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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/19090?offset=1450</link>
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	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36109/sankeynetwork-with-networkd3</guid>
	<pubDate>Fri, 06 Apr 2018 12:07:55 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36109/sankeynetwork-with-networkd3</link>
	<title><![CDATA[sankeyNetwork with networkD3]]></title>
	<description><![CDATA[<p><span>You can also create&nbsp;</span><a href="http://en.wikipedia.org/wiki/Sankey_diagram">Sankey diagrams</a><span>&nbsp;with&nbsp;</span><code>sankeyNetwork</code><span>. Here is an example using downloaded JSON data:</span></p>
<p><span>https://en.wikipedia.org/wiki/Sankey_diagram</span></p><p>Address of the bookmark: <a href="https://christophergandrud.github.io/networkD3/#sankey" rel="nofollow">https://christophergandrud.github.io/networkD3/#sankey</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36907/higlass-a-tool-for-exploring-genomic-contact-matrices-and-tracks</guid>
	<pubDate>Mon, 11 Jun 2018 09:44:49 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36907/higlass-a-tool-for-exploring-genomic-contact-matrices-and-tracks</link>
	<title><![CDATA[HiGlass: a tool for exploring genomic contact matrices and tracks.]]></title>
	<description><![CDATA[HiGlass is a tool for exploring genomic contact matrices and tracks. Please take a look at the examples and documentation for a description of the ways that it can be configured to explore and compare contact matrices. To load private data, HiGlass can be run locally within a Docker container. The HiC data in the examples below is from Rao et al. (2014)

http://higlass.io/<p>Address of the bookmark: <a href="http://higlass.io/" rel="nofollow">http://higlass.io/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38745/osprey-network-visualization-system</guid>
	<pubDate>Sun, 20 Jan 2019 05:34:24 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38745/osprey-network-visualization-system</link>
	<title><![CDATA[Osprey: Network Visualization System]]></title>
	<description><![CDATA[<p>Osprey is a software platform for the visualization of complex biological interaction networks. Osprey builds data-rich graphical representations from&nbsp;<a href="http://geneontology.org/" title="GENE ONTOLOGY CONSORTIUM">Gene Ontology (GO)</a>&nbsp;annotated interaction data maintained by the&nbsp;<a href="https://thebiogrid.org/" title="The BioGRID">BioGRID</a>.</p>
<p>Osprey is developed by the&nbsp;<a href="http://www.tyerslab.com/">TyersLab</a>&nbsp;and is a part of the&nbsp;<a href="https://thebiogrid.org/" title="The BioGRID">BioGRID</a>&nbsp;family of software. It utilizes both&nbsp;<a href="https://www.mysql.com/" title="MySQL Database">MySQL</a>&nbsp;and&nbsp;<a href="http://openjdk.java.net/" title="OpenJDK">Java</a>&nbsp;to operate and is compatible with&nbsp;<a href="https://www.microsoft.com/en-us/windows/" title="Microsoft Windows">Windows</a>,&nbsp;<a href="http://www.ubuntu.com/">Linux</a>, and&nbsp;<a href="http://www.apple.com/" title="Apple">Apple</a>&nbsp;operating systems.</p>
<p>These works were published in&nbsp;<strong>Breitkreutz, BJ., Stark, C., Tyers M. "Osprey: A Network Visualization System." Genome Biology 2003 4(3):R22</strong>&nbsp;<a href="http://genomebiology.com/2003/4/3/R22" title="Genome Biology">[Genome Biology]</a>&nbsp;<a href="http://genomebiology.com/content/pdf/gb-2003-4-3-r22.pdf" title="Osprey PDF">[PDF]</a>&nbsp;<a href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&amp;db=PubMed&amp;list_uids=12620107&amp;dopt=Abstract" title="Pubmed">[PubMed]</a>&nbsp;and supported by the&nbsp;<a href="http://www.nih.gov/" title="NIH">National Institutes of Health</a>,&nbsp;<a href="http://www.cihr-irsc.gc.ca/" title="CIHR">Canadian Institutes of Health Research</a>, and&nbsp;<a href="http://www.genomecanada.ca/en/" title="Genome Canada">Genome Canada</a>.</p><p>Address of the bookmark: <a href="https://osprey.thebiogrid.org/" rel="nofollow">https://osprey.thebiogrid.org/</a></p>]]></description>
	<dc:creator>BioJoker</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41209/juicebox-visualization-and-analysis-software-for-hi-c-data</guid>
	<pubDate>Fri, 21 Feb 2020 00:33:38 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41209/juicebox-visualization-and-analysis-software-for-hi-c-data</link>
	<title><![CDATA[Juicebox: Visualization and analysis software for Hi-C data]]></title>
