GATA: A graphic alignment tool for comparative sequenceanalysis

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Several problems exist with current methods used to align DNA sequences for comparative sequence analysis. Most dynamic programming algorithms assume that conserved sequence elements are collinear. This assumption appears valid when comparing orthologous protein coding sequences. Functional constraints on proteins provide strong selective pressure against sequence inversions, and minimize sequence duplications and feature shuffling. For non-coding sequences this collinearity assumption is often invalid. For example, enhancers contain clusters of transcription factor binding sites that change in number, orientation, and spacing during evolution yet the enhancer retains its activity. Dotplot analysis is often used to estimate non-coding sequence relatedness. Yet dot ... continued below

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Nix, David A. & Eisen, Michael B. January 1, 2005.

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Several problems exist with current methods used to align DNA sequences for comparative sequence analysis. Most dynamic programming algorithms assume that conserved sequence elements are collinear. This assumption appears valid when comparing orthologous protein coding sequences. Functional constraints on proteins provide strong selective pressure against sequence inversions, and minimize sequence duplications and feature shuffling. For non-coding sequences this collinearity assumption is often invalid. For example, enhancers contain clusters of transcription factor binding sites that change in number, orientation, and spacing during evolution yet the enhancer retains its activity. Dotplot analysis is often used to estimate non-coding sequence relatedness. Yet dot plots do not actually align sequences and thus cannot account well for base insertions or deletions. Moreover, they lack an adequate statistical framework for comparing sequence relatedness and are limited to pairwise comparisons. Lastly, dot plots and dynamic programming text outputs fail to provide an intuitive means for visualizing DNA alignments.

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  • Journal Name: BMC Bioinformatics; Journal Volume: 6; Journal Issue: 9; Related Information: Journal Publication Date: 2005

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  • Report No.: LBNL--56803
  • Grant Number: DE-AC02-05CH11231
  • Office of Scientific & Technical Information Report Number: 861245
  • Archival Resource Key: ark:/67531/metadc786264

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  • January 1, 2005

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  • Dec. 3, 2015, 9:30 a.m.

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  • April 1, 2016, 8:02 p.m.

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Nix, David A. & Eisen, Michael B. GATA: A graphic alignment tool for comparative sequenceanalysis, article, January 1, 2005; Berkeley, California. (digital.library.unt.edu/ark:/67531/metadc786264/: accessed August 17, 2017), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.