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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/27238?offset=300</link>
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	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/26852/awesome-bioinformatics-pipelines</guid>
	<pubDate>Wed, 30 Mar 2016 21:50:41 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/26852/awesome-bioinformatics-pipelines</link>
	<title><![CDATA[Awesome bioinformatics pipelines !]]></title>
	<description><![CDATA[<p><span>A curated list of awesome pipeline toolkits ...</span></p>
<p><span>https://github.com/pditommaso/awesome-pipeline</span></p><p>Address of the bookmark: <a href="https://github.com/pditommaso/awesome-pipeline" rel="nofollow">https://github.com/pditommaso/awesome-pipeline</a></p>]]></description>
	<dc:creator>Jitendra Prajapati</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/26906/paired-end-assembler-for-dna-sequences</guid>
	<pubDate>Wed, 06 Apr 2016 05:25:34 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/26906/paired-end-assembler-for-dna-sequences</link>
	<title><![CDATA[PAired-eND Assembler for DNA sequences]]></title>
	<description><![CDATA[<p>PANDASEQ is a program to align Illumina reads, optionally with PCR primers embedded in the sequence, and reconstruct an overlapping sequence.</p>
<p>&nbsp;</p>
<p>More at https://github.com/neufeld/pandaseq</p><p>Address of the bookmark: <a href="https://github.com/neufeld/pandaseq" rel="nofollow">https://github.com/neufeld/pandaseq</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/26919/pear-a-fast-and-accurate-illumina-paired-end-read-merger</guid>
	<pubDate>Wed, 06 Apr 2016 13:27:23 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/26919/pear-a-fast-and-accurate-illumina-paired-end-read-merger</link>
	<title><![CDATA[PEAR: a fast and accurate Illumina Paired-End reAd mergeR]]></title>
	<description><![CDATA[<p><strong>PEAR</strong>&nbsp;is an ultrafast, memory-efficient and highly accurate pair-end read merger. It is fully parallelized and can run with as low as just a few kilobytes of memory.</p>
<p>PEAR evaluates all possible paired-end read overlaps and without requiring the target fragment size as input. In addition, it implements a statistical test for minimizing false-positive results. Together with a highly optimized implementation, it can merge millions of paired end reads within a couple of minutes on a standard desktop computer.</p>
<p>More at&nbsp;http://www.exelixis-lab.org/web/software/pear</p>
<p>Paper:&nbsp;http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3933873/</p><p>Address of the bookmark: <a href="http://www.exelixis-lab.org/web/software/pear" rel="nofollow">http://www.exelixis-lab.org/web/software/pear</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/26968/scalce</guid>
	<pubDate>Fri, 15 Apr 2016 05:09:51 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/26968/scalce</link>
	<title><![CDATA[SCALCE]]></title>
	<description><![CDATA[<p><span>SCALCE (</span><code>/skeɪlz/</code><span>, a.k.a. boosting&nbsp;</span><span style="text-decoration: underline;">S</span><span>equence&nbsp;</span><span style="text-decoration: underline;">C</span><span>ompression&nbsp;</span><span style="text-decoration: underline;">A</span><span>lgorithms using&nbsp;</span><span style="text-decoration: underline;">L</span><span>ocally&nbsp;</span><span style="text-decoration: underline;">C</span><span>onsistent</span><span style="text-decoration: underline;">E</span><span>ncoding) is a tool for compressing FASTQ files. It is designed specifically for the Illumina-generated FASTQ files, but supports any valid FASTQ with consistent read lengths.&nbsp;</span></p>
<p><span>More at&nbsp;http://sfu-compbio.github.io/scalce/</span></p><p>Address of the bookmark: <a href="http://sfu-compbio.github.io/scalce/" rel="nofollow">http://sfu-compbio.github.io/scalce/</a></p>]]></description>
	<dc:creator>Surabhi Chaudhary</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27035/spades</guid>
	<pubDate>Tue, 19 Apr 2016 08:37:08 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27035/spades</link>
