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  • 1
    Publication Date: 2012-08-25
    Description: Motivation: Today many non-coding RNAs are known to play an active role in various important biological processes. Since RNA's functionality is correlated with specific structural motifs that are often conserved in phylogenetically related molecules, computational prediction of RNA structure should ideally be based on a set of homologous primary structures. But many available RNA secondary structure prediction programs that use sequence alignments do not consider pseudoknots or their estimations consist on a single structure without information on uncertainty. Results: In this article we present a method that takes advantage of the evolutionary history of a group of aligned RNA sequences for sampling consensus secondary structures, including pseudoknots, according to their approximate posterior probability. We investigate the benefit of using evolutionary history and demonstrate the competitiveness of our method compared with similar methods based on RNase P RNA sequences and simulated data. Availability: PhyloQFold, a C + + implementation of our method, is freely available from http://evol.bio.lmu.de/_statgen/software/phyloqfold/ Contact: gero@bioinf.uni-leipzig.de, metzler@bio.lmu.de Supplementary information: Supplementary data are available at Bioinformatics online.
    Print ISSN: 1367-4803
    Electronic ISSN: 1460-2059
    Topics: Biology , Computer Science , Medicine
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  • 2
    Publication Date: 2009-05-16
    Description: Sequence preferences of DNA binding proteins are a primary mechanism by which cells interpret the genome. Despite the central importance of these proteins in physiology, development, and evolution, comprehensive DNA binding specificities have been determined experimentally for only a few proteins. Here, we used microarrays containing all 10-base pair sequences to examine the binding specificities of 104 distinct mouse DNA binding proteins representing 22 structural classes. Our results reveal a complex landscape of binding, with virtually every protein analyzed possessing unique preferences. Roughly half of the proteins each recognized multiple distinctly different sequence motifs, challenging our molecular understanding of how proteins interact with their DNA binding sites. This complexity in DNA recognition may be important in gene regulation and in the evolution of transcriptional regulatory networks.〈br /〉〈br /〉〈a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2905877/" target="_blank"〉〈img src="https://static.pubmed.gov/portal/portal3rc.fcgi/4089621/img/3977009" border="0"〉〈/a〉   〈a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2905877/" target="_blank"〉This paper as free author manuscript - peer-reviewed and accepted for publication〈/a〉〈br /〉〈br /〉〈span class="detail_caption"〉Notes: 〈/span〉Badis, Gwenael -- Berger, Michael F -- Philippakis, Anthony A -- Talukder, Shaheynoor -- Gehrke, Andrew R -- Jaeger, Savina A -- Chan, Esther T -- Metzler, Genita -- Vedenko, Anastasia -- Chen, Xiaoyu -- Kuznetsov, Hanna -- Wang, Chi-Fong -- Coburn, David -- Newburger, Daniel E -- Morris, Quaid -- Hughes, Timothy R -- Bulyk, Martha L -- R01 HG003985/HG/NHGRI NIH HHS/ -- R01 HG003985-01/HG/NHGRI NIH HHS/ -- R01 HG003985-02/HG/NHGRI NIH HHS/ -- R01 HG003985-03/HG/NHGRI NIH HHS/ -- New York, N.Y. -- Science. 2009 Jun 26;324(5935):1720-3. doi: 10.1126/science.1162327. Epub 2009 May 14.〈br /〉〈span class="detail_caption"〉Author address: 〈/span〉Banting and Best Department of Medical Research, University of Toronto, Toronto, ON M5S 3E1, Canada.〈br /〉〈span class="detail_caption"〉Record origin:〈/span〉 〈a href="http://www.ncbi.nlm.nih.gov/pubmed/19443739" target="_blank"〉PubMed〈/a〉
    Keywords: Amino Acid Motifs ; Amino Acid Sequence ; Animals ; Base Sequence ; Binding Sites ; DNA/chemistry/*metabolism ; Electrophoretic Mobility Shift Assay ; Gene Expression Regulation ; Gene Regulatory Networks ; Humans ; Mice ; Protein Array Analysis ; Protein Binding ; Protein Structure, Tertiary ; Recombinant Fusion Proteins/chemistry/metabolism ; Transcription Factors/*chemistry/*metabolism
    Print ISSN: 0036-8075
    Electronic ISSN: 1095-9203
    Topics: Biology , Chemistry and Pharmacology , Computer Science , Medicine , Natural Sciences in General , Physics
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  • 3
    Publication Date: 2001-06-11
    Print ISSN: 0031-9007
    Electronic ISSN: 1079-7114
    Topics: Physics
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