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10.1093/bioinformatics/btx114 http://scihub22266oqcxt.onion/10.1093/bioinformatics/btx114 C5870858!5870858!28334186     free     free     free Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Bioinformatics 2017 ; 33 (14): 2089-96 Nephropedia Template TP {{tp|p=28334186|t=2017. RNAscClust: clustering RNA sequences using structure conservation and graph based motifs |pdf=|usr=}}{{28334186}} gab.com Text RNAscClust: clustering RNA sequences using structure conservation and graph based motifs JO: Bioinformatics http://www.kidney.de/pget.php?&tw=1&pmid=28334186 #FOAvip Motivation: Clustering RNA sequences with common secondary structure is an essential step towards studying RNA function. Whereas structural RNA alignment strategies typically identify common structure for orthologous structured RNAs, clustering seeks to group paralogous RNAs based on structural similarities. However, existing approaches for clustering paralogous RNAs, do not take the compensatory base pair changes obtained from structure conservation in orthologous sequences into account. Results: Here, we present RNAscClust, the implementation of a new algorithm to cluster a set of structured RNAs taking their respective structural conservation into account. For a set of multiple structural alignments of RNA sequences, each containing a paralog sequence included in a structural alignment of its orthologs, RNAscClust computes minimum free-energy structures for each sequence using conserved base pairs as prior information for the folding. The paralogs are then clustered using a graph kernel-based strategy, which identifies common structural features. We show that the clustering accuracy clearly benefits from an increasing degree of compensatory base pair changes in the alignments. Availability and Implementation: RNAscClust is available at http://www.bioinf.uni-freiburg.de/Software/RNAscClust. Supplementary information: Supplementary data are available at Bioinformatics online. Twit Text FOAVip RNAscClust: clustering RNA sequences using structure conservation and graph based motifs ????Bioinformatics http://www.kidney.de/pget.php?&tw=1&pmid=28334186 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=28334186 #FOAvip English Wikipedia <ref>{{Cite pmid|28334186}}</ref> RNAscClust: clustering RNA sequences using structure conservation and graph based motifs #MMPMID28334186 Miladi M; Junge A; Costa F; Seemann SE; Havgaard JH; Gorodkin J; Backofen R Bioinformatics 2017[Jul]; 33 (14): 2089-96 PMID28334186show ga Motivation: Clustering RNA sequences with common secondary structure is an essential step towards studying RNA function. Whereas structural RNA alignment strategies typically identify common structure for orthologous structured RNAs, clustering seeks to group paralogous RNAs based on structural similarities. However, existing approaches for clustering paralogous RNAs, do not take the compensatory base pair changes obtained from structure conservation in orthologous sequences into account. Results: Here, we present RNAscClust, the implementation of a new algorithm to cluster a set of structured RNAs taking their respective structural conservation into account. For a set of multiple structural alignments of RNA sequences, each containing a paralog sequence included in a structural alignment of its orthologs, RNAscClust computes minimum free-energy structures for each sequence using conserved base pairs as prior information for the folding. The paralogs are then clustered using a graph kernel-based strategy, which identifies common structural features. We show that the clustering accuracy clearly benefits from an increasing degree of compensatory base pair changes in the alignments. Availability and Implementation: RNAscClust is available at http://www.bioinf.uni-freiburg.de/Software/RNAscClust. Supplementary information: Supplementary data are available at Bioinformatics online. äRNAscClust: clustering RNA sequences using structure conservation and (epmc).pdf DeepDyve Pubget Overpricing