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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/43614?offset=260</link>
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	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27216/yass-genomic-similarity-search-tool</guid>
	<pubDate>Mon, 02 May 2016 09:26:00 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27216/yass-genomic-similarity-search-tool</link>
	<title><![CDATA[YASS :: genomic similarity search tool]]></title>
	<description><![CDATA[<p>YASS is a genomic similarity search tool, for nucleic (DNA/RNA) sequences in fasta or plain text format (<em>it produces local pairwise alignments</em>). Like most of the heuristic pairwise local alignment tools for DNA sequences (FASTA, BLAST, PATTERNHUNTER, BLASTZ/LASTZ, LAST ...), YASS uses <em>seeds</em> to detect potential similarity regions, and then tries to extend them to local alignments. This genomic search tool uses <em>multiple transition constrained spaced seeds</em> that enable to search more fuzzy repeats, as non-coding DNA/RNA. Another simple, but interesting feature is that you can specify the seed pattern used in the search step (as provided for example by <a href="http://bioinfo.lifl.fr/yass/iedera.php">iedera</a>).</p>
<p>Main features of YASS are:</p>
<ul>
<li>multiple, possibly overlapping seeds and a new hit criterion to ensure a good sensitivity/selectivity trade-off</li>
<li>transition-constrained spaced seeds to improve sensitivity (transition mutations are purine to purine [<code>A&lt;-&gt;G</code>] or pyrimidine to pyrimidine [<code>C&lt;-&gt;T</code>])</li>
<li>using different scoring schemes with bit-score and E-value evaluated according to the sequence background frequencies</li>
<li>parameterizable <em>output</em> filter for low complexity repeats</li>
<li>reporting of various alignment statistical parameters (mutation bias along triplets, transition/transversion)</li>
<li>post-processing step to group gapped alignments</li>
</ul><p>Address of the bookmark: <a href="http://bioinfo.lifl.fr/yass/" rel="nofollow">http://bioinfo.lifl.fr/yass/</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/28269/4dgenome</guid>
	<pubDate>Mon, 04 Jul 2016 00:44:55 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/28269/4dgenome</link>
	<title><![CDATA[4DGenome]]></title>
	<description><![CDATA[<p><span>Records in 4DGenome are compiled through comprehensive literature curation of experimentally-derived and computationally-predicted interactions. The current release contains 4,433,071 experimentally-derived and 3,605,176 computationally-predicted interactions in 5 organisms. Experimental data cover both high throughput datasets and individiual focused studies.&nbsp;</span><br><br><span>All interaction data are freely available in a standardized file format. Records can be queried by genomic regions, gene names, organism, and detection technology.&nbsp;</span></p><p>Address of the bookmark: <a href="http://4dgenome.research.chop.edu/" rel="nofollow">http://4dgenome.research.chop.edu/</a></p>]]></description>
	<dc:creator>Jitendra Narayan</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>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/29208/srf-bioinformatics-job-position-in-national-institute-of-plant-genome-research-nipgr</guid>
  <pubDate>Mon, 19 Sep 2016 05:43:38 -0500</pubDate>
  <link></link>
  <title><![CDATA[SRF Bioinformatics job position in National Institute of Plant Genome Research (NIPGR)]]></title>
  <description><![CDATA[
<p>SRF Bioinformatics job position in National Institute of Plant Genome Research (NIPGR)<br />Title : “Transcriptome and small RNA diversity analysis of developing seed contrasting rice varieties” <br />Qualification : Candidates having M.Sc./M.Tech. degree or equivalent (with minimum 60% marks) in Bioinformatics with a minimum of two years of post M.Sc./M.Tech research experience are eligible to apply.<br />No. of Post : 01<br />How to apply<br />Application should reach to Dr. Pinky Agarwal, Staff Scientist, National Institute of Plant Genome Research (NIPGR) Aruna Asaf Ali Marg, P.O. Box NO. 10531, New Delhi - 110067 on or before 30/09/2016</p>

<p>More at http://www.nipgr.res.in/careers/vacancies_latest.php#</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/28906/gene-finding-and-predictions</guid>
	<pubDate>Fri, 26 Aug 2016 07:26:27 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/28906/gene-finding-and-predictions</link>
	<title><![CDATA[Gene Finding and Predictions]]></title>
	<description><![CDATA[<p><span>In this exercise, a previously annotated gene will be used to measure the accuracy of different gene finding approaches. GRAIL, GENSCAN,&nbsp;</span><tt>geneid</tt><span>, FGENESH, GenomeScan, GrailEXP and GENEWISE will be used to annotate the sequence. Both search by signal, content and homology (protein and cDNA sequences) methods will be employed in order to improve the ab initio results. Weak conservation of Start codons will lead to wrong prediction of initial exons in most cases.</span></p>
