Clustering - Gene expression & Clustering...

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Unformatted text preview: Gene expression & Clustering Determining gene function Sequence comparison tells us if a gene is similar to another gene, e.g., in a new species Dynamic programming Approximate pattern matching Genes with similar sequence likely to have similar function Doesnt always work. Homologous genes may not be similar enough at the sequence level, to be detected this way New method to determine gene function: directly measure gene activity (DNA arrays) DNA Arrays--Technical Foundations An array works by exploiting the ability of a given mRNA molecule to hybridize to the DNA template. Using an array containing many DNA samples in an experiment, the expression levels of hundreds or thousands genes within a cell by measuring the amount of mRNA bound to each site on the array. With the aid of a computer, the amount of mRNA bound to the spots on the microarray is precisely measured, generating a profile of gene expression in the cell. May, 11, 2004 http://www.ncbi.nih.gov/About/primer/microarrays.html 3 An Introduction to Bioinformatics Algorithms www.bioalgorithms.info Gene expression Microarray gives us an n x m expression matrix I Each of n rows corresponds to a gene Each of m columns corresponds to a condition or time point Each column comes from one microarray I ( j,k ) is the expression level of gene j in condition/experiment k If two genes (rows) have similar expression profiles, then they may be related in function they may be co-regulated Clustering of Microarray Data Clusters Clustering Find groups of genes that have similar expression profiles to one another Such groups may be functionally related, and/or co-regulated Compute pairwise distance metric d ( i,j ) for every pair of genes i and j This gives an n x n distance matrix d Goal of clustering To group together genes into clusters such that Genes within a cluster have highly similar expression profiles (small d ( i,j )): homogeneity Genes in different clusters have very different expression profiles (large d ( i,j )): separation Good clustering is one that adheres to these goals A really good clustering is decided by biological interpretation of the clusters Good Clustering Bad Clustering The Points are in some multi-dimensional space Clustering problems How to measure distance/similarity ?...
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Clustering - Gene expression & Clustering...

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