TBA

From CsiBioWiki

Spectral Analysis of DNA Sequence and Microarray Data

Hong Yan City University of Hong Kong

Data collected in the real world often contain hidden periodicities or oscillatory components. Periodic patterns exist in symbolic as well as numerical information. We have recently developed spectral estimation based methods for DNA sequence and microarray data analysis. Based on parametric models, we are able to locate short exons in DNA sequences and detect tandem repeats. We have also found a closed-form mathematical solution to the correlation between spectral components. Our methods can be used to identify many regulatory gene pairs and even many-to-one regulatory gene groups based on microarray gene expression data. In addition, we can extrapolate gene expression time series and compare data obtained with different sampling rates and data lengths. Our spectral estimation based techniques can provide a robust computational tool for the detection of periodically expressed genes, study of gene functions and inference of genetic networks.

About the speaker: Hong Yan received his Ph.D. degree from Yale University. He has been Professor of Imaging Science at the University of Sydney and is currently Professor of Computer Engineering at City University of Hong Kong. His research interests include image processing, pattern recognition and bioinformatics, and he has over 300 journal and conference publications in these areas. Professor Yan is a fellow of IEEE, IAPR and IEAust.