tailieunhanh - Báo cáo hóa học: " Editorial Genomic Signal Processing"

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: Editorial Genomic Signal Processing | Hindawi Publishing Corporation EURASIP Journal on Advances in Signal Processing Volume 2010 Article ID 137263 2 pages doi 2010 137263 Editorial Genomic Signal Processing Ulisses Braga-Neto 1 Rui Kuang 2 Harri Lahdesmaki 3 Haris Vikalo 4 and Byung-Jun Yoon1 1 Department of Electrical and Computer Engineering Texas A M University College Station TX 77843 USA 2 Department of Computer Science and Engineering University of Minnesota Twin Cities Minneapolis MN 55455 USA 3 Department of Information and Computer Science Aalto University Espoo 00076 Finland 4 Department of Electrical and Computer Engineering University of Texas Austin TX 78712 USA Correspondence should be addressed to Ulisses Braga-Neto ulisses@ Received 19 December 2010 Accepted 19 December 2010 Copyright 2010 Ulisses Braga-Neto et al. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited. Genomic signal processing GSP is the engineering discipline that aims to integrate the theory and methods of signal processing with the applications arising from high-throughput technologies in biomedical research such as gene-expression microarrays or proteinabundance mass spectrometry. GSP comprises the analysis processing and use of genomic and proteomic signals for gaining knowledge into the complex structural and functional relationships among genes and proteins in living tissue as well as the translation of that knowledge into systems-based medical applications. GSP has had a significant impact in biomedical research over the last decade and promises to revolutionize medical practice. This special issue consists of 8 papers covering a broad range of topics in bioinformatics statistical signal processing stochastic modeling pattern recognition and systems identification with applications in target estimation in microarray signals gene .