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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/1515?offset=1050</link>
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	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/32011/fools-guide</guid>
	<pubDate>Sun, 02 Apr 2017 14:31:18 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/32011/fools-guide</link>
	<title><![CDATA[Fools guide]]></title>
	<description><![CDATA[<p><span>This website and accompaning documents are intended as a tool to help researchers dealing with non-model organisms acquire and process transcriptomic high-throughput sequencing data without having to learn extensive bioinformatics skills. It covers all steps from tissue collection, sample preparation and computer setup, through addressing biological questions with gene expression and SNP data.</span></p>
<p>http://sfg.stanford.edu/denovo.html</p>
<p>http://sfg.stanford.edu/sequencing.html</p>
<p>http://sfg.stanford.edu/BLAST.html</p>
<p>http://sfg.stanford.edu/denovo.html&nbsp;</p><p>Address of the bookmark: <a href="http://sfg.stanford.edu/guide.html" rel="nofollow">http://sfg.stanford.edu/guide.html</a></p>]]></description>
	<dc:creator>Poonam Mahapatra</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/862/dumontier-lab</guid>
  <pubDate>Sun, 14 Jul 2013 12:51:42 -0500</pubDate>
  <link></link>
  <title><![CDATA[Dumontier Lab]]></title>
  <description><![CDATA[
<p>Our research aims to better understand how living systems respond to chemical agents. A key aspect of our approach involves using computational frameworks that are powered by formal (i.e. machine understandable) semantics to make effectively use of vast and diverse amounts of biomedical knowledge. We are particularly interested in understanding how the response to chemical exposure is modulated by genetic and physiological variation among individuals and how this translates into altered capabilities at the molecular level.</p>

<p>Research Area</p>

<p>the discovery and on-demand use of biomedical data and services<br />the formulation, discovery and evaluation of scientific hypotheses<br />the simulation of biological systems at the level of individual molecules</p>

<p>Link @ http://dumontierlab.com/</p>
]]></description>
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<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/32129/lordec-a-hybrid-error-correction-program-for-long-pacbio-reads</guid>
	<pubDate>Mon, 10 Apr 2017 04:16:09 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/32129/lordec-a-hybrid-error-correction-program-for-long-pacbio-reads</link>
	<title><![CDATA[LoRDEC: a hybrid error correction program for long, PacBio reads]]></title>
	<description><![CDATA[<p>LoRDEC is a program to correct sequencing errors in long reads from 3rd generation sequencing with high error rate, and is especially intended for PacBio reads. It uses a hybrid strategy, meaning that it uses two sets of reads: the reference read set, whose error rate is assumed to be small, and the PacBio read set, which is then corrected using the reference set. Typically, the reference set contains Illumina reads.</p>
<p><br> Usually, errors in PacBio reads include many insertions and deletions, and comparatively less substitutions. LoRDEC can correct errors of all these types.<br> After correction, a larger portion of the sequence of PacBio reads is usable for detection of region of similarity with other sequences, for aligning them to the contigs of an assembly, etc.</p>
<p>Why is LoRDEC different?</p>
<ul>
<li>It is efficient and can process large read data sets, included from eukaryotic or vertebrate species, on a usual computing server, and even works on desktop/laptop computers.</li>
<li>It adopts a novel graph based approach: it builds a succinct De Bruijn Graph (DBG) representing the short reads, and seeks a corrective sequence for each erroneous region of a long read by traversing chosen paths in the graph.</li>
</ul><p>Address of the bookmark: <a href="http://www.atgc-montpellier.fr/lordec/" rel="nofollow">http://www.atgc-montpellier.fr/lordec/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/32154/decostar-detection-of-co-evolution</guid>
	<pubDate>Fri, 14 Apr 2017 06:27:25 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/32154/decostar-detection-of-co-evolution</link>
	<title><![CDATA[DeCoSTAR - Detection of Co-evolution]]></title>
	<description><![CDATA[<p><span>DeCoSTAR is a software which aims at reconstructing ancestral gene or genome organizations, in the form of sets of neighborhood relations -adjacencies- between pairs of ancestral genes or gene domains.</span><br><span>Ancestral genes or domains are deduced from reconciled gene trees in a context of birth, speciation, duplication, loss, transfer, which are either given as input or computed with the&nbsp;</span><a href="http://mbb.univ-montp2.fr/MBB/download_sources/16__TERA">ecceTERA package</a><span>, to which DeCoSTAR is integrated. DeCoSTAR constructs parsimonious scenarios of gains and breakages of adjacencies, and contains in particular all the features of previous software DeCo, DeCoLT, ArtDeCo and DeClone. It provides statistical supports on ancestral adjacencies, or the possibility to handle badly assembled genomes.&nbsp;</span><br><span>DeCoSTAR is able to reconstruct the histories of domains inside genes, including gene fusion and fission events, as well as ancestral genome structures for dozens of whole genomes from all kingdoms of life in a few minutes.</span></p><p>Address of the bookmark: <a href="http://pbil.univ-lyon1.fr/software/DeCoSTAR/" rel="nofollow">http://pbil.univ-lyon1.fr/software/DeCoSTAR/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/868/the-upton-vbrc-lab</guid>
  <pubDate>Sun, 14 Jul 2013 13:25:41 -0500</pubDate>
  <link></link>
  <title><![CDATA[The Upton (VBRC) lab]]></title>
  <description><![CDATA[
<p>This Bioinformatics Resource (Virology.ca, the Canadian half of the now defunct VBRC)  focuses on large DNA viruses:<br />Poxviruses<br />African Swine Fever Viruses<br />Iridoviruses<br />Baculoviruses</p>

