
- Biomarker detection:
- Unsupervised machine learning (clustering):
- Tight clustering: systematically extract stable and tight patterns in large complex data through resampling approach. (Biometrics 2005; Bioinformatics 2006)
- Penalized and weighted K-means: a class of loss function extended from K-means that allows a noise set not being clustered and incorporation of prior knowledge. (Bioinformatics 2007)
- Supervised machine learning (classification):
- Psi learning: utilize a modified penalty term in SVM to achieve a theoretically optimal error rate. (joint work with Xiaotong Shen and Wing Wong) (JASA 2003)
- Data mining and graphical visualization for genomic and proteomic data
- Quantile map: under development.
- Microarray data analysis and related statistical issues:
- Quality filtering, normalization, gene selection and multiple comparison, missing value imputation, Bayesian hierarchical model, ANOVA, pathway analysis. (NAR 1999)
- Functional genomics/regulatory networks
- Proteomics
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Collaborators:
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- Jianhua Luo, George Michalopoulos (Department of Pathology, Pitt): prostate cancer and liver cancer
- Etienne Sibille (Department of Psychiatry, Pitt): aging and depression
- Soonmyung Paik (Division of Pathology, NSABP): breast cancer
- Yuri Nikiforov (Department of Pathology, Pitt): thyroid tumors
- Timothy Billiar (Department of Surgery, Pitt): Trauma and Hemorrhagic Shock
- Julie Deloia (Magee Women Hospital, Pitt): ovarian cancer
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