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10.1186/1748-7188-9-12 http://scihub22266oqcxt.onion/10.1186/1748-7188-9-12 C4036715!4036715!24735785     free     free     free Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Algorithms+Mol+Biol 2014 ; 9 (ä): 12 Nephropedia Template TP {{tp|p=24735785|t=2014. MSARC: Multiple sequence alignment by residue clustering |pdf=|usr=}}{{24735785}} gab.com Text MSARC: Multiple sequence alignment by residue clustering JO: Algorithms Mol Biol http://www.kidney.de/pget.php?&tw=1&pmid=24735785 #FOAvip Background: Progressive methods offer efficient and reasonably good solutions to the multiple sequence alignment problem. However, resulting alignments are biased by guide-trees, especially for relatively distant sequences. Results: We propose MSARC, a new graph-clustering based algorithm that aligns sequence sets without guide-trees. Experiments on the BAliBASE dataset show that MSARC achieves alignment quality similar to the best progressive methods.Furthermore, MSARC outperforms them on sequence sets whose evolutionary distances are difficult to represent by a phylogenetic tree. These datasets are most exposed to the guide-tree bias of alignments. Availability: MSARC is available at http://bioputer.mimuw.edu.pl/msarc Twit Text FOAVip MSARC: Multiple sequence alignment by residue clustering ????Algorithms Mol Biol http://www.kidney.de/pget.php?&tw=1&pmid=24735785 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=24735785 #FOAvip English Wikipedia <ref>{{Cite pmid|24735785}}</ref> MSARC: Multiple sequence alignment by residue clustering #MMPMID24735785 Modzelewski M; Dojer N Algorithms Mol Biol 2014[]; 9 (ä): 12 PMID24735785show ga Background: Progressive methods offer efficient and reasonably good solutions to the multiple sequence alignment problem. However, resulting alignments are biased by guide-trees, especially for relatively distant sequences. Results: We propose MSARC, a new graph-clustering based algorithm that aligns sequence sets without guide-trees. Experiments on the BAliBASE dataset show that MSARC achieves alignment quality similar to the best progressive methods.Furthermore, MSARC outperforms them on sequence sets whose evolutionary distances are difficult to represent by a phylogenetic tree. These datasets are most exposed to the guide-tree bias of alignments. Availability: MSARC is available at http://bioputer.mimuw.edu.pl/msarc äMSARC: Multiple sequence alignment by residue clustering (epmc).pdf DeepDyve Pubget Overpricing