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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/41918?offset=30</link>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34720/meraculous-haplotype-sensitive-assembly-of-highly-heterozygous-genomes</guid>
	<pubDate>Wed, 20 Dec 2017 18:59:42 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34720/meraculous-haplotype-sensitive-assembly-of-highly-heterozygous-genomes</link>
	<title><![CDATA[Meraculous: Haplotype-sensitive Assembly of Highly Heterozygous genomes.]]></title>
	<description><![CDATA[<p><span>Meraculous is a whole genome assembler for Next Generation Sequencing data geared for large genomes. It is a hybrid k-mer/read-based assembler that capitalizes on the high accuracy of Illumina sequence by eschewing an explicit error correction step which we argue to be redundant with the assembly process. Meraculous achieves high performance with large datasets by utilizing lightweight data structures and multi-threaded parallelization, allowing to assemble human-sized genomes on commodity clusters in under a day. The process pipeline implements a highly transparent and portable model of job control and monitoring where different assembly stages can be executed and re-executed separately or in unison on a wide variety of architectures.</span></p>
<p><span>https://jgi.doe.gov/data-and-tools/meraculous/</span></p>
<p><span>https://arxiv.org/ftp/arxiv/papers/1703/1703.09852.pdf</span></p><p>Address of the bookmark: <a href="https://sourceforge.net/projects/meraculous20/" rel="nofollow">https://sourceforge.net/projects/meraculous20/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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	<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/36837/ranbow-a-haplotype-assembler-for-polyploid-genomes</guid>
	<pubDate>Fri, 01 Jun 2018 07:21:54 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36837/ranbow-a-haplotype-assembler-for-polyploid-genomes</link>
	<title><![CDATA[Ranbow: a haplotype assembler for polyploid genomes]]></title>
	<description><![CDATA[Ranbow is a haplotype assembler for polyploid genomes. It has been developed for the haplotype assembly of the hexaploid sweet potato genome, which is highly heterozygous. Ranbow can also be applied to other polyploid genomes. After a first phasing, Ranbow utilizes the assembled haplotypes to improve the accuracy of variant calling results and to infer the evolutionary history of the organism´s genome. Ranbow has three main modes of function:

ranbow hap: for haplotyping
ranbow eval: for evaluating of the assemble haplotypes by gold standard (long) reads 
ranbow phylo: for the phylogenetic analysis<p>Address of the bookmark: <a href="https://www.molgen.mpg.de/ranbow" rel="nofollow">https://www.molgen.mpg.de/ranbow</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38505/allhic-phasing-and-scaffolding-polyploid-genomes-based-on-hi-c-data</guid>
	<pubDate>Thu, 20 Dec 2018 12:03:32 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38505/allhic-phasing-and-scaffolding-polyploid-genomes-based-on-hi-c-data</link>
	<title><![CDATA[ALLHiC: Phasing and scaffolding polyploid genomes based on Hi-C data]]></title>
	<description><![CDATA[<p><span>The major problem of scaffolding polyploid genome is that Hi-C signals are frequently detected between allelic haplotypes and any existing stat of art Hi-C scaffolding program links the allelic haplotypes together. To solve the problem, we developed a new Hi-C scaffolding pipeline, called ALLHIC, specifically tailored to the polyploid genomes. ALLHIC pipeline contains a total of 5 steps:&nbsp;</span><em>prune</em><span>,&nbsp;</span><em>partition</em><span>,&nbsp;</span><em>rescue</em><span>,&nbsp;</span><em>optimize</em><span>&nbsp;and&nbsp;</span><em>build</em><span>.</span></p><p>Address of the bookmark: <a href="https://github.com/tangerzhang/ALLHiC/wiki" rel="nofollow">https://github.com/tangerzhang/ALLHiC/wiki</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<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>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41686/catbat-tool-for-taxonomic-classification-of-contigs-and-metagenome-assembled-genomes-mags</guid>
	<pubDate>Mon, 18 May 2020 10:53:32 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41686/catbat-tool-for-taxonomic-classification-of-contigs-and-metagenome-assembled-genomes-mags</link>
	<title><![CDATA[CAT/BAT: tool for taxonomic classification of contigs and metagenome-assembled genomes (MAGs)]]></title>
