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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/36109?offset=60</link>
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	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/33887/gview-a-java-application-for-viewing-and-examining-prokaryotic-genomes-in-a-circular-or-linear-context</guid>
	<pubDate>Fri, 14 Jul 2017 07:47:03 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/33887/gview-a-java-application-for-viewing-and-examining-prokaryotic-genomes-in-a-circular-or-linear-context</link>
	<title><![CDATA[GView: A Java application for viewing and examining prokaryotic genomes in a circular or linear context]]></title>
	<description><![CDATA[<p>GView is a Java application for viewing and examining prokaryotic genomes in a circular or linear context. It accepts standard sequence file formats and an optional style specification file to generate customizable, publication quality genome maps in bitmap and scalable vector graphics formats. GView features an interactive pan-and-zoom interface, a command-line interface for incorporation in genome analysis pipelines, and a public Application Programming Interface for incorporation in other Java applications.</p>
<p><strong>Availability:</strong>&nbsp;GView is a freely available application licensed under the GNU Public License. The application, source code, documentation, file specifications, tutorials and image galleries are available at&nbsp;<a href="http://gview.ca/" target="pmc_ext">http://gview.ca</a></p>
<p><strong>Contact:</strong>&nbsp;<a href="mailto:dev@null">ac.cg.cpsa-cahp@raalesmod.nav.yrag</a></p>
<p>https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2995121/</p><p>Address of the bookmark: <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2995121/" rel="nofollow">https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2995121/</a></p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/17966/internship-program-for-bioinformatics-biotechnology-professionals-no-of-vacancy-2</guid>
  <pubDate>Wed, 08 Oct 2014 01:10:08 -0500</pubDate>
  <link></link>
  <title><![CDATA[Internship Program for Bioinformatics / Biotechnology Professionals (No. Of Vacancy: 2)]]></title>
  <description><![CDATA[
<p>ArrayGen is offering an Internship Program for Post graduate Bioinformatics / Biotechnology students and professionals. ArrayGen Technologies provide an excellent opportunity to gain research experience and explore if a scientific career is right for you. Currently we offer positions to outstanding students interested in Next Generation Sequencing (NGS) data analysis. Applications are accepted throughout the year. Accepted students will be listed on web with their schedules. Accepted students can attend our future workshops and trainings freely at the specified venue.</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/31100/vaguevelvet-assembler-graphical-front-end</guid>
	<pubDate>Fri, 24 Feb 2017 08:56:49 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/31100/vaguevelvet-assembler-graphical-front-end</link>
	<title><![CDATA[VAGUE:Velvet Assembler Graphical Front End]]></title>
	<description><![CDATA[<p>VAGUE is a vague acronym for "Velvet Assembler Graphical Front End", which means it is a GUI for the Velvet <em>de novo</em> assembler. The command line version of Velvet can be complicated for beginners to use, but VAGUE makes it clear and simple</p>
<p>More at&nbsp;http://www.vicbioinformatics.com/software.vague.shtml</p><p>Address of the bookmark: <a href="http://www.vicbioinformatics.com/software.vague.shtml" rel="nofollow">http://www.vicbioinformatics.com/software.vague.shtml</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/29276/murasaki</guid>
	<pubDate>Fri, 30 Sep 2016 10:22:30 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/29276/murasaki</link>
	<title><![CDATA[Murasaki]]></title>
	<description><![CDATA[<p>Murasaki is an anchor alignment program that is</p>
<ul style="margin-left: 16px;">
<li>exteremely fast (17 CPU hours for whole Human x Mouse genome (with 40 nodes: 35 wall minutes), or 8 mammals in 21 CPU hours (42 wall minutes))</li>
<li>scalable (Arbitrarily parallelizable across multiple nodes using MPI)</li>
<li>memory efficient. (Even a single node with 16GB of ram can handle over 1Gbp of sequence)</li>
