TY - JOUR AU1 - Eric P. Xing, Richard M. Karp AB - We present CLIFF, an algorithm for clustering biological samples using gene expression microarray data. This clustering problem is difficult for several reasons, in particular the sparsity of the data, the high dimensionality of the feature (gene) space, and the fact that many features are irrelevant or redundant. Our algorithm iterates between two computational processes, feature filtering and clustering. Given a reference partition that approximates the correct clustering of the samples, our feature filtering procedure ranks the features according to their intrinsic discriminability, relevance to the reference partition, and irredundancy to other relevant features, and uses this ranking to select the features to be used in the following round of clustering. Our clustering algorithm, which is based on the concept of a normalized cut, clusters the samples into a new reference partition on the basis of the selected features. On a well-studied problem involving 72 leukemia samples and 7130 genes, we demonstrate that CLIFF outperforms standard clustering approaches that do not consider the feature selection issue, and produces a result that is very close to the original expert labeling of the sample set. Contact: epxing@cs.berkeley.edu © Oxford University Press 2001 « Previous | Next Article » Table of Contents This Article Bioinformatics (2001) 17 (suppl 1): S306-S315. doi: 10.1093/bioinformatics/17.suppl_1.S306 This article appears in: Proceedings for the Ninth international Conference on Intelligent Systems for Molecular Biology » Abstract Free Full Text (PDF) Free Classifications Original Paper Services Article metrics Alert me when cited Alert me if corrected Alert me if commented Find similar articles Similar articles in Web of Science Similar articles in PubMed Add to my archive Download citation Request Permissions Responses Submit a response No responses published Citing Articles Load citing article information Citing articles via CrossRef Citing articles via Scopus Citing articles via Web of Science Citing articles via Google Scholar Google Scholar Articles by Xing, E. P. Articles by Karp, R. M. Search for related content PubMed PubMed citation Articles by Xing, E. P. 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