Use my Search Websuite to scan PubMed, PMCentral, Journal Hosts and Journal Archives, FullText. Kick-your-searchterm to multiple Engines kick-your-query now !>

A dictionary by aggregated review articles of nephrology, medicine and the life sciences Your one-stop-run pathway from word to the immediate pdf of peer-reviewed on-topic knowledge.

10.1186/s12864-016-2627-0 http://scihub22266oqcxt.onion/10.1186/s12864-016-2627-0 C4869251!4869251!27184979     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       BMC+Genomics 2016 ; 17 (ä): ä Nephropedia Template TP {{tp|p=27184979|t=2016. CRISPRDetect: A flexible algorithm to define CRISPR arrays |pdf=|usr=}}{{27184979}} gab.com Text CRISPRDetect: A flexible algorithm to define CRISPR arrays JO: BMC Genomics http://www.kidney.de/pget.php?&tw=1&pmid=27184979 #FOAvip Background: CRISPR (clustered regularly interspaced short palindromic repeats) RNAs provide the specificity for noncoding RNA-guided adaptive immune defence systems in prokaryotes. CRISPR arrays consist of repeat sequences separated by specific spacer sequences. CRISPR arrays have previously been identified in a large proportion of prokaryotic genomes. However, currently available detection algorithms do not utilise recently discovered features regarding CRISPR loci. Results: We have developed a new approach to automatically detect, predict and interactively refine CRISPR arrays. It is available as a web program and command line from bioanalysis.otago.ac.nz/CRISPRDetect. CRISPRDetect discovers putative arrays, extends the array by detecting additional variant repeats, corrects the direction of arrays, refines the repeat/spacer boundaries, and annotates different types of sequence variations (e.g. insertion/deletion) in near identical repeats. Due to these features, CRISPRDetect has significant advantages when compared to existing identification tools. As well as further support for small medium and large repeats, CRISPRDetect identified a class of arrays with ?extra-large? repeats in bacteria (repeats 44?50 nt). The CRISPRDetect output is integrated with other analysis tools. Notably, the predicted spacers can be directly utilised by CRISPRTarget to predict targets. Conclusion: CRISPRDetect enables more accurate detection of arrays and spacers and its gff output is suitable for inclusion in genome annotation pipelines and visualisation. It has been used to analyse all complete bacterial and archaeal reference genomes. Electronic supplementary material: The online version of this article (doi:10.1186/s12864-016-2627-0) contains supplementary material, which is available to authorized users. Twit Text FOAVip CRISPRDetect: A flexible algorithm to define CRISPR arrays ????BMC Genomics http://www.kidney.de/pget.php?&tw=1&pmid=27184979 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=27184979 #FOAvip English Wikipedia <ref>{{Cite pmid|27184979}}</ref> CRISPRDetect: A flexible algorithm to define CRISPR arrays #MMPMID27184979 Biswas A; Staals RH; Morales SE; Fineran PC; Brown CM BMC Genomics 2016[]; 17 (ä): ä PMID27184979show ga Background: CRISPR (clustered regularly interspaced short palindromic repeats) RNAs provide the specificity for noncoding RNA-guided adaptive immune defence systems in prokaryotes. CRISPR arrays consist of repeat sequences separated by specific spacer sequences. CRISPR arrays have previously been identified in a large proportion of prokaryotic genomes. However, currently available detection algorithms do not utilise recently discovered features regarding CRISPR loci. Results: We have developed a new approach to automatically detect, predict and interactively refine CRISPR arrays. It is available as a web program and command line from bioanalysis.otago.ac.nz/CRISPRDetect. CRISPRDetect discovers putative arrays, extends the array by detecting additional variant repeats, corrects the direction of arrays, refines the repeat/spacer boundaries, and annotates different types of sequence variations (e.g. insertion/deletion) in near identical repeats. Due to these features, CRISPRDetect has significant advantages when compared to existing identification tools. As well as further support for small medium and large repeats, CRISPRDetect identified a class of arrays with ?extra-large? repeats in bacteria (repeats 44?50 nt). The CRISPRDetect output is integrated with other analysis tools. Notably, the predicted spacers can be directly utilised by CRISPRTarget to predict targets. Conclusion: CRISPRDetect enables more accurate detection of arrays and spacers and its gff output is suitable for inclusion in genome annotation pipelines and visualisation. It has been used to analyse all complete bacterial and archaeal reference genomes. Electronic supplementary material: The online version of this article (doi:10.1186/s12864-016-2627-0) contains supplementary material, which is available to authorized users. äCRISPRDetect: A flexible algorithm to define CRISPR arrays (epmc).pdf DeepDyve Pubget Overpricing