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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/41582?offset=30</link>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41736/synvisio-an-interactive-multiscale-synteny-visualization-tool-for-mcscanx</guid>
	<pubDate>Sun, 31 May 2020 02:01:14 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41736/synvisio-an-interactive-multiscale-synteny-visualization-tool-for-mcscanx</link>
	<title><![CDATA[SynVisio: An Interactive Multiscale Synteny Visualization Tool for McScanX.]]></title>
	<description><![CDATA[<p>SynVisio lets you explore the results of&nbsp;<a href="http://chibba.pgml.uga.edu/mcscan2/">McScanX</a>&nbsp;a popular synteny and collinearity detection toolkit and generate publication ready images.</p>
<p>SynVisio requires two files to run:</p>
<ul>
<li>The&nbsp;<strong>simplified gff file</strong>&nbsp;that was used as an input for a McScanX query.</li>
<li>The&nbsp;<strong>collinearity file</strong>&nbsp;generated as an output by McScanX for the same input query.</li>
<li>Optional&nbsp;<strong>track file</strong>&nbsp;in bedgraph format to annotate the generated charts.</li>
</ul>
<p>SynVisio offers different types of visualizations such as&nbsp;<strong>Linear Parallel plots</strong>,&nbsp;<strong>Hive plots</strong>,&nbsp;<strong>Stacked Parallel Plots&nbsp;</strong>and&nbsp;<strong>Dot plots</strong>. Users can configure the type of plots required and then choose the source and the target chromosomes that need to be mapped. Users also have option to download the generated visualizations in publication ready SVG or PNG formats.</p><p>Address of the bookmark: <a href="https://synvisio.github.io/#/" rel="nofollow">https://synvisio.github.io/#/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41459/jcvipython-utility-libraries-on-genome-assembly-annotation-and-comparative-genomics</guid>
	<pubDate>Tue, 17 Mar 2020 06:19:06 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41459/jcvipython-utility-libraries-on-genome-assembly-annotation-and-comparative-genomics</link>
	<title><![CDATA[JCVI:Python utility libraries on genome assembly, annotation and comparative genomics]]></title>
	<description><![CDATA[<p>Collection of Python libraries to parse bioinformatics files, or perform computation related to assembly, annotation, and comparative genomics.</p>
<p>https://github.com/tanghaibao/jcvi</p>
<p>More at https://github.com/tanghaibao/jcvi/wiki</p><p>Address of the bookmark: <a href="https://github.com/tanghaibao/jcvi" rel="nofollow">https://github.com/tanghaibao/jcvi</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43062/jcvi-utility-libraries</guid>
	<pubDate>Sat, 08 May 2021 22:04:02 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43062/jcvi-utility-libraries</link>
	<title><![CDATA[JCVI utility libraries]]></title>
	<description><![CDATA[<p><span>Collection of Python libraries to parse bioinformatics files, or perform computation related to assembly, annotation, and comparative genomics.</span></p><p>Address of the bookmark: <a href="https://github.com/tanghaibao/jcvi" rel="nofollow">https://github.com/tanghaibao/jcvi</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/file/view/13911/amino-acid-flash-tutorial</guid>
	<pubDate>Mon, 11 Aug 2014 08:58:17 -0500</pubDate>
	<link>https://bioinformaticsonline.com/file/view/13911/amino-acid-flash-tutorial</link>
	<title><![CDATA[Amino Acid Flash Tutorial]]></title>
	<description><![CDATA[<p>Protein is a part of every cell in your body, and no other nutrient plays as many different roles in keeping you alive and healthy. Protein is the building block of our body, and amino acids are the main areas of interest. We have emphasized on all 20 amino acids in this documentary movie. This documentary has been developed that emphasize on chemical structure, chemical formula, IUPAC name and other detail information of all 20 amino acids with the voice, picture with interactive button. This will be helpful for the entire biology and bioinformatics student.</p><p>How to run?</p><p>You need to install flash player or open it with web browser ( I guess you have installed flash plugin) to play.</p><p>Comment below if you like it. Thanks</p>]]></description>
	<dc:creator>Jit</dc:creator>
	<enclosure url="https://bioinformaticsonline.com/file/download/13911" length="33435911" type="application/x-shockwave-flash" />
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/file/view/42559/sample-bandage-input-file-for-visual-analysis</guid>
	<pubDate>Wed, 06 Jan 2021 03:51:50 -0600</pubDate>
	<link>https://bioinformaticsonline.com/file/view/42559/sample-bandage-input-file-for-visual-analysis</link>
	<title><![CDATA[Sample bandage input file for visual analysis]]></title>
	<description><![CDATA[<p>Sample bandage input file for visual analysis ...</p>]]></description>
	<dc:creator>Jit</dc:creator>
	<enclosure url="https://bioinformaticsonline.com/file/download/42559" length="112199" type="text/plain" />
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/39630/vespa-very-large-scale-evolutionary-and-selective-pressure-analyses</guid>
	<pubDate>Sat, 22 Jun 2019 03:07:04 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/39630/vespa-very-large-scale-evolutionary-and-selective-pressure-analyses</link>
	<title><![CDATA[VESPA: Very large-scale Evolutionary and Selective Pressure Analyses]]></title>
	<description><![CDATA[<p>find the resources we provide here useful in getting you set up to analyse and interpret your data.</p>