<p>Research Area</p>

<p>Custom searches of the viral databases<br />Building new tools .<br />The genome annotation<br /> <br />Link @ http://athena.bioc.uvic.ca/</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/32399/mapping-ngs</guid>
	<pubDate>Tue, 02 May 2017 07:58:07 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/32399/mapping-ngs</link>
	<title><![CDATA[Mapping NGS]]></title>
	<description><![CDATA[<p>NGS data are just a bunch of sequences, you have no idea which region in the genome each sequences comes from, which gene it represents...<br>To know that you have to align the sequences to the reference sequence. The reference sequence is in most cases the full genome sequence but sometimes, a library of EST sequences is used.<br>In either way, aligning your sequence reads to the reference sequence is called mapping.</p>
<p>The most used mappers of DNA-seq data are&nbsp;<a href="http://bio-bwa.sourceforge.net/" target="_blank">BWA</a>&nbsp;and&nbsp;<a href="http://bowtie-bio.sourceforge.net/bowtie2/index.shtml" target="_blank">Bowtie</a>&nbsp;for DNA-Seq data and&nbsp;<a href="http://tophat.cbcb.umd.edu/" target="_blank">Tophat</a>,&nbsp;<a href="https://github.com/alexdobin/STAR" target="_blank">STAR</a>&nbsp;or&nbsp;<a href="http://www.ccb.jhu.edu/software/hisat/index.shtml" target="_blank">HISAT</a>&nbsp;for RNA-Seq data. Mappers differ in which options they can take in, how fast and how accurate they are. Bowtie is faster than BWA, but looses some sensitivity (does not map an equal amount of reads to the correct position in the genome).</p><p>Address of the bookmark: <a href="http://wiki.bits.vib.be/index.php/Mapping_of_NGS_data" rel="nofollow">http://wiki.bits.vib.be/index.php/Mapping_of_NGS_data</a></p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/926/list-of-popular-bioinformatics-softwaretools</guid>
	<pubDate>Tue, 16 Jul 2013 14:30:30 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/926/list-of-popular-bioinformatics-softwaretools</link>
	<title><![CDATA[List of popular bioinformatics software/tools]]></title>
	<description><![CDATA[<p><a href="http://samtools.sourceforge.net/swlist.shtml">I</a>n current genome era, our day to day work is to handle the huge geneome sequences, expression data, several other datasets. This link provide a comprehensive list of commonly used sofware/tools.</p><p>Address of the bookmark: <a href="http://samtools.sourceforge.net/swlist.shtml" rel="nofollow">http://samtools.sourceforge.net/swlist.shtml</a></p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/32483/cla-contig-layout-authenticator</guid>
	<pubDate>Fri, 05 May 2017 05:58:36 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/32483/cla-contig-layout-authenticator</link>
	<title><![CDATA[CLA: Contig-Layout-Authenticator]]></title>
	<description><![CDATA[<p><span>To improve upon the shortcomings associated with the construction of draft genomes with Illumina paired-end sequencing, we developed Contig-Layout-Authenticator (CLA). The CLA pipeline can scaffold reference-sorted contigs based on paired reads, resulting in better assembled genomes. Moreover, CLA also hints at probable misassemblies and contaminations, for the users to cross-check before constructing the consensus draft. The CLA pipeline was designed and trained extensively on various bacterial genome datasets for the ordering and scaffolding of large repetitive contigs. The tool has been validated and compared favorably with other widely-used scaffolding and ordering tools using both simulated and real sequence datasets. CLA is a user friendly tool that requires a single command line input to generate ordered scaffolds.</span></p>
<p><span>Script&nbsp;https://sourceforge.net/projects/c-l-authenticator/files/</span></p><p>Address of the bookmark: <a href="http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0155459" rel="nofollow">http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0155459</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/32629/bienko-and-crosetto-labs</guid>
  <pubDate>Fri, 12 May 2017 07:42:15 -0500</pubDate>
  <link></link>
  <title><![CDATA[Bienko and Crosetto Labs]]></title>
  <description><![CDATA[
<p>We are two groups of scientists doing frontier research in quantitative biology and biomedicine. The Bienko group is interested in exploring the fundamental design principles controlling how DNA is packed in the eukaryotic nucleus and its relation to gene expression regulation. The Crosetto group engineers new molecular methods for single-cell and spatially resolved omic measurements of DNA, RNA, and proteins, with a strong focus on tumor heterogeneity. By sharing ideas and resources, we work synergistically towards a more quantitative understanding of life’s processes in healthy and diseased conditions.</p>

<p>https://bienkocrosettolabs.org/</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/file/view/2780/life-of-bi</guid>
	<pubDate>Thu, 22 Aug 2013 16:13:36 -0500</pubDate>
	<link>https://bioinformaticsonline.com/file/view/2780/life-of-bi</link>
	<title><![CDATA[Life of BI !!!]]></title>
	<description><![CDATA[<p>Hmm .. Don't worry you read it right .. this is not pi but bi ... "life of Bioinformatician(BI)".&nbsp;</p><p><span>Disclaimer:</span>&nbsp;This cartoon is solely designed to create humour and fun, not to offend any PI, supervisor or student.</p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
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