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10.1093/bioinformatics/btu270 http://scihub22266oqcxt.onion/10.1093/bioinformatics/btu270 C4058930!4058930 !24931994     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 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 Warning: imagejpeg(C:\Inetpub\vhosts\kidney.de\httpdocs\phplern\24931994 .jpg): Failed to open stream: No such file or directory in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 117       Bioinformatics 2014 ; 30 (12 ): i274-82 Nephropedia Template TP {{tp|p=24931994 |t=2014. BlockClust: efficient clustering and classification of non-coding RNAs from short read RNA-seq profiles |pdf=|usr=}}{{24931994 }} gab.com Text BlockClust: efficient clustering and classification of non-coding RNAs from short read RNA-seq profiles JO: Bioinformatics http://www.kidney.de/pget.php?&tw=1&pmid=24931994 #FOAvip SUMMARY: Non-coding RNAs (ncRNAs) play a vital role in many cellular processes such as RNA splicing, translation, gene regulation. However the vast majority of ncRNAs still have no functional annotation. One prominent approach for putative function assignment is clustering of transcripts according to sequence and secondary structure. However sequence information is changed by post-transcriptional modifications, and secondary structure is only a proxy for the true 3D conformation of the RNA polymer. A different type of information that does not suffer from these issues and that can be used for the detection of RNA classes, is the pattern of processing and its traces in small RNA-seq reads data. Here we introduce BlockClust, an efficient approach to detect transcripts with similar processing patterns. We propose a novel way to encode expression profiles in compact discrete structures, which can then be processed using fast graph-kernel techniques. We perform both unsupervised clustering and develop family specific discriminative models; finally we show how the proposed approach is scalable, accurate and robust across different organisms, tissues and cell lines. AVAILABILITY: The whole BlockClust galaxy workflow including all tool dependencies is available at http://toolshed.g2.bx.psu.edu/view/rnateam/blockclust_workflow. Twit Text FOAVip BlockClust: efficient clustering and classification of non-coding RNAs from short read RNA-seq profiles ????Bioinformatics http://www.kidney.de/pget.php?&tw=1&pmid=24931994 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=24931994 #FOAvip English Wikipedia <ref>{{Cite pmid|24931994 }}</ref> BlockClust: efficient clustering and classification of non-coding RNAs from short read RNA-seq profiles #MMPMID24931994 Videm P ; Rose D ; Costa F ; Backofen R Bioinformatics 2014[Jun]; 30 (12 ): i274-82 PMID24931994 show ga SUMMARY: Non-coding RNAs (ncRNAs) play a vital role in many cellular processes such as RNA splicing, translation, gene regulation. However the vast majority of ncRNAs still have no functional annotation. One prominent approach for putative function assignment is clustering of transcripts according to sequence and secondary structure. However sequence information is changed by post-transcriptional modifications, and secondary structure is only a proxy for the true 3D conformation of the RNA polymer. A different type of information that does not suffer from these issues and that can be used for the detection of RNA classes, is the pattern of processing and its traces in small RNA-seq reads data. Here we introduce BlockClust, an efficient approach to detect transcripts with similar processing patterns. We propose a novel way to encode expression profiles in compact discrete structures, which can then be processed using fast graph-kernel techniques. We perform both unsupervised clustering and develop family specific discriminative models; finally we show how the proposed approach is scalable, accurate and robust across different organisms, tissues and cell lines. AVAILABILITY: The whole BlockClust galaxy workflow including all tool dependencies is available at http://toolshed.g2.bx.psu.edu/view/rnateam/blockclust_workflow. |Artificial Intelligence [MESH] |Cluster Analysis [MESH] |Gene Expression Profiling/*methods [MESH] |High-Throughput Nucleotide Sequencing [MESH] |Humans [MESH] |Molecular Sequence Annotation [MESH] |RNA, Small Untranslated/chemistry/*classification/metabolism [MESH] |Sequence Analysis, RNA/*methods [MESH]BlockClust: efficient clustering and classification of non-coding RNAs(epmc).pdf DeepDyve Pubget Overpricing