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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/31024?</link>
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	<description><![CDATA[]]></description>
	
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38055/ancestral-genomes-a-resource-for-reconstructed-ancestral-genes-and-genomes-across-the-tree-of-life</guid>
	<pubDate>Fri, 02 Nov 2018 08:16:27 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38055/ancestral-genomes-a-resource-for-reconstructed-ancestral-genes-and-genomes-across-the-tree-of-life</link>
	<title><![CDATA[Ancestral Genomes: a resource for reconstructed ancestral genes and genomes across the tree of life]]></title>
	<description><![CDATA[<p><span>&nbsp;Ancestral Genomes (</span><a href="http://ancestralgenomes.org/" target="">http://ancestralgenomes.org</a><span>) is a resource for comprehensive reconstructions of these &lsquo;fossil genomes&rsquo;. Comprehensive sets of protein-coding genes have been reconstructed for 78 genomes of now-extinct species that were the common ancestors of extant species from across the tree of life.&nbsp;</span></p><p>Address of the bookmark: <a href="http://ancestralgenomes.org/" rel="nofollow">http://ancestralgenomes.org/</a></p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27427/rcircos-an-r-package-for-circos-2d-track-plots</guid>
	<pubDate>Fri, 20 May 2016 11:01:13 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27427/rcircos-an-r-package-for-circos-2d-track-plots</link>
	<title><![CDATA[RCircos: an R package for Circos 2D track plots]]></title>
	<description><![CDATA[<p>RCircos package provides a simple and flexible way to make Circos 2D track plots with R and could be easily integrated into other R data processing and graphic manipulation pipelines for presenting large-scale multi-sample genomic research data. It can also serve as a base tool to generate complex Circos images.</p>
<p>More at https://bitbucket.org/henryhzhang/rcircos/src</p><p>Address of the bookmark: <a href="https://bitbucket.org/henryhzhang/rcircos/src" rel="nofollow">https://bitbucket.org/henryhzhang/rcircos/src</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27463/bpipe-a-tool-for-running-and-managing-bioinformatics-pipelines</guid>
	<pubDate>Sat, 21 May 2016 22:42:16 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27463/bpipe-a-tool-for-running-and-managing-bioinformatics-pipelines</link>
	<title><![CDATA[Bpipe - a tool for running and managing bioinformatics pipelines]]></title>
	<description><![CDATA[<p>Bpipe provides a platform for running big bioinformatics jobs that consist of a series of processing stages - known as 'pipelines'.</p>
<ul>
<li>January 20th, 2016 - New! Bpipe 0.9.9 released!</li>
<li>Download <a href="http://download.bpipe.org/versions/bpipe-0.9.9.tar.gz">latest</a>, <a href="http://download.bpipe.org">all</a></li>
<li><a href="http://docs.bpipe.org">Documentation</a></li>
<li><a href="https://groups.google.com/forum/#%21forum/bpipe-discuss">Mailing List</a> (Google Group)</li>
</ul>
<p>Bpipe has been published in <a href="http://bioinformatics.oxfordjournals.org/content/early/2012/04/11/bioinformatics.bts167.abstract">Bioinformatics</a>! If you use Bpipe, please cite:</p>
<p><em>Sadedin S, Pope B &amp; Oshlack A, Bpipe: A Tool for Running and Managing Bioinformatics Pipelines, Bioinformatics</em></p><p>Address of the bookmark: <a href="http://docs.bpipe.org/" rel="nofollow">http://docs.bpipe.org/</a></p>]]></description>
	<dc:creator>Radha Agarkar</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27479/biogps</guid>
	<pubDate>Mon, 23 May 2016 03:15:46 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27479/biogps</link>
	<title><![CDATA[BioGPS]]></title>
	<description><![CDATA[<p>A free&nbsp;<em>extensible</em>&nbsp;and&nbsp;<em>customizable</em>&nbsp;<strong>gene annotation portal</strong>, a complete resource for learning about&nbsp;<strong>gene and protein function</strong>.</p>
<p>http://biogps.org/#goto=welcome</p><p>Address of the bookmark: <a href="http://biogps.org/#goto=welcome" rel="nofollow">http://biogps.org/#goto=welcome</a></p>]]></description>
