tailieunhanh - Báo cáo sinh học: " P-value based visualization of codon usage data"

Tuyển tập các báo cáo nghiên cứu về sinh học được đăng trên tạp chí y học Molecular Biology cung cấp cho các bạn kiến thức về ngành sinh học đề tài: P-value based visualization of codon usage data. | Algorithms for Molecular Biology BioMed Central Open Access P-value based visualization of codon usage data Peter Meinicke 1 Thomas Brodag2 Wolfgang Florian Fricke3 and Stephan Waack2 Address 1Abteilung Bioinformatik Institut fur Mikrobiologie und Genetik Georg-August-Universitat Gottingen Goldschmidtstr. 1 37077 Gottingen Germany 2Institut fur Numerische und Angewandte Mathematik Universitat Gottingen Lotzestr. 16 37083 Gottingen Germany and 3Gottingen Genomics Laboratory Universitat Gottingen Grisebachstr. 8 37077 Gottingen Germany Email Peter Meinicke - pmeinic@ Thomas Brodag - Wolfgang Florian Fricke - wfricke@ Stephan Waack - waack@ Corresponding author Published 29 June 2006 Received 13 March 2006 Algorithms for Molecular Biology 2006 1 10 doi 1748-7188-1-10 Accepted 29 June 2006 This article is available from http content 1 1 10 2006 Meinicke et al licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License http licenses by which permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited. Abstract_ Two important and not yet solved problems in bacterial genome research are the identification of horizontally transferred genes and the prediction of gene expression levels. Both problems can be addressed by multivariate analysis of codon usage data. In particular dimensionality reduction methods for visualization of multivariate data have shown to be effective tools for codon usage analysis. We here propose a multidimensional scaling approach using a novel similarity measure for codon usage tables. Our probabilistic similarity measure is based on P-values derived from the well-known chi-square test for comparison of two distributions. .