[Legacy Report] SMC and EMB Seminar on Change-point Models for Detecting Aberrant Gene Expression Patterns in Cancers
IEEE Northern Jersey Section SMC and EMBS Chapters
Change-point Models for Detecting Aberrant Gene Expression Patterns in Cancers
Zhi Wei, Ph.D.& Associate Professor
Department of Computer Science
New Jersey Institute of Technology
Time: 5:00pm, Wed., April 22, 2015
Place: ECE 202, New Jersey Institute of Technology
Abstract:
In cancer cells, the protein products of oncogenes can be overexpressed without alteration of the proto-oncogene but with shorter 3' untranslated regions (UTRs). During the past few years, RNA-seq has matured as a powerful tool for characterizing gene expressions because of its affordable cost and highly accurate digital resolution. For cancer study, the introduction of RNA-Seq technology, equipped with new analytic methods, makes it possible to capture aberrant shortening or lengthening expression patterns of oncogenes.
Change-point models are a classical approach to determine whether a change has taken place and where the changes occur. In this talk I will introduce change-point models for detecting aberrant gene expression patterns. We develop appropriate parametrical models for characterizing RNA-seq data. In the multiple-testing framework, we will introduce Type I error control and testing efficiency issues for pattern recognition. The numerical performances of the approaches will be illustrated using both simulation study and applications to real cancer data.
Bio: Dr. Zhi Wei is an associate professor at the Department of Computer Science, New Jersey Institute of Technology. He receives his Ph.D. from the University of Pennsylvania and M.S. from the Rutgers University-New Brunswick. His research interests include multiple testing, statistical modelling, machine learning and data mining with applications to Bioinformatics and genetics. His recent research focuses on developing statistical models and data mining algorithms for analysis of high dimensional data. His research is funded by the National Institutes of Health, Department of Defense, the Pheo Para Alliance, the Henry M. Jackson Foundation, and the Robert Mapplethorpe Foundation. His methodology works have been published in prestigious journals and conferences including JASA, Biometrika, AJHG, AOAS, Bioinformatics, Biostatistics, PLoS Genetics, NAR and NIPS. He is an editorial board member of PLoS ONE, Frontiers in Bioinformatics and Computational Biology, and Frontiers in Applied Genetic Epidemiology.
Contact: Prof. Mengchu Zhou at zhou@njit.edu if any question. ECE 202 is located at the intersection between warren St. and Summit St., Newark, NJ 07102.
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