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	<title><![CDATA[BOL: Related items]]></title>
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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>
	
</item>
<item>
	<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>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34718/dipspades-assembler-for-highly-polymorphic-diploid-genomes</guid>
	<pubDate>Wed, 20 Dec 2017 18:35:16 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34718/dipspades-assembler-for-highly-polymorphic-diploid-genomes</link>
	<title><![CDATA[dipSPAdes: Assembler for Highly Polymorphic Diploid Genomes.]]></title>
	<description><![CDATA[<p><span>While the number of sequenced diploid genomes have been steadily increasing in the last few years, assembly of highly polymorphic (HP) diploid genomes remains challenging. As a result, there is a shortage of tools for assembling HP genomes from the next generation sequencing (NGS) data. The initial approaches to assembling HP genomes were proposed in the pre-NGS era and are not well suited for NGS projects. To address this limitation, we developed the first de Bruijn graph assembler, dipSPAdes, for HP genomes that significantly improves on the state-of-the-art assemblers for HP diploid genomes.</span></p><p>Address of the bookmark: <a href="https://www.ncbi.nlm.nih.gov/pubmed/25734602" rel="nofollow">https://www.ncbi.nlm.nih.gov/pubmed/25734602</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/35418/karyoploter-plot-whole-genomes-with-arbitrary-data</guid>
	<pubDate>Fri, 02 Feb 2018 03:24:28 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/35418/karyoploter-plot-whole-genomes-with-arbitrary-data</link>
	<title><![CDATA[karyoploteR: plot whole genomes with arbitrary data]]></title>
	<description><![CDATA[<p><span><a href="http://bioconductor.org/packages/karyoploteR">karyoploteR</a></span><span>&nbsp;is an R package to create karyoplots, that is, representations of whole genomes with arbitrary data plotted on them. It is inspired by the R base graphics system and does not depend on other graphics packages. The aim of karyoploteR is to offer the user an easy way to plot data along the genome to get broad genome-wide view to facilitate the identification of genome wide relations and distributions.</span></p><p>Address of the bookmark: <a href="https://bernatgel.github.io/karyoploter_tutorial/" rel="nofollow">https://bernatgel.github.io/karyoploter_tutorial/</a></p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
</item>
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	<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/bookmarks/view/36590/digest-in-silico-restriction-digest-of-complete-genomes</guid>
	<pubDate>Mon, 14 May 2018 04:02:52 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36590/digest-in-silico-restriction-digest-of-complete-genomes</link>
	<title><![CDATA[Digest: In silico restriction digest of complete genomes]]></title>
	<description><![CDATA[<p><span>This tool allows to retrieve number of cleavages yielded by commercially available endonucleases in up-to-date sequenced prokaryotic genomes. When the number of fragments is bellow 50, Pulse Field gel Electrophoresis (PFGE) is simulated.</span></p>
<p>A tool for restriction digest of&nbsp;<a href="http://insilico.ehu.eus/restriction/long_seq/">long</a>user's sequences is available.</p>
<p>&nbsp;</p><p>Address of the bookmark: <a href="http://insilico.ehu.es/digest/" rel="nofollow">http://insilico.ehu.es/digest/</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/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/40409/haplotypo-a-variant-calling-pipeline-for-phased-genomes</guid>
	<pubDate>Thu, 19 Dec 2019 07:33:40 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40409/haplotypo-a-variant-calling-pipeline-for-phased-genomes</link>
	<title><![CDATA[HaploTypo: a variant-calling pipeline for phased genomes]]></title>
	<description><![CDATA[<p>An increasing number of phased (i.e. with resolved haplotypes) reference genomes are available. However, most genetic variant calling tools do not explicitly account for haplotype structure. Here, we present HaploTypo, a pipeline tailored to resolve haplotypes in genetic variation analyses. HaploTypo infers the haplotype correspondence for each heterozygous variant called on a phased reference genome.</p>
<div>Availability and Implementation</div>
<p>HaploTypo is implemented in Python 2.7 and Python 3.5, and is freely available at&nbsp;<a href="https://github.com/gabaldonlab/haplotypo" target="">https://github.com/gabaldonlab/haplotypo</a>, and as a Docker image.</p><p>Address of the bookmark: <a href="https://github.com/gabaldonlab/haplotypo" rel="nofollow">https://github.com/gabaldonlab/haplotypo</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

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