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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/36837?offset=230</link>
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	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43652/peregrine-shimmer-genome-assembly-toolkit</guid>
	<pubDate>Thu, 16 Dec 2021 02:50:19 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43652/peregrine-shimmer-genome-assembly-toolkit</link>
	<title><![CDATA[Peregrine &amp; SHIMMER Genome Assembly Toolkit]]></title>
	<description><![CDATA[<p><span>Peregrine is a fast genome assembler for accurate long reads (length &gt; 10kb, accuracy &gt; 99%). It can assemble a human genome from 30x reads within 20 cpu hours from reads to polished consensus. It uses Sparse HIereachical MimiMizER (SHIMMER) for fast read-to-read overlaping without quadratic comparisions used in other OLC assemblers.</span></p><p>Address of the bookmark: <a href="https://github.com/cschin/Peregrine" rel="nofollow">https://github.com/cschin/Peregrine</a></p>]]></description>
	<dc:creator>Abhi</dc:creator>
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<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44474/claw-chloroplast-long-read-assembly-workflow</guid>
	<pubDate>Wed, 21 Feb 2024 12:37:46 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44474/claw-chloroplast-long-read-assembly-workflow</link>
	<title><![CDATA[CLAW: Chloroplast Long-read Assembly Workflow]]></title>
	<description><![CDATA[<p dir="auto">CLAW (Chloroplast Long-read Assembly Workflow) is an mostly-automated Snakemake-based workflow for the assembly of chloroplast genomes. CLAW uses chloroplast long-reads, which are baited out of larger read libraries (e.g., an Oxford Nanopore Technologies MinION read library derived from photosynthetic tissue), for assembly with Flye and/or Unicycler. CLAW was designed with the novice bioinformatician in mind - it is easy to install and easy to use, requiring only minimal user input.</p><p>Address of the bookmark: <a href="https://github.com/aaronphillips7493/CLAW" rel="nofollow">https://github.com/aaronphillips7493/CLAW</a></p>]]></description>
	<dc:creator>LEGE</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/videolist/watch/2699/translational-bioinformatics-transforming-300-billion-points-of-data</guid>
	<pubDate>Tue, 20 Aug 2013 19:03:47 -0500</pubDate>
	<link>https://bioinformaticsonline.com/videolist/watch/2699/translational-bioinformatics-transforming-300-billion-points-of-data</link>
	<title><![CDATA[Translational Bioinformatics: Transforming 300 Billion Points of Data]]></title>
	<description><![CDATA[<iframe width="" height="" src="https://www.youtube-nocookie.com/embed/o4KNG7nd938" frameborder="0" allowfullscreen></iframe>Translational Bioinformatics: Transforming 300 Billion Points of Data into Diagnostics, Therapeutics, and New Insights into Disease      
      
Air date:  Wednesday, June 20, 2012, 3:00:00 PM
Time displayed is Eastern Time, Washington DC Local  
 
Description:  There is an urgent need to translate genome-era discoveries into clinical utility, but the difficulties in making bench-to-bedside translations haven't been well described. The nascent field of translational bioinformatics may help. Dr. Butte's lab at Stanford University builds and applies tools that convert more than 300 billion points of molecular, clinical, and epidemiological data (measured by researchers and clinicians over the past decade) into diagnostics, therapeutics, and new insights into disease. Dr. Butte, a bioinformatician and pediatric endocrinologist, will highlight his lab's work on using publicly available molecular measurements to find new uses for drugs, discovering new treatable mechanisms of disease in type 2 diabetes, and evaluating patients presenting with whole genomes sequenced. 

The NIH Wednesday Afternoon Lecture Series includes weekly scientific talks by some of the top researchers in the biomedical sciences worldwide. 

For more information, visit: 
The NIH Director's Wednesday Afternoon Lecture Series  
Author:  Atul Butte, M.D., Ph.D., Stanford University  
Runtime:  01:07:42  
Permanent link:  http://videocast.nih.gov/launch.asp?17321]]></description>
	
