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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 Information Theoretic Methods for Bioinformatics | Hindawi Publishing Corporation EURASIP Journal on Bioinformatics and Systems Biology Volume 2007 Article ID 79128 2 pages doi 10.1155 2007 79128 Editorial Information Theoretic Methods for Bioinformatics Jorma Rissanen 1 2 Peter Grunwald 3 Jukka Heikkonen 4 Petri Myllymaki 2 5 Teemu Roos 2 5 and Juho Rousu5 1 Computer Learning Research Center University of London Royal Holloway TW20 0EX UK 2 Helsinki Institute for Information Technology University of Helsinki P.O. Box 68 00014 Helsinki Finland 3 Centrum voor Wiskunde en Informatica CWI P.O. Box 94079 1090 GB Amsterdam The Netherlands 4 Laboratory of Computational Engineering Helsinki University of Technology P.O. Box 9203 02015 HUT Finland 5 Department of Computer Science University of Helsinki P. O. Box 68 00014 Helsinki Finland Received 24 December 2007 Accepted 24 December 2007 Copyright 2007 Jorma Rissanen 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. The ever-ongoing growth in the amount of biological data the development of genome-wide measurement technologies and the gradual inevitable shift in molecular biology from the study of individual genes to the systems view all these factors contribute to the need to study biological systems by statistical and computational means. In this task we are facing a dual challenge on the one hand biological systems and hence their models are inherently complex and on the other hand the measurement data while being genomewide are typically scarce in terms of sample sizes the large p small n problem and noisy. This means that the traditional statistical approach where the model is viewed as a distorted image of something called a true distribution which the statisticians are trying to estimate is poorly justified. This lack of rationality is particularly striking when one tries to learn the structure of .
