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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/30149?offset=100</link>
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	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/videolist/watch/19555/a-3d-map-of-the-human-genome</guid>
	<pubDate>Fri, 12 Dec 2014 22:27:55 -0600</pubDate>
	<link>https://bioinformaticsonline.com/videolist/watch/19555/a-3d-map-of-the-human-genome</link>
	<title><![CDATA[A 3D Map of the Human Genome]]></title>
	<description><![CDATA[<iframe width="" height="" src="https://www.youtube-nocookie.com/embed/dES-ozV65u4" frameborder="0" allowfullscreen></iframe>Suhas Rao and Miriam Huntley (of the Aiden Lab) describe a 3D map of the human genome at kilobase resolution, revealing the principles of chromatin looping. Guest Origami Folding: Sarah Nyquist.

Suhas S.P. Rao*, Miriam H. Huntley*, Neva C. Durand, Elena K. Stamenova, Ivan D. Bochkov, James T. Robinson, Adrian L. Sanborn, Ido Machol, Arina D. Omer, Eric S. Lander, Erez Lieberman Aiden. (2014). A 3D Map of the Human Genome at Kilobase Resolution Reveals Principles of Chromatin Looping. Cell.]]></description>
	
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44168/environmental-genomics-group-scilifelabkth-stockholm</guid>
	<pubDate>Thu, 01 Dec 2022 01:12:43 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44168/environmental-genomics-group-scilifelabkth-stockholm</link>
	<title><![CDATA[Environmental Genomics Group SciLifeLab/KTH Stockholm]]></title>
	<description><![CDATA[<p>Useful Metagenomics resources</p><p>Address of the bookmark: <a href="https://github.com/envgen" rel="nofollow">https://github.com/envgen</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/22793/sequencing-by-xpansion</guid>
	<pubDate>Wed, 17 Jun 2015 20:58:11 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/22793/sequencing-by-xpansion</link>
	<title><![CDATA[Sequencing By Xpansion]]></title>
	<description><![CDATA[<p>Sequencing By Xpansion (SBX) is a DNA sequencing method that uses a simple biochemical reaction to encode the sequence of a DNA molecule into a highly measurable surrogate called an Xpandomer. This single molecule approach produces enough Xpandomer in a single drop reaction to sequence an entire human genome 1000X over. To achieve this, an Xpandomer replaces each DNA sequence with a sequence of large, high signal reporter molecules using the SBX molecular expansion technology. The DNA sequence is then read out as the Xpandomer reporters pass sequentially through a nanopore detector. SBX is a molecular engineering platform that benefits from core design principles that separate the multiple molecular functions. This systems approach enables efficient development and incorporation of improvements to SBX and is key to reconfiguring and optimizing Xpandomer measurement for different detection platforms.</p><p>http://www.stratosgenomics.com/stratos-genomics-technology</p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/26569/genome-stability-laboratory</guid>
  <pubDate>Mon, 07 Mar 2016 04:16:32 -0600</pubDate>
  <link></link>
  <title><![CDATA[Genome Stability Laboratory]]></title>
  <description><![CDATA[
<p>The bakers yeast, Saccharomyces cerevisiae is an ideal model organism to understand mechanisms of meiotic chromosome segregation. In S. cerevisiae and in mammals, the majority of meiotic crossovers are formed through a highly conserved MSH4p-MSH5p, MLH1p-MLH3p dependent pathway. We are interested in charactering the role of these complexes in crossover formation and distribution among all homolog pairs. Errors in this process are linked to congenital birth defects in humans such as Down's syndrome.Our laboratory is also interested in understanding the effect of genetic background on mutation rate variation using S. cerevisiae as a model. These studies are relevant for understanding cancer progression, genome evolution and architecture. We use high- throughput genomic methods as well as classical genetics to achieve these aims. </p>

<p>More at http://faculty.iisertvm.ac.in/~nishantkt/index.html</p>
]]></description>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/26499/katju-lab</guid>
  <pubDate>Fri, 26 Feb 2016 03:25:32 -0600</pubDate>
  <link></link>
  <title><![CDATA[Katju Lab]]></title>
  <description><![CDATA[
<p>TheLab seek to understand the genetic factors contributing to genomic variation and phenotypic diversity.  To this end, we employ molecular and bioinformatic tools to study evolutionary processes at the level of populations, both experimental and natural, and genomes.  Our research interests encompass a wide range of topics, including the evolution of organellar and nuclear genomes, gene duplication and the origin of novel function, and the fitness and phenotypic consequences of mutation in evolution. For details regards ongoing projects, please see the Research page.</p>