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/32851/anges-reconstructing-ancestral-genomes-maps</guid>
	<pubDate>Thu, 18 May 2017 05:27:08 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/32851/anges-reconstructing-ancestral-genomes-maps</link>
	<title><![CDATA[ANGES: reconstructing ANcestral GEnomeS maps]]></title>
	<description><![CDATA[<p>This page contains the software ANGES 1.01, that aims at reconstucting ancestral genome maps from homologous markers in extant related genomes.</p>
<h3>Download</h3>
<ul>
<li><a href="http://paleogenomics.irmacs.sfu.ca/ANGES/anges_1.01.tar.gz">Program, version 1.01</a>&nbsp;(July 10, 2012, documentation updated in August 2014)</li>
<li><a href="http://paleogenomics.irmacs.sfu.ca/ANGES/anges_1.01_examples_with_results.tar.gz">Examples with results (featured ancestors: boreoeutherian, amniote, yeasts, Burkholderia, monocots)</a>; please refer to the documentation of the distribution above.</li>
</ul><p>Address of the bookmark: <a href="http://paleogenomics.irmacs.sfu.ca/ANGES/" rel="nofollow">http://paleogenomics.irmacs.sfu.ca/ANGES/</a></p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36905/d-genies-a-tool-for-dotplot-large-genomes-in-an-interactive-efficient-and-simple-way</guid>
	<pubDate>Mon, 11 Jun 2018 09:41:22 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36905/d-genies-a-tool-for-dotplot-large-genomes-in-an-interactive-efficient-and-simple-way</link>
	<title><![CDATA[D-GENIES: A tool for Dotplot large Genomes in an Interactive, Efficient and Simple way]]></title>
	<description><![CDATA[D-GENIES – for Dotplot large Genomes in an Interactive, Efficient and Simple way – is an online tool designed to compare two genomes. It supports large genome and you can interact with the dot plot to improve the visualisation.

We use minimap version 2 to align the two genomes. Then, the PAF file is parsed and plotted into an interactive plot written with d3.js library.

D-Genies also allows to display dot plots from other aligners by uploading their PAF or MAF alignment file.

