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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: Research Article TRII: A Probabilistic Scoring of Drosophila melanogaster Translation Initiation Sites | Hindawi Publishing Corporation EURASIP Journal on Bioinformatics and Systems Biology Volume 2010 Article ID814127 14 pages doi 10.1155 2010 814127 Research Article TRII A Probabilistic Scoring of Drosophila melanogaster Translation Initiation Sites Michael P. Weir1 and Michael D. Rice2 1 Department of Biology Wesleyan University Middletown CT 06459 USA 2 Department of Mathematics and Computer Science Wesleyan University Middletown CT 06459 USA Correspondence should be addressed to Michael P. Weir mweir@wesleyan.edu Received 29 April 2010 Revised 23 August 2010 Accepted 14 October 2010 Academic Editor Yufei Huang Copyright 2010 M. P. Weir and M. D. Rice. 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. Relative individual information is a measurement that scores the quality of DNA- and RNA-binding sites for biological machines. The development of analytical approaches to increase the power of this scoring method will improve its utility in evaluating the functions of motifs. In this study the scoring method was applied to potential translation initiation sites in Drosophila to compute Translation Relative Individual Information TRII scores. The weight matrix at the core of the scoring method was optimized based on high-confidence translation initiation sites identified by using a progressive partitioning approach. Comparing the distributions of TRII scores for sites of interest with those for high-confidence translation initiation sites and random sequences provides a new methodology for assessing the quality of translation initiation sites. The optimized weight matrices can also be used to describe the consensus at translation initiation sites providing a quantitative measure of preferred and avoided nucleotides at each position. 1. Introduction Understanding how biological machines work in the context of
