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 Clustering of Gene Expression Data Based on Shape Similarity | Hindawi Publishing Corporation EURASIP Journal on Bioinformatics and Systems Biology Volume 2009 Article ID 195712 12 pages doi 2009 195712 Research Article Clustering of Gene Expression Data Based on Shape Similarity Travis J. Hestilow1 and Yufei Huang1 2 1 Department of Electrical and Computer Engineering The University of Texas at San Antonio San Antonio TX 78249 USA 2 Greehey Children s Cancer Research Institute University of Texas Health Science Center at San Antonio TX 78229 USA Correspondence should be addressed to Yufei Huang Received 4 August 2008 Revised 8 January 2009 Accepted 27 January 2009 Recommended by Erchin Serpedin A method for gene clustering from expression profiles using shape information is presented. The conventional clustering approaches such as K-means assume that genes with similar functions have similar expression levels and hence allocate genes with similar expression levels into the same cluster. However genes with similar function often exhibit similarity in signal shape even though the expression magnitude can be far apart. Therefore this investigation studies clustering according to signal shape similarity. This shape information is captured in the form of normalized and time-scaled forward first differences which then are subject to a variational Bayes clustering plus a non-Bayesian Silhouette cluster statistic. The statistic shows an improved ability to identify the correct number of clusters and assign the components of cluster. Based on initial results for both generated test data and Escherichia coli microarray expression data and initial validation of the Escherichia coli results it is shown that the method has promise in being able to better cluster time-series microarray data according to shape similarity. Copyright 2009 T. J. Hestilow and Y. Huang. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use distribution and .
