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The immense volume of data resulting from DNA microarray experiments, accompanied by an increase in the number of publications discussing gene-related discoveries, presents a major data analysis challenge. Current methods for genome-wide analysis of expression data typically rely on cluster analysis of gene expression patterns. Clustering indeed reveals(More)
A dvances in computational and biological methods during the last decade have remarkably changed the scale of genome research. Sequencing machines and assembly algorithms enable sequencing complete genomes within months and even weeks. Automated gene-finding methods 1,2 expedite the identification of tens of thousands of genes in the sequenced DNA. Modern(More)
This paper presents an efficient method for constructing aligned blocks (i.e., gap-free multiple alignments) from a set of pairwise alignments. The method is more sensitive than some earlier block-constructing methods for detecting conserved sequence regions. The technique is applied to analyze conserved regions in protein prenyltransferases and to detect(More)
XREFdb supports the investigation of protein function in the context of information available through work in multiple organisms. In addition to facilitating the association of functional data among known genes from multiple organisms, XREFdb has developed strategies that provide access to information associated with as-yet unstudied genes. The database(More)
In this poster we present a new heuristic algorithm for gapless local multiple sequence alignment, also known as motif extraction, from a set of unlabeled DNA or protein sequences. When the information theoretic entropy, or more generally a maximum likelihood ratio score is used this problem is NP-hard for general motif widths (Akutsu 1998). Thus heuristics(More)
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