	<description><![CDATA[<p>Contig Annotation Tool (CAT) and Bin Annotation Tool (BAT) are pipelines for the taxonomic classification of long DNA sequences and metagenome assembled genomes (MAGs/bins) of both known and (highly) unknown microorganisms, as generated by contemporary metagenomics studies. The core algorithm of both programs involves gene calling, mapping of predicted ORFs against the nr protein database, and voting-based classification of the entire contig / MAG based on classification of the individual ORFs. CAT and BAT can be run from intermediate steps if files are formated appropriately (see <a href="https://github.com/dutilh/CAT#usage">Usage</a>).</p><p>Address of the bookmark: <a href="https://github.com/dutilh/CAT" rel="nofollow">https://github.com/dutilh/CAT</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42357/irscope-an-online-program-to-visualize-the-junction-sites-of-chloroplast-genomes</guid>
	<pubDate>Wed, 25 Nov 2020 19:44:46 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42357/irscope-an-online-program-to-visualize-the-junction-sites-of-chloroplast-genomes</link>
	<title><![CDATA[IRscope: an online program to visualize the junction sites of chloroplast genomes]]></title>
	<description><![CDATA[<p><span>eMPRess, a software program for phylogenetic tree reconciliation under the duplication-transfer-loss model that systematically addresses the problems of choosing event costs and selecting representative solutions, enabling users to make more robust inferences.</span></p><p>Address of the bookmark: <a href="https://sites.google.com/g.hmc.edu/empress/home" rel="nofollow">https://sites.google.com/g.hmc.edu/empress/home</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44525/synorth-exploring-the-evolution-of-synteny-and-long-range-regulatory-interactions-in-vertebrate-genomes</guid>
	<pubDate>Mon, 06 May 2024 06:21:10 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44525/synorth-exploring-the-evolution-of-synteny-and-long-range-regulatory-interactions-in-vertebrate-genomes</link>
	<title><![CDATA[Synorth: exploring the evolution of synteny and long-range regulatory interactions in vertebrate genomes]]></title>
	<description><![CDATA[<p><span>Genomic regulatory blocks are chromosomal regions spanned by long clusters of highly conserved noncoding elements devoted to long-range regulation of developmental genes, often immobilizing other, unrelated genes into long-lasting syntenic arrangements. Synorth&nbsp;</span><a href="http://synorth.genereg.net/" target="_blank">http://synorth.genereg.net/</a><span>&nbsp;is a web resource for exploring and categorizing the syntenic relationships in genomic regulatory blocks across multiple genomes, tracing their evolutionary fate after teleost whole genome duplication at the level of genomic regulatory block loci, individual genes, and their phylogenetic context.</span></p>
<p><span>More at&nbsp;https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2745767/</span></p><p>Address of the bookmark: <a href="http://synorth.genereg.net/" rel="nofollow">http://synorth.genereg.net/</a></p>]]></description>
	<dc:creator>LEGE</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44873/bakrep-denglish-blend-of-bakterien-repository-simplifies-access-to-this-data</guid>
	<pubDate>Wed, 13 Aug 2025 02:31:28 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44873/bakrep-denglish-blend-of-bakterien-repository-simplifies-access-to-this-data</link>
	<title><![CDATA[BakRep (Denglish blend of Bakterien &amp; Repository) simplifies access to this data]]></title>
	<description><![CDATA[<p>2,438,386 bacterial genomes at your fingertips consistently processed &amp; characterized, enriched with metadata, accessible via a flexible search engine.</p>
<p>BakRep (Denglish blend of Bakterien &amp; Repository) simplifies access to this data. It integrates enriched genomic information with metadata accessible via a flexible search-engine.</p>
<h1>Key features</h1>
<ul>
<li>Assembly statistics: ensure data quality with genome-based key metrics</li>
<li>Taxonomic classification: robust, purely genome-based classifications (<a href="https://gtdb.ecogenomic.org/" target="_blank">GTDB</a>)</li>
<li><a href="https://pubmlst.org/">MLST</a>: subtyping for deeper insights into genetic variation</li>
<li>Annotation: comprehensive &amp; taxonomy-independent (<a href="https://bakta.computational.bio/" target="_blank">Bakta</a>)</li>
<li>Metadata: full original submission records</li>
</ul>
<div>&nbsp;</div><p>Address of the bookmark: <a href="https://bakrep.computational.bio/" rel="nofollow">https://bakrep.computational.bio/</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
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	<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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