<p>To reference VESPA:&nbsp;<a href="https://peerj.com/preprints/1895/">https://peerj.com/preprints/1895/</a></p>
<p>Documentation is now hosted on&nbsp;<a href="http://vespa-evol.readthedocs.io/en/latest/">ReadTheDocs</a></p>
<p>&nbsp;</p>
<h2>&nbsp;</h2><p>Address of the bookmark: <a href="https://github.com/aewebb80/VESPA" rel="nofollow">https://github.com/aewebb80/VESPA</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43384/lncpipea-nextflow-based-pipeline-for-comprehensive-analyses-of-long-non-coding-rnas-from-rna-seq-datasets</guid>
	<pubDate>Fri, 17 Sep 2021 01:57:02 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43384/lncpipea-nextflow-based-pipeline-for-comprehensive-analyses-of-long-non-coding-rnas-from-rna-seq-datasets</link>
	<title><![CDATA[LncPipe:A Nextflow-based pipeline for comprehensive analyses of long non-coding RNAs from RNA-seq datasets]]></title>
	<description><![CDATA[<p><span>The pipeline was developed based on a popular workflow framework&nbsp;</span><a href="https://github.com/nextflow-io/nextflow">Nextflow</a><span>, composed of four core procedures including reads alignment, assembly, identification and quantification. It contains various unique features such as well-designed lncRNAs annotation strategy, optimized calculating efficiency, diversified classification and interactive analysis report.&nbsp;</span><a href="https://github.com/likelet/LncPipe">LncPipe</a><span>&nbsp;allows users additional control in interuppting the pipeline, resetting parameters from command line, modifying main script directly and resume analysis from previous checkpoint.</span></p>
<p>Ref&nbsp;https://www.lncrnablog.com/lncpipe-a-nextflow-based-pipeline-for-identification-and-analysis-of-long-non-coding-rnas-from-rna-seq-data/</p>
<p><img src="https://ars.els-cdn.com/content/image/1-s2.0-S1673852718301176-gr1.jpg" alt="image" style="border: 0px;"></p><p>Address of the bookmark: <a href="https://github.com/likelet/LncPipe" rel="nofollow">https://github.com/likelet/LncPipe</a></p>]]></description>
	<dc:creator>LEGE</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41941/svengine-allele-specific-and-haplotype-aware-structural-variants-simulator</guid>
	<pubDate>Sat, 04 Jul 2020 05:52:34 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41941/svengine-allele-specific-and-haplotype-aware-structural-variants-simulator</link>
	<title><![CDATA[SVEngine: Allele Specific and Haplotype Aware Structural Variants Simulator]]></title>
	<description><![CDATA[<p>SVEngine (Structural Variants Engine)</p>
<ul>
<li>SVEngine is a multi-purpose and self-contained simulator for whole genome scale spike-in of thousands of SV events of various types in both single-sample and matched sample scenarios.</li>
<li>SVEngine takes as input reference contigs in FASTA files, variant meta distribution as specified in META files (see Manual) or specific variant information as specified in VAR files (see Manual) and NEWICK files for specifying clonal phylogenetic trees in cancer.</li>
<li>SVEngine outpus alterred contigs in FASTA files, spiked-in variants in VAR files (see Manual), simulated short read in FASTQ files and aligned short reads in BAM files.</li>
</ul>
<p>&nbsp;</p><p>Address of the bookmark: <a href="https://bitbucket.org/charade/svengine/src/master/" rel="nofollow">https://bitbucket.org/charade/svengine/src/master/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/videolist/watch/2791/ncbi-psi-blast-tutorial</guid>
	<pubDate>Fri, 23 Aug 2013 02:25:02 -0500</pubDate>
	<link>https://bioinformaticsonline.com/videolist/watch/2791/ncbi-psi-blast-tutorial</link>
	<title><![CDATA[NCBI PSI-BLAST Tutorial]]></title>
	<description><![CDATA[<iframe width="" height="" src="https://www.youtube-nocookie.com/embed/T3kHEieyylk" frameborder="0" allowfullscreen></iframe>http:--www.biotechnology.jhu.edu-
Tutorial for PSI-BLAST, an extension of BLAST that uses matrix algebra. BLAST is a cornerstone bioinformatics tool at NCBI. BLAST is the
Basic Local Alignment Search tool and will protein and DNA sequences that
are related to a sequence that the user provides.]]></description>
	
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/22793/sequencing-by-xpansion</guid>
	<pubDate>Wed, 17 Jun 2015 20:58:11 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/22793/sequencing-by-xpansion</link>
	<title><![CDATA[Sequencing By Xpansion]]></title>
	<description><![CDATA[<p>Sequencing By Xpansion (SBX) is a DNA sequencing method that uses a simple biochemical reaction to encode the sequence of a DNA molecule into a highly measurable surrogate called an Xpandomer. This single molecule approach produces enough Xpandomer in a single drop reaction to sequence an entire human genome 1000X over. To achieve this, an Xpandomer replaces each DNA sequence with a sequence of large, high signal reporter molecules using the SBX molecular expansion technology. The DNA sequence is then read out as the Xpandomer reporters pass sequentially through a nanopore detector. SBX is a molecular engineering platform that benefits from core design principles that separate the multiple molecular functions. This systems approach enables efficient development and incorporation of improvements to SBX and is key to reconfiguring and optimizing Xpandomer measurement for different detection platforms.</p><p>http://www.stratosgenomics.com/stratos-genomics-technology</p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
</item>

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