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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/38212?offset=200</link>
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	<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/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/42198/pggb-the-pangenome-graph-builder</guid>
	<pubDate>Sun, 13 Sep 2020 20:54:20 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42198/pggb-the-pangenome-graph-builder</link>
	<title><![CDATA[pggb: the pangenome graph builder]]></title>
	<description><![CDATA[<p><span>This pangenome graph construction pipeline renders a collection of sequences into a pangenome graph (in the variation graph model). Its goal is to build a graph that is locally directed and acyclic while preserving large-scale variation. Maintaining local linearity is important for the interpretation, visualization, and reuse of pangenome variation graphs.</span></p>
<p><img src="https://raw.githubusercontent.com/pangenome/pggb/master/data/images/DRB1-3123.fa.gz.pggb-s3000-p70-n10-a70-K11-k8-w10000-j5000-W0-e100.smooth.og.viz.png" alt="image" style="border: 0px;"></p><p>Address of the bookmark: <a href="https://github.com/pangenome/pggb" rel="nofollow">https://github.com/pangenome/pggb</a></p>]]></description>
	<dc:creator>biogeek</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44887/alfapang-alignment-free-algorithm-for-pangenome-graph-construction</guid>
	<pubDate>Thu, 28 Aug 2025 02:56:35 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44887/alfapang-alignment-free-algorithm-for-pangenome-graph-construction</link>
	<title><![CDATA[AlfaPang: alignment free algorithm for pangenome graph construction]]></title>
	<description><![CDATA[<p><span>AlfaPang constructs variation graphs, leveraging its alignment-free and reference-free approach, based solely on intrinsic sequence properties. This design allows AlfaPang's runtime and memory usage to scale linearly with the size of input sequences, enabling it to handle significantly larger genome sets compared to other methods.</span></p><p>Address of the bookmark: <a href="https://github.com/AdamCicherski/AlfaPang" rel="nofollow">https://github.com/AdamCicherski/AlfaPang</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/35619/tallymer-method-to-compute-k-mer-frequencies-and-its-application-to-annotate-large-repetitive-plant-genomes</guid>
	<pubDate>Thu, 15 Feb 2018 10:21:02 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/35619/tallymer-method-to-compute-k-mer-frequencies-and-its-application-to-annotate-large-repetitive-plant-genomes</link>
	<title><![CDATA[Tallymer: method to compute K-mer frequencies and its application to annotate large repetitive plant genomes]]></title>
	<description><![CDATA[<p>Tallymer is based on enhanced suffix arrays. This gives a much larger flexibility concerning the choice of the&nbsp;<span>k</span>-mer size. Tallymer can process large data sizes of several billion bases. We used it in a variety of applications to study the genomes of maize and other plant species. In particular, Tallymer was used to index a set whole genome shotgun sequences from maize (B73) (total size 10<sup>9</sup>&nbsp;bp).&nbsp;<br>Tallymer was effective in a variety of applications to aid genome annotation in maize, despite limitations imposed by the relatively low coverage of sequence available.</p>
<p>A manual can be found&nbsp;<a href="https://www.zbh.uni-hamburg.de/fileadmin/gi/tallymer/tallymer.pdf" target="_blank" title="tallymer.pdf (111 KB)">here</a>.</p><p>Address of the bookmark: <a href="https://www.zbh.uni-hamburg.de/forschung/arbeitsgruppe-genominformatik/software/tallymer.html" rel="nofollow">https://www.zbh.uni-hamburg.de/forschung/arbeitsgruppe-genominformatik/software/tallymer.html</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40699/kevler-reference-free-variant-discovery-in-large-eukaryotic-genomes</guid>
	<pubDate>Tue, 28 Jan 2020 03:21:53 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40699/kevler-reference-free-variant-discovery-in-large-eukaryotic-genomes</link>
	<title><![CDATA[Kevler: Reference-free variant discovery in large eukaryotic genomes]]></title>
	<description><![CDATA[<p><span>Welcome to&nbsp;</span><span>kevlar</span><span>, software for predicting&nbsp;</span><em>de novo</em><span>&nbsp;genetic variants without mapping reads to a reference genome! kevlar's&nbsp;</span><em>k</em><span>-mer abundance based method calls single nucleotide variants (SNVs), multinucleotide variants (MNVs), insertion/deletion variants (indels), and structural variants (SVs) simultaneously with a single simple model.&nbsp;</span></p>
<p><span>More at&nbsp;<a href="https://kevlar.readthedocs.io/en/latest/">https://kevlar.readthedocs.io/en/latest/</a></span></p>
<p><span><a href="https://www.cell.com/iscience/pdf/S2589-0042(19)30259-7.pdf">https://www.cell.com/iscience/pdf/S2589-0042(19)30259-7.pdf</a></span></p><p>Address of the bookmark: <a href="https://github.com/kevlar-dev/kevlar" rel="nofollow">https://github.com/kevlar-dev/kevlar</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/4211/socbin-bioinformatics-2014</guid>
  <pubDate>Tue, 03 Sep 2013 18:50:20 -0500</pubDate>
  <link></link>
  <title><![CDATA[SocBiN Bioinformatics 2014]]></title>
  <description><![CDATA[
<p>14th annual conference in Bioinformatics</p>