<li>unlimited by pattern length or selection</li>
<li>repeat tolerant</li>
</ul>
<p><img src="http://murasaki.dna.bio.keio.ac.jp/9mammals-small.png" width="500" height="375" alt="image" style="border: 0px;"></p><p>Address of the bookmark: <a href="http://murasaki.dna.bio.keio.ac.jp/wiki/index.php?Murasaki" rel="nofollow">http://murasaki.dna.bio.keio.ac.jp/wiki/index.php?Murasaki</a></p>]]></description>
	<dc:creator>Anjana</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/30966/maftools</guid>
	<pubDate>Thu, 16 Feb 2017 11:16:01 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/30966/maftools</link>
	<title><![CDATA[MafTools]]></title>
	<description><![CDATA[<p>maftools - An R package to summarize, analyze and visualize MAF files. <a href="https://github.com/PoisonAlien/maftools#introduction"></a>Introduction.</p>
<p>With advances in Cancer Genomics, Mutation Annotation Format (MAF) is being widley accepted and used to store variants detected. <a href="http://cancergenome.nih.gov">The Cancer Genome Atlas</a> Project has seqenced over 30 different cancers with sample size of each cancer type being over 200. The <a href="https://wiki.nci.nih.gov/display/TCGA/TCGA+MAF+Files">resulting data</a> consisting of genetic variants is stored in the form of <a href="https://wiki.nci.nih.gov/display/TCGA/Mutation+Annotation+Format+%28MAF%29+Specification">Mutation Annotation Format</a>. This package attempts to summarize, analyze, annotate and visualize MAF files in an efficient manner either from TCGA sources or any in-house studies as long as the data is in MAF format. Maftools can also handle ICGC Simple Somatic Mutation format.</p>
<p>maftools is on <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f449.png" alt=":point_right:" width="20" height="20" style="border: 0px;"> <a href="http://biorxiv.org/content/early/2016/05/11/052662">bioRxiv</a> <img src="https://assets-cdn.github.com/images/icons/emoji/bowtie.png" alt=":bowtie:" title=":bowtie:" width="20" height="20" style="border: 0px; text-align: absmiddle;"></p>
<p>Please cite the below if you find this tool useful for you.</p>
<p>Mayakonda, A. and H.P. Koeffler, Maftools: Efficient analysis, visualization and summarization of MAF files from large-scale cohort based cancer studies. bioRxiv, 2016. doi: <a href="http://dx.doi.org/10.1101/052662">http://dx.doi.org/10.1101/052662</a></p><p>Address of the bookmark: <a href="https://github.com/PoisonAlien/maftools" rel="nofollow">https://github.com/PoisonAlien/maftools</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/31371/phenogram</guid>
	<pubDate>Tue, 07 Mar 2017 08:35:12 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/31371/phenogram</link>
	<title><![CDATA[PhenoGram]]></title>
	<description><![CDATA[<p><span>With PhenoGram researchers can create chomosomal ideograms annotated with lines in color at specific base-pair locations, or colored base-pair to base-pair regions, with or without other annotation. PhenoGram allows for annotation of chromosomal locations and/or regions with shapes in different colors, gene identifiers, or other text. PhenoGram also allows for creation of plots showing expanded chromosomal locations, providing a way to show results for specific chromosomal regions in greater detail.</span></p><p>Address of the bookmark: <a href="http://ritchielab.psu.edu/software/phenogram-downloads" rel="nofollow">http://ritchielab.psu.edu/software/phenogram-downloads</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41571/wego-simple-but-useful-tool-for-visualizing-comparing-and-plotting-go-gene-ontology-annotation-results</guid>
	<pubDate>Sun, 12 Apr 2020 10:02:22 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41571/wego-simple-but-useful-tool-for-visualizing-comparing-and-plotting-go-gene-ontology-annotation-results</link>
	<title><![CDATA[WEGO : simple but useful tool for visualizing, comparing and plotting GO (Gene Ontology) annotation results]]></title>