<p>http://katjulab.com/research.html</p>
]]></description>
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<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/26414/advanced-bash-scripting-guide</guid>
	<pubDate>Thu, 18 Feb 2016 04:50:51 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/26414/advanced-bash-scripting-guide</link>
	<title><![CDATA[Advanced Bash-Scripting Guide]]></title>
	<description><![CDATA[<p>This tutorial assumes no previous knowledge of scripting or programming, yet progresses rapidly toward an intermediate/advanced level of instruction <em>. . . all the while sneaking in little nuggets of <span>UNIX</span>&reg; wisdom and lore</em>. It serves as a textbook, a manual for self-study, and as a reference and source of knowledge on shell scripting techniques. The exercises and heavily-commented examples invite active reader participation, under the premise that <tt><strong>the only way to really learn scripting is to write scripts</strong></tt>.</p>
<p>This book is suitable for classroom use as a general introduction to programming concepts.</p>
<p>More at http://tldp.org/LDP/abs/html/</p><p>Address of the bookmark: <a href="http://tldp.org/LDP/abs/html/" rel="nofollow">http://tldp.org/LDP/abs/html/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27090/canu-assembling-large-genomes-with-single-molecule-sequencing-and-locality-sensitive-hashing</guid>
	<pubDate>Tue, 26 Apr 2016 11:38:10 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27090/canu-assembling-large-genomes-with-single-molecule-sequencing-and-locality-sensitive-hashing</link>
	<title><![CDATA[CANU: Assembling Large Genomes with Single-Molecule Sequencing and Locality Sensitive Hashing.]]></title>
	<description><![CDATA[<p>Canu is a fork of the&nbsp;<a href="http://wgs-assembler.sourceforge.net/wiki/index.php?title=Main_Page" title="Celera Assembler">Celera Assembler</a>&nbsp;designed for high-noise single-molecule sequencing (such as the PacBio RSII or Oxford Nanopore MinION). The software is currently alpha level, feel free to use and report issues encountered.</p>
<p>Canu is a hierachical assembly pipeline which runs in four steps:</p>
<ul>
<li>Detect overlaps in high-noise sequences using&nbsp;<a href="https://github.com/marbl/MHAP" title="MHAP">MHAP</a></li>
<li>Generate corrected sequence consensus</li>
<li>Trim corrected sequences</li>
<li>Assemble trimmed corrected sequences</li>
</ul>
<p>Read the&nbsp;<a href="http://canu.readthedocs.org/" title="docs">documentation</a></p>
<p>New release https://github.com/marbl/canu/releases</p><p>Address of the bookmark: <a href="https://github.com/marbl/canu" rel="nofollow">https://github.com/marbl/canu</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/28809/kissplice</guid>
	<pubDate>Tue, 16 Aug 2016 08:34:19 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/28809/kissplice</link>
	<title><![CDATA[KisSplice]]></title>
	<description><![CDATA[<p>KisSplice is a software that enables to analyse RNA-seq data with or without a reference genome. It is an exact local transcriptome assembler that allows to identify SNPs, indels and alternative splicing events. It can deal with an arbitrary number of biological conditions, and will quantify each variant in each condition. It has been tested on Illumina datasets of up to 1G reads. Its memory consumption is around 5Gb for 100M reads.</p>
<p>KisSplice is not a full-length transcriptome assembler. This means that it will output the variable regions of the transcripts, not reconstruct them entirely.</p>
<p>KisSplice comes as a workflow, with several possible post-treatments meant to facilitate the analysis of the results. The choice of the post-treatment depends on the availability of a reference genome/transcriptome and on the need to perform a differential analysis, as summarised in the following table.</p><p>Address of the bookmark: <a href="http://kissplice.prabi.fr/" rel="nofollow">http://kissplice.prabi.fr/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/28835/a5-miseq</guid>
	<pubDate>Thu, 18 Aug 2016 04:05:23 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/28835/a5-miseq</link>
	<title><![CDATA[A5-miseq]]></title>
	<description><![CDATA[<p><span><span>_A5-miseq_ is a pipeline for assembling DNA sequence data generated on the Illumina sequencing platform. This README will take you through the steps necessary for running _A5-miseq_. </span></span></p>
<p><span>Point to note:</span></p>
<p><span>There are many situations where A5-miseq is not the right tool for the job. In order to produce accurate results, A5-miseq requires Illumina data with certain characteristics. A5-miseq will likely not work well with Illumina reads shorter than around 80nt, or reads where the base qualities are low in all or most reads before 60nt. A5-miseq assumes it is assembling homozygous haploid genomes. Use a different assembler for metagenomes and heterozygous diploid or polyploid organisms. Use a different assembler if a tool like FastQC reports your data quality is dubious. You have been warned! Datasets consisting solely of unpaired reads are not currently supported.</span></p><p>Address of the bookmark: <a href="https://sourceforge.net/projects/ngopt/" rel="nofollow">https://sourceforge.net/projects/ngopt/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/29235/valet</guid>
	<pubDate>Thu, 22 Sep 2016 04:27:09 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/29235/valet</link>
	<title><![CDATA[valet]]></title>
	<description><![CDATA[<div>
<div>
<div>VALET is a pipeline for performing&nbsp;<em>de novo</em>&nbsp;validation of metagenomic assemblies. VALET checks a number of properties that should hold true for a correct assembly (e.g., mate-pairs are aligned at the correct distance from each other in the assembly, the depth of coverage is fairly uniform along contigs, etc.). The violations of these invariants are reported allowing one to pinpoint areas that were potentially mis-assembled, or to compare the quality of different assemblies. For comparing multiple assemblies of the same data-sets, VALET also reports an overall estimate of the likelihood a particular assembly is correct.</div>
</div>
</div>
<div>
<div>Home Page:&nbsp;</div>
<div>
<div><a href="https://github.com/jgluck/VALET">VALET code repository</a></div>
</div>
</div><p>Address of the bookmark: <a href="https://www.cbcb.umd.edu/software/valet" rel="nofollow">https://www.cbcb.umd.edu/software/valet</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

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