	<description><![CDATA[<p>Juicebox is visualization software for Hi-C data. This distribution includes the source code for Juicebox,&nbsp;<a href="https://github.com/theaidenlab/juicer/wiki/Download">Juicer Tools</a>, and&nbsp;<a href="https://aidenlab.org/assembly/">Assembly Tools</a>.&nbsp;<a href="https://github.com/theaidenlab/juicebox/wiki/Download">Download Juicebox here</a>, or use&nbsp;<a href="https://aidenlab.org/juicebox">Juicebox on the web</a>. Detailed documentation is available&nbsp;<a href="https://github.com/theaidenlab/juicebox/wiki">on the wiki</a>. Instructions below pertain primarily to usage of command line tools and the Juicebox jar files.</p>
<p>Juicebox can now be used to visualize and interactively (re)assemble genomes. Check out the Juicebox Assembly Tools Module website&nbsp;<a href="https://aidenlab.org/assembly">https://aidenlab.org/assembly</a>&nbsp;for more details on how to use Juicebox for assembly.</p>
<p>GUI at&nbsp;<a href="https://aidenlab.org/juicebox/">https://aidenlab.org/juicebox/</a></p><p>Address of the bookmark: <a href="https://github.com/aidenlab/Juicebox" rel="nofollow">https://github.com/aidenlab/Juicebox</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/33942/mulan-multiple-sequence-local-alignment-and-conservation-visualization-tool</guid>
	<pubDate>Thu, 20 Jul 2017 08:02:32 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/33942/mulan-multiple-sequence-local-alignment-and-conservation-visualization-tool</link>
	<title><![CDATA[Mulan: MUltiple sequence Local AligNment and conservation visualization tool]]></title>
	<description><![CDATA[<p><span>Mulan performs multiple (2 or more) sequence alignments with an efficient and rapid "full local" alignment strategy that ensures a recapitulation of evolutionary sequence rearrangements (such as inversions and reshuffling) in any of the species. It combines&nbsp;</span><a href="http://www.bx.psu.edu/miller_lab/" target="_new"><em>refine</em>&nbsp;and&nbsp;<em>tba</em></a><span>&nbsp;tools to align either "draft" or "finished" quality sequences. Mulan provides a dynamic graphical interface to align and visualize conservation profiles for evolutionarily distant and closely related species.</span><br><span></span></p>
<p><span>Input formats, automated data upload from the&nbsp;</span><a href="http://genome.ucsc.edu/" target="_new">UCSC Genome Browser</a><span>, gene annotation, annotation of repetitive elements, and progress report were previously described in the&nbsp;</span><a href="https://zpicture.dcode.org/zpInstructions.html" target="_zp">zPicture instructions</a><span>&nbsp;and we refer the users to these materials for more details. This introduction is mainly focused on some novel features unique to the Mulan.</span><span><br></span></p><p>Address of the bookmark: <a href="https://mulan.dcode.org/mulanInstructions.php" rel="nofollow">https://mulan.dcode.org/mulanInstructions.php</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/26380/hicdat</guid>
	<pubDate>Fri, 12 Feb 2016 05:23:44 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/26380/hicdat</link>
	<title><![CDATA[HiCdat]]></title>
	<description><![CDATA[<p>HiCdat: a fast and easy-to-use Hi-C data analysis tool</p>
<p>HiCdat is easy-to-use and provides solutions starting from aligned reads up to in-depth analyses. Importantly, HiCdat is focussed on the analysis of larger structural features of chromosomes, their correlation to genomic and epigenomic features, and on comparative studies. It uses simple input and output formats and can therefore easily be integrated into existing workflows or combined with alternative tools.</p>
<p>More at http://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-015-0678-x</p><p>Address of the bookmark: <a href="https://github.com/MWSchmid/HiCdat" rel="nofollow">https://github.com/MWSchmid/HiCdat</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34920/xmatchview-smith-waterman-alignment-visualization</guid>
	<pubDate>Thu, 28 Dec 2017 09:00:58 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34920/xmatchview-smith-waterman-alignment-visualization</link>
	<title><![CDATA[xmatchview: smith-waterman alignment visualization]]></title>
	<description><![CDATA[<p><span>xmatchview and xmatchview-conifer are imaging tools for comparing the synteny between DNA sequences. It allows users to align 2 DNA sequences in fasta format using cross_match and displays the alignment in a variety of image formats. xmatchview and xmatchview-conifer are written in python and run on linux and windows. They serve as visual tools for analyzing cross_match alignments. Cross_match (Green, P. (1994)&nbsp;</span><a href="http://www.phrap.org/">http://www.phrap.org</a><span>) uses an implementation of the Smith-Waterman algorithm for comparing DNA sequences that is sensitive.</span></p>