	<dc:creator>Anjana</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27959/darkhorse</guid>
	<pubDate>Wed, 22 Jun 2016 05:37:38 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27959/darkhorse</link>
	<title><![CDATA[DarkHorse]]></title>
	<description><![CDATA[<p><em>DarkHorse</em>&nbsp;is a bioinformatic method for rapid, automated identification and ranking of phylogenetically atypical proteins on a genome-wide basis. It works by selecting potential ortholog matches from a reference database of amino acid sequences, then using these matches to calculate a lineage probability index (LPI) score for each genome protein.</p>
<p>LPI scores are inversely proportional to the phylogenetic distance between database match sequences and the query genome. These scores are useful not only for large-scale<em>de novo</em>&nbsp;predictions of horizontally transferred proteins, but can also serve as an independent quality control test for potential horizontal transfer candidates identified by alternative methods, especially those based on nucleic acid signatures. Candidates having high LPI scores are unlikely to have been horizontally transferred, since they are highly conserved among closely related organisms.</p>
<p>One unique and powerful feature of the DarkHorse HGT Candidate database is the opportunity to explore the phylogenetic background of potential HGT donors as well as recipients. The breadth of the database allows not only query sequences, but also their database match partners to be evaluated for sequence similarity or novelty compared to taxonomically related organisms.</p>
<p><em>DarkHorse</em>&nbsp;is configurable for varying degrees of phylogenetic granularity and protein sequence conservation. Users should consult the&nbsp;<a href="http://darkhorse.ucsd.edu/#references">references</a>&nbsp;cited below for a complete explanation of parameter selection and result interpretation. A brief&nbsp;<a href="http://darkhorse.ucsd.edu/tutorial.html">tutorial</a>&nbsp;page is also available on-line.</p><p>Address of the bookmark: <a href="http://darkhorse.ucsd.edu/download.html" rel="nofollow">http://darkhorse.ucsd.edu/download.html</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
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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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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/43292/bioinformatics-scientist-production-bioinformatics-south-san-francisco-ca</guid>
  <pubDate>Thu, 19 Aug 2021 08:45:24 -0500</pubDate>
  <link></link>
  <title><![CDATA[Bioinformatics Scientist, Production Bioinformatics @ South San Francisco, CA]]></title>
  <description><![CDATA[
<p>wist is looking for a Bioinformatics Scientist to join our Production Bioinformatics Team. You will work alongside research scientists, software engineers and data scientists to further deliver on our mission to expand access to best-in-class synthetic biology and next-generation sequencing applications. You will be developing and engineering tools to better evaluate and build hardened, production quality pipelines, optimize data quality, and automate lab and bioinformatics processes. Our ideal candidate is an organized problem solver with a background in developing and building novel production-quality bioinformatics tools and packages. Equally excellent communication skills and a proven ability to work independently are required.</p>

<p>More at https://boards.greenhouse.io/twistbioscience/jobs/3135495?gh_src=9ecc0b941us</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/36870/understanding-liftover</guid>
	<pubDate>Wed, 06 Jun 2018 10:00:20 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/36870/understanding-liftover</link>
	<title><![CDATA[Understanding liftOver !]]></title>
