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IEEE Computer Society Bioinformatics Conference (CSB'03)   p. 277
SMASHing regulatory sites in DNA by human-mouse sequence comparisons
Mihaela Zavolan, The Rockefeller University
Nicholas D. Socci, Albert Einstein College of Medicine
Nikolaus Rajewsky, New York University
Terry Gaasterlamd, The Rockefeller University

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DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/CSB.2003.1227328
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Abstract
Regulatory sequence elements provide important clues to understanding and predicting gene expression. Although the binding sites for hundreds of transcription factors are known, there has been no systematic attempt to incorporate this information in the annotation of the human genome. Cross species sequence comparisons are critical to a meaningful annotation of regulatory elements since they generally reside in conserved non-coding regions. To take advantage of the recently completed drafts of the mouse and human genomes for annotating transcription factor binding sites, we developed SMASH, a computational pipeline that identifies thousands of orthologous human/ mouse proteins, maps them to genomic sequences, extracts and compares upstream regions and annotates putative regulatory elements in conserved, non-coding, upstream regions. Our current dataset consists of approximately 2500 human/mouse gene pairs. Transcription start sites were estimated by mapping quasi-full length cDNA sequences. SMASH uses a novel probabilistic method to identify putative conserved binding sites that takes into account the competition between transcription factors for binding DNA. SMASH presents the results via a genome browser web interface which displays the predicted regulatory information together with the current annotations for the human genome. Our results are validated by comparison to previously published experimental data. SMASH results compare favorably to other existing computational approaches.
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Citation:  Mihaela Zavolan, Nicholas D. Socci, Nikolaus Rajewsky, Terry Gaasterlamd, "SMASHing regulatory sites in DNA by human-mouse sequence comparisons," csb, p. 277,  IEEE Computer Society Bioinformatics Conference (CSB'03),  2003