<p><span>http://www.bcgsc.ca/platform/bioinfo/software/xmatchview</span></p><p>Address of the bookmark: <a href="https://github.com/warrenlr/xmatchview" rel="nofollow">https://github.com/warrenlr/xmatchview</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37529/bokeh-an-interactive-visualization-library-that-targets-modern-web-browsers-for-presentation</guid>
	<pubDate>Fri, 10 Aug 2018 18:43:08 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37529/bokeh-an-interactive-visualization-library-that-targets-modern-web-browsers-for-presentation</link>
	<title><![CDATA[Bokeh: An interactive visualization library that targets modern web browsers for presentation]]></title>
	<description><![CDATA[<p id="about">Bokeh is an interactive visualization library that targets modern web browsers for presentation. Its goal is to provide elegant, concise construction of versatile graphics, and to extend this capability with high-performance interactivity over very large or streaming datasets. Bokeh can help anyone who would like to quickly and easily create interactive plots, dashboards, and data applications.</p>
<p>To get started using Bokeh to make your visualizations, see the&nbsp;<a href="https://bokeh.pydata.org/en/latest/docs/user_guide.html#userguide">User Guide</a>.</p>
<p>To see examples of how you might use Bokeh with your own data, check out the&nbsp;<a href="https://bokeh.pydata.org/en/latest/docs/gallery.html#gallery">Gallery</a>.</p>
<p>A complete API reference of Bokeh is at&nbsp;<a href="https://bokeh.pydata.org/en/latest/docs/reference.html#refguide">Reference Guide</a>.</p>
<p>If you are interested in contributing to Bokeh, or extending the library, see the&nbsp;<a href="https://bokeh.pydata.org/en/latest/docs/dev_guide.html#devguide">Developer Guide</a>.</p><p>Address of the bookmark: <a href="https://bokeh.pydata.org/en/latest/" rel="nofollow">https://bokeh.pydata.org/en/latest/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40298/environment-for-tree-exploration-ete-is-a-python-programming-toolkit-that-assists-in-the-recontruction-manipulation-analysis-and-visualization-of-phylogenetic-trees</guid>
	<pubDate>Wed, 27 Nov 2019 05:32:33 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40298/environment-for-tree-exploration-ete-is-a-python-programming-toolkit-that-assists-in-the-recontruction-manipulation-analysis-and-visualization-of-phylogenetic-trees</link>
	<title><![CDATA[Environment for Tree Exploration (ETE) is a Python programming toolkit that assists in the recontruction, manipulation, analysis and visualization of phylogenetic trees]]></title>
	<description><![CDATA[<p><span>The Environment for Tree Exploration (ETE) is a Python programming toolkit that assists in the recontruction, manipulation, analysis and visualization of phylogenetic trees (although clustering trees or any other tree-like data structure are also supported).</span></p>
<p><span>Other tools</span></p>
<p><span><a href="https://github.com/shenwei356/taxonkit">https://github.com/shenwei356/taxonkit</a></span></p>
<p>&nbsp;</p>
<ul>
<li>ETE, version:&nbsp;<a href="https://pypi.org/project/ete3/3.1.1/">3.1.1</a></li>
<li>BioPython, version:&nbsp;<a href="https://pypi.org/project/biopython/1.73/">1.73</a></li>
<li>taxadb, version:&nbsp;<a href="https://pypi.org/project/taxadb/0.9.0">0.10.1</a></li>
<li>TaxonKit, version:&nbsp;<a href="https://github.com/shenwei356/taxonkit/releases/tag/0.10.1">0.5.0</a></li>
</ul><p>Address of the bookmark: <a href="https://pypi.org/project/ete3/3.1.1/" rel="nofollow">https://pypi.org/project/ete3/3.1.1/</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/26456/the-mills-lab</guid>
  <pubDate>Wed, 24 Feb 2016 16:18:38 -0600</pubDate>
  <link></link>
  <title><![CDATA[The Mills lab]]></title>
  <description><![CDATA[
<p>The laboratory is focused on the discovery and analysis of structural variation (SVs) from genomic sequence data. As part of the 1000 Genomes Project and other endeavors, we have helped produce initial fine-scale maps using a variety of SV discovery approaches including: (i) paired-end mapping (or read pair analysis) based on abnormally mapped pairs of clone ends; (ii) read-depth analysis, which detects deletions and duplications through analysis of the read depth-of-coverage; (iii) split read analysis, which detects SVs by evaluating gapped sequence alignments; and (iv) sequence assembly, which enables the discovery of novel (non-reference) sequence insertions.</p>

<p>http://millslab.org/research.html</p>
]]></description>
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