<p>Date : June 10-13</p>

<p>Organizers: The Society for Bioinformatics in Northern European countries (SocBiN) and the Norwegian Bioinformatics Platform / ELIXIR.NO </p>

<p>Venue: Department of Informatics, University of Oslo, Norway</p>

<p>Topics:<br />Tools and technologies for integrative bioinformatics<br />Metagenomics<br />Comparative genomics and phylogeny<br />Post-ENCODE bioinformatics<br />Gene regulation<br />Cancer genomes<br />Marine genomics</p>
]]></description>
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<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/39674/simka-and-simkamin-are-comparative-metagenomics-method-dedicated-to-ngs-datasets</guid>
	<pubDate>Sat, 06 Jul 2019 13:56:10 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/39674/simka-and-simkamin-are-comparative-metagenomics-method-dedicated-to-ngs-datasets</link>
	<title><![CDATA[Simka and SimkaMin are comparative metagenomics method dedicated to NGS datasets]]></title>
	<description><![CDATA[<p>Simka is a de novo comparative metagenomics tool. Simka represents each dataset as a k-mer spectrum and compute several classical ecological distances between them.</p>
<p>Developper:&nbsp;<a href="http://people.rennes.inria.fr/Gaetan.Benoit/">Ga&euml;tan Benoit</a>, PhD, former member of the&nbsp;<a href="http://team.inria.fr/genscale/">Genscale</a>&nbsp;team at Inria.</p>
<p>Contact: claire dot lemaitre at inria dot fr</p>
<p><span>Simka and SimkaMin are comparative metagenomics method dedicated to NGS datasets.&nbsp;</span><span></span><span><a href="https://gatb.inria.fr/software/simka/">https://gatb.inria.fr/software/simka/</a></span></p><p>Address of the bookmark: <a href="https://github.com/GATB/simka" rel="nofollow">https://github.com/GATB/simka</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43048/coverm-read-coverage-calculator-for-metagenomics</guid>
	<pubDate>Thu, 29 Apr 2021 23:39:14 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43048/coverm-read-coverage-calculator-for-metagenomics</link>
	<title><![CDATA[CoverM: Read coverage calculator for metagenomics]]></title>
	<description><![CDATA[<p>CoverM aims to be a configurable, easy to use and fast DNA read coverage and relative abundance calculator focused on metagenomics applications.</p>
<p>CoverM calculates coverage of genomes/MAGs&nbsp;<code>coverm genome</code>&nbsp;(<a href="https://wwood.github.io/CoverM/coverm-genome.html">help</a>) or individual contigs&nbsp;<code>coverm contig</code>&nbsp;(<a href="https://wwood.github.io/CoverM/coverm-contig.html">help</a>). Calculating coverage by read mapping, its input can either be BAM files sorted by reference, or raw reads and reference genomes in various formats.</p><p>Address of the bookmark: <a href="https://github.com/wwood/CoverM" rel="nofollow">https://github.com/wwood/CoverM</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>

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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/6954/workshop-on-population-and-metagenomics-analysis-nerc</guid>
  <pubDate>Sun, 01 Dec 2013 14:25:45 -0600</pubDate>
  <link></link>
  <title><![CDATA[Workshop on population and metagenomics analysis @ NERC]]></title>
  <description><![CDATA[
<p>Workshop Overview</p>

<p>A ten-day workshop taking place between 25 February - 6 March 2014 providing detailed hands-on training for population and meta-genomics analysis for researchers with little or no background in mathematics or computing.</p>

<p>Venue: Dartington Hall, Totnes, Devon (nearest train station - Totnes)</p>

<p>Times: 25 February - 6th March 2014.</p>

<p>Arrival evening of Tuesday 25 February 2014. Departure morning of 6th March 2014. The course itself will take place 9am-12pm, 2pm-5pm and on some evenings 7pm-10pm everyday 26 February-5th March. Students are expected to attend the entire course.</p>

<p>Contact: research-events@exeter.ac.uk</p>

<p>Registration</p>

<p>The course itself is free of charged and is funded by a Professional Postgraduate Development Award from NERC.</p>

<p>A total of 30 funded places are available which cover the costs of accommodation and food, but not the cost of transportation to/from the venue.</p>

<p>An additional 10 places are available for participants from industry. The cost of accommodation and meals will need to be covered by the participants.</p>

<p>You should register your interest by 31 December 2013. Participants will be informed by 10th January 2014 as to whether they have been selected. Please note that preference will be given to researchers funded by NERC.</p>

<p>More at http://www.eventbrite.co.uk/e/nerc-workshop-on-population-and-metagenomics-analysis-tickets-8628888237</p>
]]></description>
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