tailieunhanh - Báo cáo hóa học: " Genomic Signal Processing: The Salient Issues"

Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Genomic Signal Processing: The Salient Issues | EURASIP Journal on Applied Signal Processing 2004 1 146-153 2004 Hindawi Publishing Corporation Genomic Signal Processing The Salient Issues Edward R. Dougherty Department of Electrical Engineering Texas A M University 3128 TAMU College Station TX 77843-3128 USA Email e-dougherty@ Ilya Shmulevich Department of Pathology The University of Texas MD Anderson Cancer Center Houston TX 77030 USA Email is@ Michael L. Bittner Molecular Diagnostics and Target Validation Division Translational Genomics Research Institute Tempe AZ 85281 USA Email mbittner@ Received 10 October 2003 This paper considers key issues in the emerging field of genomic signal processing and its relationship to functional genomics. It focuses on some of the biological mechanisms driving the development of genomic signal processing in addition to their manifestation in gene-expression-based classification and genetic network modeling. Certain problems are inherent. For instance small-sample error estimation variable selection and model complexity are important issues for both phenotype classification and expression prediction used in network inference. A long-term goal is to develop intervention strategies to drive network behavior which is briefly discussed. It is hoped that this nontechnical paper demonstrates that the field of signal processing has the potential to impact and help drive genomics research. Keywords and phrases functional genomics gene network genomics genomic signal processing microarray. 1. INTRODUCTION Sequences and clones for over a million expressed sequence tagged sites ESTs are currently publicly available. Only a minority of these identified clusters contains genes associated with a known functionality. One way of gaining insight into a gene s role in cellular activity is to study its expression pattern in a variety of circumstances and contexts as it responds to its environment and to the action of other genes. Recent methods facilitate large-scale .