<?xml version='1.0'?><rss version="2.0" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:georss="http://www.georss.org/georss" xmlns:atom="http://www.w3.org/2005/Atom" >
<channel>
	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/42198?offset=10</link>
	<atom:link href="https://bioinformaticsonline.com/related/42198?offset=10" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/45240/pg2-making-pangenome-graphs-easier-to-understand</guid>
	<pubDate>Tue, 18 Aug 2026 04:38:23 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/45240/pg2-making-pangenome-graphs-easier-to-understand</link>
	<title><![CDATA[PG2: Making Pangenome Graphs Easier to Understand]]></title>
	<description><![CDATA[<p>Genomics is moving beyond the traditional approach of studying DNA using a single reference genome. Today, researchers are increasingly using pangenomes, which represent genetic information from multiple genomes and capture a much broader range of genetic diversity.</p><p>However, pangenome graphs can be highly complex, making them difficult to visualize and interpret. A recent study published in BMC Bioinformatics introduces PG2 (PanGenoGrapher), an open-source, web-based tool designed to address this challenge.&nbsp;The source code and user guide are openly available on GitHub at https://github.com/iVis-at-Bilkent/pangenographer. A publicly accessible sample deployment is hosted at http://pg2.cs.bilkent.edu.tr. In addition, a demonstration video illustrating the primary use cases of PG2 is available at https://www.youtube.com/watch?v=yCd7-aGY6CQ.</p><p>PG2 combines advanced graph-layout algorithms with an interactive visualization platform. It allows researchers to explore genomic paths, identify variations, and examine relationships between different parts of a pangenome graph more easily.</p><p>This is important because visualization can play a major role in bioinformatics. When complex genomic information is presented clearly, researchers can more easily identify patterns, understand genetic variation, and generate new biological insights.</p><p>The development of PG2 represents a step toward making pangenome analysis more accessible and intuitive. As genomic datasets continue to grow and graph-based representations become more common, tools like PG2 can help researchers navigate this increasing complexity.</p><p>Ultimately, PG2 demonstrates how combining genomics, graph algorithms, and interactive visualization can make sophisticated biological data easier to understand and analyze.</p><p>Reference: Solun, G. K., Dogrusoz, U., Bing&ouml;l, Z., &amp; Alkan, C. (2026). PG2: algorithms and a web-based tool for effective layout and visual analysis of pangenome graphs. BMC Bioinformatics. DOI: 10.1186/s12859-026-06555-4.</p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/29635/r-graphs</guid>
	<pubDate>Fri, 04 Nov 2016 10:48:00 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/29635/r-graphs</link>
	<title><![CDATA[R Graphs !!]]></title>
	<description><![CDATA[<p><span>The blog is a collection of script examples with example data and output plots. R produce excellent quality graphs for data analysis, science and business presentation, publications and other purposes. Self-help codes and examples are provided. Enjoy nice graphs !!</span></p><p>Address of the bookmark: <a href="http://rgraphgallery.blogspot.be/" rel="nofollow">http://rgraphgallery.blogspot.be/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/35896/phylographer-graph-visualization-tool</guid>
	<pubDate>Wed, 07 Mar 2018 18:11:25 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/35896/phylographer-graph-visualization-tool</link>
	<title><![CDATA[PhyloGrapher - Graph Visualization Tool]]></title>
	<description><![CDATA[<p><strong>PhyloGrapher</strong><span>&nbsp;is a program designed to visualize and study evolutionary relationships within families of homologous genes or proteins (elements).&nbsp;</span><strong>PhyloGrapher</strong><span>&nbsp;is a drawing tool that generates custom graphs for a given set of elements. In general, it is possible to use&nbsp;</span><strong>PhyloGrapher</strong><span>&nbsp;to visualize any type of relations between elements.&nbsp;</span></p>