http://dgenies.toulouse.inra.fr/<p>Address of the bookmark: <a href="http://dgenies.toulouse.inra.fr/" rel="nofollow">http://dgenies.toulouse.inra.fr/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44539/bactopia-a-flexible-pipeline-for-complete-analysis-of-bacterial-genomes</guid>
	<pubDate>Wed, 15 May 2024 14:36:12 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44539/bactopia-a-flexible-pipeline-for-complete-analysis-of-bacterial-genomes</link>
	<title><![CDATA[Bactopia: a Flexible Pipeline for Complete Analysis of Bacterial Genomes]]></title>
	<description><![CDATA[<p dir="auto">Bactopia is a flexible pipeline for complete analysis of bacterial genomes. The goal of Bactopia is to process your data with a broad set of tools, so that you can get to the fun part of analyses quicker!</p>
<p dir="auto">Bactopia can be split into two main parts:&nbsp;<a href="https://bactopia.github.io/latest/beginners-guide/">Bactopia Analysis Pipeline</a>, and&nbsp;<a href="https://bactopia.github.io/latest/bactopia-tools/">Bactopia Tools</a>.</p>
<p dir="auto">Bactopia Analysis Pipeline is the main&nbsp;<em>per-isolate</em>&nbsp;workflow in Bactopia. Built with&nbsp;<a href="https://www.nextflow.io/">Nextflow</a>, input FASTQs (local or available from SRA/ENA) are put through numerous analyses including: quality control, assembly, annotation, minmer sketch queries, sequence typing, and more.</p>
<p dir="auto"><a href="https://github.com/bactopia/bactopia/blob/master/data/bactopia-workflow.png" target="_blank"><img src="https://github.com/bactopia/bactopia/raw/master/data/bactopia-workflow.png" alt="Bactopia Overview" style="border: 0px;"></a></p>
<p dir="auto">Bactopia Tools are a set a independent workflows fo</p><p>Address of the bookmark: <a href="https://github.com/bactopia/bactopia" rel="nofollow">https://github.com/bactopia/bactopia</a></p>]]></description>
	<dc:creator>Abhi</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34569/ksnp30-snp-detection-and-phylogenetic-analysis-of-genomes-without-genome-alignment-or-reference-genome</guid>
	<pubDate>Fri, 08 Dec 2017 16:48:40 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34569/ksnp30-snp-detection-and-phylogenetic-analysis-of-genomes-without-genome-alignment-or-reference-genome</link>
	<title><![CDATA[kSNP3.0: SNP detection and phylogenetic analysis of genomes without genome alignment or reference genome]]></title>
	<description><![CDATA[<p><span>Sept. 20, 2017 Version 3.1 released. Major upgrade. Version 3.1 fixes the problems with SNP annotation that arose when NCBI discontinued use of GI numbers. Please read carefully the Preface (page 3) and the File of annotated genomes section (pages 9-10) in the version 3.1 User Guide. Thanks to Tom Slezak for revsing the get_genbank_file3 script and to Tod Stuber (USDA) for testing version 3.1 even though he doesn't need the annotation feature. All users are encouraged to upgrade to version 3.1.&nbsp;<br></span></p><p>Address of the bookmark: <a href="https://sourceforge.net/projects/ksnp/files/" rel="nofollow">https://sourceforge.net/projects/ksnp/files/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/35802/bioinformatics-tools-to-detect-horizontal-gene-transfer-hgt-in-genomes</guid>
	<pubDate>Fri, 02 Mar 2018 04:56:23 -0600</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/35802/bioinformatics-tools-to-detect-horizontal-gene-transfer-hgt-in-genomes</link>
	<title><![CDATA[Bioinformatics tools to detect horizontal gene transfer (HGT) in genomes]]></title>
	<description><![CDATA[<p>Horizontal gene transfer (HGT), the &ldquo;non-sexual movement of genetic material between two organisms&rdquo; , is relatively common in prokaryotes&nbsp;and single-celled eukaryotes, but a number of factors combine to make it far rarer in multicellular eukaryotes. In order for a eukaryotic species to gain a gene by HGT, foreign DNA must enter the host nucleus, integrate into the genome, and in more complex organisms it must enter the sequestered germline in order to be transmitted to offspring. Once there, it must not experience strong negative selection, despite potential for genetic incompatibility with the host genome and mismatch between the niche of the donor and the host. Over the longer term, foreign DNA may become &ldquo;domesticated&rdquo; in the recipient genome and provide novel function.</p><p>Following are the popular tool to detect HGT in genomes:</p><p><a href="http://www.trex.uqam.ca/index.php?action=hgt&amp;project=trex">T-REX</a>&nbsp;/&nbsp;<a href="http://www.trex.uqam.ca/download/hgt-detection_3.22.zip">3.22</a></p><p>HGT detection /&nbsp;download &amp; compile</p><p><a href="https://www.ncbi.nlm.nih.gov/pubmed/20525630">20525630</a></p><p>&nbsp;</p><p><a href="http://compbio.engr.uconn.edu/software/RANGER-DTL/">RANGER-DTL</a>&nbsp;/&nbsp;<a href="http://compbio.engr.uconn.edu/software/RANGER-DTL/Linux.zip">2.0</a></p><p>HGT detection /&nbsp;download binary</p><p><a href="https://www.ncbi.nlm.nih.gov/pubmed/22689773">22689773</a></p><p>&nbsp;</p><p><a href="https://bioinfocs.rice.edu/phylonet">PhyloNet</a>&nbsp;/&nbsp;<a href="https://bioinfocs.rice.edu/sites/g/files/bxs266/f/kcfinder/files/PhyloNet_3.6.1.jar">3.6.1</a></p><p>HGT detection /&nbsp;download binary</p><p><a href="https://www.ncbi.nlm.nih.gov/pubmed/18662388">18662388</a></p><p>&nbsp;</p><p><a href="https://www.cs.hmc.edu/~hadas/jane/index.html">Jane</a>&nbsp;/&nbsp;<a href="https://www.cs.hmc.edu/~hadas/jane/form.html">4.01</a></p><p>HGT detection /&nbsp;download binary (!license!)