	<description><![CDATA[<p>LiftOver is a necesary step to bring all genetical analysis to the same reference build. LiftOver can have three use cases:</p><p>(1) <a href="https://genome.sph.umich.edu/wiki/LiftOver#Lift_genome_positions">Convert genome position from one genome assembly to another genome assembly</a></p><p>In most scenarios, we have known genome positions in NCBI build 36 (UCSC hg 18) and hope to lift them over to NCBI build 37 (UCSC hg19).</p><p>(2) <a href="https://genome.sph.umich.edu/wiki/LiftOver#Lift_dbSNP_rs_numbers">Convert dbSNP rs number from one build to another</a></p><p>(3) <a href="https://genome.sph.umich.edu/wiki/LiftOver#Lift_Merlin.2FPLINK_format">Convert both genome position and dbSNP rs number over different versions</a></p><p>Run:</p><pre>liftOver input.bed hg18ToHg19.over.chain.gz output.bed unlifted.bed</pre><p>The outformat is as follow:</p><pre>Deleted in new:
    Sequence intersects no chains
Partially deleted in new:
    Sequence insufficiently intersects one chain
Split in new:
    Sequence insufficiently intersects multiple chains
Duplicated in new:
    Sequence sufficiently intersects multiple chains
Boundary problem:
    Missing start or end base in an exon</pre><p>For example:</p><p>If you liftOver <span>chr4:6497-6497 from <span>hg19 to GRch38 </span>and it return "deleted in new". </span></p><p>It means chr4:6497-6497 is part of a genomic contig on hg19 that is not anymore mapped on GRch38 because the new assembly is now better built without including this contig.</p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37980/csbfinder-discovery-of-colinear-syntenic-blocks-across-thousands-of-prokaryotic-genomes</guid>
	<pubDate>Wed, 24 Oct 2018 22:12:27 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37980/csbfinder-discovery-of-colinear-syntenic-blocks-across-thousands-of-prokaryotic-genomes</link>
	<title><![CDATA[CSBFinder: Discovery of colinear syntenic blocks across thousands of prokaryotic genomes]]></title>
	<description><![CDATA[<p>CSBFinder is a standalone Desktop java application with a graphical user interface, that can also be executed via command line.</p>
<p>CSBFinder implements a novel methodology for the discovery, ranking, and taxonomic distribution analysis of colinear syntenic blocks (<span>CSBs</span>) - groups of genes that are consistently located close to each other, in the same order, across a wide range of taxa. CSBFinder incorporates an efficient algorithm that identifies CSBs in large genomic datasets. The discovered CSBs are ranked according to a probabilistic score and clustered to families according to their gene content similarity.</p><p>Address of the bookmark: <a href="https://github.com/dinasv/CSBFinder" rel="nofollow">https://github.com/dinasv/CSBFinder</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27850/clusterprofiler</guid>
	<pubDate>Thu, 16 Jun 2016 18:57:03 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27850/clusterprofiler</link>
	<title><![CDATA[clusterProfiler]]></title>
	<description><![CDATA[<p>statistical analysis and visulization of functional profiles for genes and gene clusters<br><br>Bioconductor version: Release (3.3)<br><br>This package implements methods to analyze and visualize functional profiles (GO and KEGG) of gene and gene clusters.<br><br>Author: Guangchuang Yu &lt;guangchuangyu at gmail.com&gt; with contributions from Li-Gen Wang and Giovanni Dall'Olio.<br><br>Maintainer: Guangchuang Yu &lt;guangchuangyu at gmail.com&gt;<br><br>Citation (from within R, enter citation("clusterProfiler")):<br><br>Yu G, Wang L, Han Y and He Q (2012). &ldquo;clusterProfiler: an R package for comparing biological themes among gene clusters.&rdquo; OMICS: A Journal of Integrative Biology, 16(5), pp. 284-287.<br>Installation<br><br>To install this package, start R and enter:<br><br>## try http:// if https:// URLs are not supported<br>source("https://bioconductor.org/biocLite.R")<br>biocLite("clusterProfiler")</p>
<p>https://www.bioconductor.org/packages/devel/bioc/vignettes/clusterProfiler/inst/doc/clusterProfiler.html</p><p>Address of the bookmark: <a href="https://www.bioconductor.org/packages/devel/bioc/vignettes/clusterProfiler/inst/doc/clusterProfiler.html" rel="nofollow">https://www.bioconductor.org/packages/devel/bioc/vignettes/clusterProfiler/inst/doc/clusterProfiler.html</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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