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10.1186/1471-2105-15-128 http://scihub22266oqcxt.onion/10.1186/1471-2105-15-128 C4062517!4062517!24885091     free     free     free Warning: file_get_contents(https://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?dbfrom=pubmed&id=24885091&cmd=llinks): Failed to open stream: HTTP request failed! 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BLASTGrabber: a bioinformatic tool for visualization, analysis and sequence selection of massive BLAST data |pdf=|usr=}}{{24885091}} gab.com Text BLASTGrabber: a bioinformatic tool for visualization, analysis and sequence selection of massive BLAST data JO: BMC Bioinformatics http://www.kidney.de/pget.php?&tw=1&pmid=24885091 #FOAvip Background: Advances in sequencing efficiency have vastly increased the sizes of biological sequence databases, including many thousands of genome-sequenced species. The BLAST algorithm remains the main search engine for retrieving sequence information, and must consequently handle data on an unprecedented scale. This has been possible due to high-performance computers and parallel processing. However, the raw BLAST output from contemporary searches involving thousands of queries becomes ill-suited for direct human processing. Few programs attempt to directly visualize and interpret BLAST output; those that do often provide a mere basic structuring of BLAST data. Results: Here we present a bioinformatics application named BLASTGrabber suitable for high-throughput sequencing analysis. BLASTGrabber, being implemented as a Java application, is OS-independent and includes a user friendly graphical user interface. Text or XML-formatted BLAST output files can be directly imported, displayed and categorized based on BLAST statistics. Query names and FASTA headers can be analysed by text-mining. In addition to visualizing sequence alignments, BLAST data can be ordered as an interactive taxonomy tree. All modes of analysis support selection, export and storage of data. A Java interface-based plugin structure facilitates the addition of customized third party functionality. Conclusion: The BLASTGrabber application introduces new ways of visualizing and analysing massive BLAST output data by integrating taxonomy identification, text mining capabilities and generic multi-dimensional rendering of BLAST hits. The program aims at a non-expert audience in terms of computer skills; the combination of new functionalities makes the program flexible and useful for a broad range of operations. Twit Text FOAVip BLASTGrabber: a bioinformatic tool for visualization, analysis and sequence selection of massive BLAST data ????BMC Bioinformatics http://www.kidney.de/pget.php?&tw=1&pmid=24885091 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=24885091 #FOAvip English Wikipedia <ref>{{Cite pmid|24885091}}</ref> BLASTGrabber: a bioinformatic tool for visualization, analysis and sequence selection of massive BLAST data #MMPMID24885091 Neumann RS; Kumar S; Haverkamp THA; Shalchian-Tabrizi K BMC Bioinformatics 2014[]; 15 (ä): 128 PMID24885091show ga Background: Advances in sequencing efficiency have vastly increased the sizes of biological sequence databases, including many thousands of genome-sequenced species. The BLAST algorithm remains the main search engine for retrieving sequence information, and must consequently handle data on an unprecedented scale. This has been possible due to high-performance computers and parallel processing. However, the raw BLAST output from contemporary searches involving thousands of queries becomes ill-suited for direct human processing. Few programs attempt to directly visualize and interpret BLAST output; those that do often provide a mere basic structuring of BLAST data. Results: Here we present a bioinformatics application named BLASTGrabber suitable for high-throughput sequencing analysis. BLASTGrabber, being implemented as a Java application, is OS-independent and includes a user friendly graphical user interface. Text or XML-formatted BLAST output files can be directly imported, displayed and categorized based on BLAST statistics. Query names and FASTA headers can be analysed by text-mining. In addition to visualizing sequence alignments, BLAST data can be ordered as an interactive taxonomy tree. All modes of analysis support selection, export and storage of data. A Java interface-based plugin structure facilitates the addition of customized third party functionality. Conclusion: The BLASTGrabber application introduces new ways of visualizing and analysing massive BLAST output data by integrating taxonomy identification, text mining capabilities and generic multi-dimensional rendering of BLAST hits. The program aims at a non-expert audience in terms of computer skills; the combination of new functionalities makes the program flexible and useful for a broad range of operations. äBLASTGrabber: a bioinformatic tool for visualization, analysis and seq(epmc).pdf DeepDyve Pubget Overpricing