</p><p><a href="https://www.ncbi.nlm.nih.gov/pubmed/20181081">20181081</a></p><p>&nbsp;</p><p><a href="http://www.tree-puzzle.de/">TREE-PUZZLE</a>&nbsp;/&nbsp;<a href="http://www.tree-puzzle.de/tree-puzzle-5.3.rc16-linux.tar.gz">5.3.rc16</a></p><p>HGT detection /&nbsp;download &amp; compile</p><p><a href="https://www.ncbi.nlm.nih.gov/pubmed/11934758">11934758</a></p><p>&nbsp;</p><p><a href="http://www.sigmath.es.osaka-u.ac.jp/shimo-lab/prog/consel/">CONSEL</a>&nbsp;/&nbsp;<a href="http://www.sigmath.es.osaka-u.ac.jp/shimo-lab/prog/consel/pub/cnsls020.tgz">0.20</a></p><p>HGT detection /&nbsp;download</p><p><a href="https://www.ncbi.nlm.nih.gov/pubmed/11751242">11751242</a></p><p>&nbsp;</p><p><a href="http://darkhorse.ucsd.edu/">DarkHorse</a>&nbsp;/&nbsp;<a href="http://darkhorse.ucsd.edu/DarkHorse-1.5_rev170.tar.gz">1.5 rev170</a></p><p>HGT detection /&nbsp;download &amp; install</p><p><a href="https://www.ncbi.nlm.nih.gov/pubmed/17274820">17274820</a></p><p>&nbsp;</p><p><a href="https://github.com/DittmarLab/HGTector">HGTector</a>&nbsp;/&nbsp;<a href="https://github.com/DittmarLab/HGTector/archive/wgshgt.zip">0.2.1</a></p><p>HGT detection /&nbsp;git clone</p><p><a href="https://www.ncbi.nlm.nih.gov/pubmed/25159222">25159222</a></p><p>&nbsp;</p><p><a href="http://www5.esu.edu/cpsc/bioinfo/software/EGID/">EGID</a>&nbsp;/&nbsp;<a href="http://www5.esu.edu/cpsc/bioinfo/software/EGID/EGID_1.0.tar.gz">1.0</a></p><p>HGT detection /&nbsp;download</p><p><a href="https://www.ncbi.nlm.nih.gov/pubmed/22355228">22355228</a></p><p>&nbsp;</p><p><a href="http://exon.gatech.edu/GeneMark/">GeneMarkS</a>&nbsp;/&nbsp;<a href="http://exon.gatech.edu/GeneMark/license_download.cgi">4.30</a></p><p>HGT detection / download binary (!license!)</p><p><a href="https://www.ncbi.nlm.nih.gov/pubmed/9461475">9461475</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37520/mmgenome-tools-for-extracting-individual-genomes-from-metagneomes</guid>
	<pubDate>Thu, 09 Aug 2018 17:41:17 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37520/mmgenome-tools-for-extracting-individual-genomes-from-metagneomes</link>
	<title><![CDATA[mmgenome: Tools for extracting individual genomes from metagneomes]]></title>
	<description><![CDATA[<p>The mmgenome toolbox enables reproducible extraction of individual genomes from metagenomes. It builds on the&nbsp;<a href="http://madsalbertsen.github.io/multi-metagenome/">multi-metagenome</a>&nbsp;concept, but wraps most of the process of extracting genomes in simple R functions. Thereby making the whole process of binning easy and at the same time reproducible through the Rmarkdown format.</p>
<p>The mmgenome R package also facilitates effortless integration with additional data sources and hence should not be seen as "yet another binning method", but rather a package to integrate different binning strategies.</p>
<p>All functions in the mmgenome R package has associated documentation, check it out in R by e.g.&nbsp;<code>?mmplot</code>.</p><p>Address of the bookmark: <a href="https://github.com/MadsAlbertsen/mmgenome" rel="nofollow">https://github.com/MadsAlbertsen/mmgenome</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/39869/mfannot-a-program-for-the-annotation-of-mitochondrial-and-plastid-genomes</guid>
	<pubDate>Mon, 26 Aug 2019 11:47:56 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/39869/mfannot-a-program-for-the-annotation-of-mitochondrial-and-plastid-genomes</link>
	<title><![CDATA[MFannot : a program for the annotation of mitochondrial and plastid genomes]]></title>
	<description><![CDATA[<p><span>MFannot is a program for the annotation of mitochondrial and plastid genomes</span></p>
<p>MFannot is a program for the annotation of mitochondrial and plastid genomes. It is a PERL wrapper around a set of diverse, external independent tools.</p>
<p>It makes intense use of RNA/intron detection tools including&nbsp;<a href="http://hmmer.org/">HMMER</a>,&nbsp;<a href="https://github.com/nathanweeks/exonerate">Exonerate</a>,&nbsp;<a href="https://bioinformatics.ca/links_directory/tool/9822/erpin">Erpin</a>&nbsp;and others.</p>
<p><a href="http://megasun.bch.umontreal.ca/cgi-bin/mfannot/mfannotInterface.pl">http://megasun.bch.umontreal.ca/cgi-bin/mfannot/mfannotInterface.pl</a></p><p>Address of the bookmark: <a href="https://github.com/BFL-lab/Mfannot" rel="nofollow">https://github.com/BFL-lab/Mfannot</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

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