<p>http://genome.crg.es/courses/Bioinformatics2003_genefinding/</p><p>Address of the bookmark: <a href="http://genome.crg.es/courses/Bioinformatics2003_genefinding/" rel="nofollow">http://genome.crg.es/courses/Bioinformatics2003_genefinding/</a></p>]]></description>
	<dc:creator>Poonam Mahapatra</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/29123/artemis-comparison-tool-act</guid>
	<pubDate>Wed, 07 Sep 2016 03:54:41 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/29123/artemis-comparison-tool-act</link>
	<title><![CDATA[Artemis Comparison Tool (ACT)]]></title>
	<description><![CDATA[<p><span>ACT is a Java application for displaying pairwise comparisons between two or more DNA sequences. It can be used to identify and analyse regions of similarity and difference between genomes and to explore conservation of synteny, in the context of the entire sequences and their annotation.&nbsp;It can read complete EMBL,&nbsp;GENBANK and GFF entries or sequences in FASTA or raw format.&nbsp;</span></p><p>Address of the bookmark: <a href="http://www.sanger.ac.uk/science/tools/artemis-comparison-tool-act" rel="nofollow">http://www.sanger.ac.uk/science/tools/artemis-comparison-tool-act</a></p>]]></description>
	<dc:creator>Shruti Paniwala</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/file/view/29108/assembly-tutorial-ppt</guid>
	<pubDate>Wed, 07 Sep 2016 03:12:53 -0500</pubDate>
	<link>https://bioinformaticsonline.com/file/view/29108/assembly-tutorial-ppt</link>
	<title><![CDATA[Assembly tutorial PPT]]></title>
	<description><![CDATA[<p>Saved Cornell University assembly workshop PPT.</p><p>Reference:&nbsp;</p><p>http://cbsu.tc.cornell.edu/lab/doc/assembly_workshop_20150420_lecture1.pdf</p>]]></description>
	<dc:creator>Jit</dc:creator>
	<enclosure url="https://bioinformaticsonline.com/file/download/29108" length="1617402" type="application/pdf" />
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/29144/fermi</guid>
	<pubDate>Fri, 09 Sep 2016 05:37:13 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/29144/fermi</link>
	<title><![CDATA[FERMI]]></title>
	<description><![CDATA[<p><span>Fermi is a de novo assembler with a particular focus on assembling Illumina&nbsp;</span><span>short sequence reads from a mammal-sized genome. In addition to the role of a&nbsp;</span><span>typical assembler, fermi also aims to preserve heterozygotes which are often&nbsp;</span><span>collapsed by other assemblers. Its ultimate goal is to find a minimal set of</span><br><span>unitigs to represent all the information in raw reads.</span><br><br><span>Fermi follows the overlap-layout-consensus paradigm and uses the FM-DNA-index&nbsp;</span><span>(FMD-index) as the key data structure. It is inspired by the string graph&nbsp;</span><span>assembler (Simpson and Durbin, 2010 and 2012) and has a similar workflow.</span><br><br><span>As a typical de novo assembler, fermi tends to produce contigs with slightly&nbsp;</span><span>longer N50. However, the major weakness of fermi is the high misassembly rate.&nbsp;</span><span>Although fermi provides a tool to fix misassemblies by using paired-end reads&nbsp;</span><span>to achieve an accuracy comparable to other assemblers, this is not a favorable&nbsp;</span><span>solution.</span><br><br><span>Fermi is designed to be used on a multi-core Linux machine with large shared&nbsp;</span><span>memory. The easiest way to run fermi is to use the run-fermi.pl script. It&nbsp;</span><span>generates a Makefile. The actual assembly is done by invoking make. Premature&nbsp;</span><span>assembly processes can be resumed. Here is an example:</span><br><br><span>run-fermi.pl -dAPe ./fermi -p NA12878 -t16 -f18 reads*.fq.gz &gt; NA12878.mak</span><br><span>make -f NA12878.mak -j16</span></p><p>Address of the bookmark: <a href="https://github.com/lh3/fermi" rel="nofollow">https://github.com/lh3/fermi</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/29274/strudel</guid>
	<pubDate>Fri, 30 Sep 2016 09:47:02 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/29274/strudel</link>
	<title><![CDATA[Strudel]]></title>
	<description><![CDATA[<p>Strudel is our graphical tool for visualizing genetic and physical maps of genomes for comparative purposes. The application aims to let the user examine their data at a variety of different levels of resolution, from entire maps to individual markers, and explore syntenic relationships between genomes. All browsing and interaction with Strudel happens in real-time &ndash; there is no need to wait while the maps are generated. It is built using Java 1.6 and ships with its own JRE, so there is no need for users to install or update Java.</p><p>Address of the bookmark: <a href="https://ics.hutton.ac.uk/strudel/" rel="nofollow">https://ics.hutton.ac.uk/strudel/</a></p>]]></description>
	<dc:creator>Anjana</dc:creator>
</item>

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