<p><span>https://www.youtube.com/watch?v=WgufqYMHCvM</span></p><p>Address of the bookmark: <a href="http://www.atgc.org/PhyloGrapher/PhyloGrapher_Welcome.html" rel="nofollow">http://www.atgc.org/PhyloGrapher/PhyloGrapher_Welcome.html</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38212/megahit-an-ultra-fast-single-node-solution-for-large-and-complex-metagenomics-assembly-via-succinct-de-bruijn-graph</guid>
	<pubDate>Wed, 14 Nov 2018 04:50:27 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38212/megahit-an-ultra-fast-single-node-solution-for-large-and-complex-metagenomics-assembly-via-succinct-de-bruijn-graph</link>
	<title><![CDATA[MEGAHIT: an ultra-fast single-node solution for large and complex metagenomics assembly via succinct de Bruijn graph]]></title>
	<description><![CDATA[<p><span>MEGAHIT is a single node assembler for large and complex metagenomics NGS reads, such as soil. It makes use of succinct&nbsp;</span><em>de Bruijn</em><span>&nbsp;graph (SdBG) to achieve low memory assembly. MEGAHIT can&nbsp;</span><span>optionally</span><span>&nbsp;utilize a CUDA-enabled GPU to accelerate its SdBG contstruction. The GPU-accelerated version of MEGAHIT has been tested on NVIDIA GTX680 (4G memory) and Tesla K40c (12G memory) with CUDA 5.5, 6.0 and 6.5. MEGAHIT v1.0 or greater also supports IBM Power PC and has been tested on IBM POWER8.</span></p>
<p><span>https://academic.oup.com/bioinformatics/article/31/10/1674/177884</span></p><p>Address of the bookmark: <a href="https://github.com/voutcn/megahit" rel="nofollow">https://github.com/voutcn/megahit</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43263/jumbodb-tool-for-de-bruijn-graph-construction</guid>
	<pubDate>Tue, 17 Aug 2021 13:33:46 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43263/jumbodb-tool-for-de-bruijn-graph-construction</link>
	<title><![CDATA[JumboDB: tool for de Bruijn graph construction]]></title>
	<description><![CDATA[<p><span>jumboDB tool for fast de Bruijn graph construction from long sequences (reads or genomes) with very low error rate. JumboDB is not a genome assembler by itself but rather a subroutine that translates a set of reads into compressed de Bruijn graph.</span></p>
<p><span>More at&nbsp;https://github.com/AntonBankevich/jumboDB</span></p><p>Address of the bookmark: <a href="https://github.com/AntonBankevich/jumboDB" rel="nofollow">https://github.com/AntonBankevich/jumboDB</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/45273/a-subway-map-for-the-genome</guid>
	<pubDate>Fri, 04 Sep 2026 04:14:14 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/45273/a-subway-map-for-the-genome</link>
	<title><![CDATA[A Subway Map for the Genome]]></title>
	<description><![CDATA[<p>Maya was looking at a genome graph on her computer. There were nodes, branches, and paths going in every direction.</p><p>&ldquo;It&rsquo;s like a subway map,&rdquo; she said, &ldquo;but for DNA.&rdquo;</p><p>That idea is exactly what Sequence Tube Map brings to life.</p><p>Instead of showing a genome as one long, confusing sequence, it displays different genomic paths like routes on a metro map. Where sequences are shared, the paths travel together. Where genetic variation occurs, they branch into different routes and may join again later.</p><p>This makes complex genome graphs much easier to explore.</p><p>Maya could now see how different haplotypes moved through the same genomic region and where they took different paths. She could even view sequencing reads mapped onto the graph, helping her understand what was happening in regions with genetic variation.</p><p>What once looked like a tangled network now looked like a journey.</p><p>Sequence Tube Map turns the complexity of graph genomes into a visual story&mdash;making it easier for scientists to see how DNA can take different routes.</p><p>Read more at&nbsp; https://github.com/vgteam/sequencetubemap&nbsp;</p><p>and</p><p>https://academic.oup.com/bioinformatics/article/35/24/5318/5542397</p><p>Demo at&nbsp;https://vgteam.github.io/sequenceTubeMap/</p>]]></description>
	<dc:creator>LEGE</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/29917/gojs</guid>
	<pubDate>Tue, 22 Nov 2016 08:25:37 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/29917/gojs</link>
	<title><![CDATA[GoJS]]></title>