	<description><![CDATA[<p><span>WEGO (Web Gene Ontology Annotation Plot) is a simple but useful tool for visualizing, comparing and plotting GO (Gene Ontology) annotation results. As the GO vocabulary became more and more popular, WEGO was widely adopted and used in many researches. Therefore we have updated WEGO 2.0 in 2018. Here are some changes we&rsquo;ve made:</span><br><span>1. The limit of input file numbers was cancelled. Now the users could upload as many files as they want with one operation.</span><br><span>2. We have added the reference data of 9 species for users selection.</span><br><span>3. Besides the traditional WEGO histogram, WEGO 2.0 outputs an additional type of bar graph showing GO terms with significant gene number differences.</span></p><p>Address of the bookmark: <a href="http://wego.genomics.org.cn/" rel="nofollow">http://wego.genomics.org.cn/</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38166/pygenometracks-standalone-program-and-library-to-plot-beautiful-genome-browser-tracks</guid>
	<pubDate>Fri, 09 Nov 2018 12:34:23 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38166/pygenometracks-standalone-program-and-library-to-plot-beautiful-genome-browser-tracks</link>
	<title><![CDATA[pyGenomeTracks: Standalone program and library to plot beautiful genome browser tracks]]></title>
	<description><![CDATA[<p>pyGenomeTracks aims to produce high-quality genome browser tracks that are highly customizable. Currently, it is possible to plot:</p>
<ul>
<li>bigwig</li>
<li>bed (many options)</li>
<li>bedgraph</li>
<li>links (represented as arcs)</li>
<li>Hi-C matrices (if&nbsp;<a href="http://hicexplorer.readthedocs.io/">HiCExplorer</a>&nbsp;is installed)</li>
</ul><p>Address of the bookmark: <a href="https://github.com/deeptools/pyGenomeTracks" rel="nofollow">https://github.com/deeptools/pyGenomeTracks</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40991/jtools-more-efficient-presentation-of-regression-analyses</guid>
	<pubDate>Tue, 11 Feb 2020 23:10:49 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40991/jtools-more-efficient-presentation-of-regression-analyses</link>
	<title><![CDATA[jtools : more efficient presentation of regression analyses]]></title>
	<description><![CDATA[<p>This package consists of a series of functions created by the author (Jacob) to automate otherwise tedious research tasks. At this juncture, the unifying theme is the more efficient presentation of regression analyses. There are a number of functions for other programming and statistical purposes as well. Support for the&nbsp;<code>survey</code>&nbsp;package&rsquo;s&nbsp;<code>svyglm</code>&nbsp;objects as well as weighted regressions is a common theme throughout.</p>
<p><strong>Notice:</strong>&nbsp;As of&nbsp;<code>jtools</code>&nbsp;version 2.0.0, all functions dealing with interactions (e.g.,&nbsp;<code>interact_plot()</code>,&nbsp;<code>sim_slopes()</code>,&nbsp;<code>johnson_neyman()</code>) have been moved to a new package, aptly named&nbsp;<a href="https://interactions.jacob-long.com/"><code>interactions</code></a>.</p><p>Address of the bookmark: <a href="https://cran.r-project.org/web/packages/jtools/readme/README.html" rel="nofollow">https://cran.r-project.org/web/packages/jtools/readme/README.html</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44182/collection-of-graph-visualization-tools</guid>
	<pubDate>Wed, 25 Jan 2023 02:57:42 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44182/collection-of-graph-visualization-tools</link>
	<title><![CDATA[Collection of Graph Visualization tools !]]></title>
	<description><![CDATA[<p>Standard approaches to genome inference and analysis relate sequences to a single linear reference genome. This is efficient but has a fundamental problem: Differences from this reference are hard to observe and describe in a coherent way. Variation and sequence are separated.</p>
<p><a href="https://pangenome.github.io/images/genomic-vs-pangenomic-analysis.png"><img src="https://pangenome.github.io/images/genomic-vs-pangenomic-analysis.png" alt="image" width="45%" style="border: 0px; border: 0px;"></a><span>&nbsp;</span><a href="https://pangenome.github.io/images/genomic-vs-pangenomic-models.png"><img src="https://pangenome.github.io/images/genomic-vs-pangenomic-models.png" alt="image" width="54%" style="border: 0px; border: 0px;"></a></p>
<p><a href="https://fungidb.org/fungidb/app/downloads/Current_Release/GultimumBR650/" target="_blank">https://fungidb.org/fungidb/app/downloads/Current_Release/GultimumBR650/</a></p><p>Address of the bookmark: <a href="https://pangenome.github.io/" rel="nofollow">https://pangenome.github.io/</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
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