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10.4137/EBO.S40138 http://scihub22266oqcxt.onion/10.4137/EBO.S40138 C5089818!5089818!27812277     free     free     free Deprecated: Implicit conversion from float 219.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 219.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 219.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 219.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 219.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Evol+Bioinform+Online 2016 ; 12 (ä): 247-51 Nephropedia Template TP {{tp|p=27812277|t=2016. A Bioinformatics Approach for Detecting Repetitive Nested Motifs using Pattern Matching |pdf=|usr=}}{{27812277}} gab.com Text A Bioinformatics Approach for Detecting Repetitive Nested Motifs using Pattern Matching JO: Evol Bioinform Online http://www.kidney.de/pget.php?&tw=1&pmid=27812277 #FOAvip The identification of nested motifs in genomic sequences is a complex computational problem. The detection of these patterns is important to allow the discovery of transposable element (TE) insertions, incomplete reverse transcripts, deletions, and/or mutations. In this study, a de novo strategy for detecting patterns that represent nested motifs was designed based on exhaustive searches for pairs of motifs and combinatorial pattern analysis. These patterns can be grouped into three categories, motifs within other motifs, motifs flanked by other motifs, and motifs of large size. The methodology used in this study, applied to genomic sequences from the plant species Aegilops tauschii and Oryza sativa, revealed that it is possible to identify putative nested TEs by detecting these three types of patterns. The results were validated through BLAST alignments, which revealed the efficacy and usefulness of the new method, which is called Mamushka. Twit Text FOAVip A Bioinformatics Approach for Detecting Repetitive Nested Motifs using Pattern Matching ????Evol Bioinform Online http://www.kidney.de/pget.php?&tw=1&pmid=27812277 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=27812277 #FOAvip English Wikipedia <ref>{{Cite pmid|27812277}}</ref> A Bioinformatics Approach for Detecting Repetitive Nested Motifs using Pattern Matching #MMPMID27812277 Romero JR; Carballido JA; Garbus I; Echenique VC; Ponzoni I Evol Bioinform Online 2016[]; 12 (ä): 247-51 PMID27812277show ga The identification of nested motifs in genomic sequences is a complex computational problem. The detection of these patterns is important to allow the discovery of transposable element (TE) insertions, incomplete reverse transcripts, deletions, and/or mutations. In this study, a de novo strategy for detecting patterns that represent nested motifs was designed based on exhaustive searches for pairs of motifs and combinatorial pattern analysis. These patterns can be grouped into three categories, motifs within other motifs, motifs flanked by other motifs, and motifs of large size. The methodology used in this study, applied to genomic sequences from the plant species Aegilops tauschii and Oryza sativa, revealed that it is possible to identify putative nested TEs by detecting these three types of patterns. The results were validated through BLAST alignments, which revealed the efficacy and usefulness of the new method, which is called Mamushka. äA Bioinformatics Approach for Detecting Repetitive Nested Motifs using(epmc).pdf DeepDyve Pubget Overpricing