	<description><![CDATA[<p><strong>GoJS</strong> is a feature-rich JavaScript library for implementing custom interactive diagrams and complex visualizations across modern web browsers and platforms. <strong>GoJS</strong> makes constructing JavaScript diagrams of complex nodes, links, and groups easy with customizable templates and layouts.</p>
<p><strong>GoJS</strong> offers many advanced features for user interactivity such as drag-and-drop, copy-and-paste, in-place text editing, tooltips, context menus, automatic layouts, templates, data binding and models, transactional state and undo management, palettes, overviews, event handlers, commands, and an extensible tool system for custom operations.</p>
<p><strong>GoJS</strong> is pure JavaScript, so users get interactivity without requiring round-trips to servers and without plugins. <strong>GoJS</strong> normally runs completely in the browser, rendering to an HTML5 Canvas element or SVG without any server-side requirements. <strong>GoJS</strong> does not depend on any JavaScript libraries or frameworks, so it should work with any HTML or JavaScript framework or with no framework at all. &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;</p>
<p>More at&nbsp;http://gojs.net/latest/index.html</p><p>Address of the bookmark: <a href="http://gojs.net/latest/index.html" rel="nofollow">http://gojs.net/latest/index.html</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38039/vgsc-a-web-based-vector-graph-toolkit-of-genome-synteny-and-collinearity</guid>
	<pubDate>Tue, 30 Oct 2018 10:46:28 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38039/vgsc-a-web-based-vector-graph-toolkit-of-genome-synteny-and-collinearity</link>
	<title><![CDATA[VGSC: A Web-Based Vector Graph Toolkit of Genome Synteny and Collinearity]]></title>
	<description><![CDATA[<p><span>VGSC, the Vector Graph toolkit of genome Synteny and Collinearity, and its online service, to visualize the synteny and collinearity in the common graphical format, including both raster (JPEG, Bitmap, and PNG) and vector graphic (SVG, EPS, and PDF).</span><em>&nbsp;</em></p><p>Address of the bookmark: <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4783527/" rel="nofollow">https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4783527/</a></p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38892/wtdbg2-a-fuzzy-bruijn-graph-approach-to-long-noisy-reads-assembly</guid>
	<pubDate>Mon, 04 Feb 2019 04:53:47 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38892/wtdbg2-a-fuzzy-bruijn-graph-approach-to-long-noisy-reads-assembly</link>
	<title><![CDATA[wtdbg2: A fuzzy Bruijn graph approach to long noisy reads assembly]]></title>
	<description><![CDATA[<p><span>Wtdbg2 is a&nbsp;</span><em>de novo</em><span>&nbsp;sequence assembler for long noisy reads produced by PacBio or Oxford Nanopore Technologies (ONT). It assembles raw reads without error correction and then builds the consensus from intermediate assembly output.&nbsp;</span></p>
<pre>./wtdbg2 -x rs -g 4.6m -t 16 -i reads.fa.gz -fo prefix
./wtpoa-cns -t 16 -i prefix.ctg.lay.gz -fo prefix.ctg.fa</pre><p>Address of the bookmark: <a href="https://github.com/ruanjue/wtdbg2" rel="nofollow">https://github.com/ruanjue/wtdbg2</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44889/gfaffix-identifies-walk-preserving-shared-affixes-in-variation-graphs-and-collapses-them-into-a-non-redundant-graph-structure</guid>
	<pubDate>Thu, 28 Aug 2025 03:11:25 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44889/gfaffix-identifies-walk-preserving-shared-affixes-in-variation-graphs-and-collapses-them-into-a-non-redundant-graph-structure</link>
	<title><![CDATA[GFAffix : Identifies walk-preserving shared affixes in variation graphs and collapses them into a non-redundant graph structure.]]></title>
	<description><![CDATA[<p><span>GFAffix identifies walk-preserving shared affixes in variation graphs and collapses them into a non-redundant graph structure.</span></p>
<p>&nbsp;</p>
<p><span><img src="https://github.com/codialab/GFAffix/raw/main/doc/gfaffix-illustration.png?raw=true" alt="image" style="border: 0px; border: 0px;"></span></p><p>Address of the bookmark: <a href="https://github.com/codialab/GFAffix" rel="nofollow">https://github.com/codialab/GFAffix</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>

</channel>
</rss>