	<title><![CDATA[SPAdes]]></title>
	<description><![CDATA[<p>SPAdes &ndash; St. Petersburg genome assembler &ndash; is intended for both standard isolates and single-cell MDA bacteria assemblies. This manual will help you to install and run SPAdes. SPAdes version 3.7.1 was released under GPLv2 on March 8, 2016 and can be downloaded from <a href="http://bioinf.spbau.ru/en/spades" target="_blank">http://bioinf.spbau.ru/en/spades</a>.</p>
<p>Manual at http://spades.bioinf.spbau.ru/release3.7.1/manual.html</p><p>Address of the bookmark: <a href="http://bioinf.spbau.ru/spades" rel="nofollow">http://bioinf.spbau.ru/spades</a></p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27257/busco-assessing-genome-assembly-and-annotation-completeness-with-benchmarking-universal-single-copy-orthologs</guid>
	<pubDate>Tue, 10 May 2016 07:46:24 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27257/busco-assessing-genome-assembly-and-annotation-completeness-with-benchmarking-universal-single-copy-orthologs</link>
	<title><![CDATA[BUSCO: Assessing genome assembly and annotation completeness with Benchmarking Universal Single-Copy Orthologs]]></title>
	<description><![CDATA[<ul>
<li><span>High-throughput genomics has revolutionized biological research, however, while the number of sequenced genomes grows by the day, quality assessment of the resulting assembled sequences remains complicated and mostly limited to technical measures like N50.&nbsp;</span></li>
<li></li>
<li><span>BUSCO provides measures for quantitative assessment of genome assembly, gene set, and transcriptome completeness based on evolutionarily informed expectations of gene content from near-universal single-copy orthologs selected from&nbsp;</span><a href="http://orthodb.org/">OrthoDB</a><span>.&nbsp;</span></li>
<li></li>
<li><span>BUSCO assessments are implemented in open-source software, with comprehensive lineage-specific sets of Benchmarking Universal Single-Copy Orthologs for arthropods, vertebrates, metazoans, fungi, eukaryotes, and bacteria.&nbsp;</span></li>
<li></li>
<li><span>These conserved orthologs are ideal candidates for large-scale phylogenomics studies, and the annotated BUSCO gene models built during genome assessments provide a comprehensive gene predictor training set for use as part of genome annotation pipelines.&nbsp;</span></li>
<li></li>
<li><span>BUSCO assessments offer intuitive metrics, based on evolutionarily informed expectations of gene content from hundreds of species, to gauge completeness of rapidly accumulating genomic data and satisfy an Iberian's quest for quality - "Busco calidad/qualidade".</span></li>
</ul><p>Address of the bookmark: <a href="http://busco.ezlab.org/" rel="nofollow">http://busco.ezlab.org/</a></p>]]></description>
	<dc:creator>Anjana</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27080/mrfast-micro-read-fast-alignment-search-tool</guid>
	<pubDate>Tue, 26 Apr 2016 03:50:06 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27080/mrfast-micro-read-fast-alignment-search-tool</link>
	<title><![CDATA[mrFAST:  Micro Read Fast Alignment Search Tool]]></title>
	<description><![CDATA[<p><span>mrFAST is a read mapper that is designed to map short reads to reference genome with a special emphasis on the discovery of structural variation and segmental duplications. mrFAST maps short reads with respect to user defined error threshold, including indels up to 4+4 bp. This manual, describes how to choose the parameters and tune mrFAST with respect to the library settings. mrFAST is designed to find&nbsp;</span><strong><span style="text-decoration: underline;">'all'</span></strong><span>&nbsp; mappings for a given set of reads, however it can return one "best" map location if the relevant parameter is invoked.</span></p>
<p><span>More at&nbsp;http://mrfast.sourceforge.net/manual.html</span></p><p>Address of the bookmark: <a href="http://mrfast.sourceforge.net/manual.html" rel="nofollow">http://mrfast.sourceforge.net/manual.html</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/27211/srbioinformatics-analyst-ngs-ocimumbio</guid>
  <pubDate>Mon, 02 May 2016 04:41:22 -0500</pubDate>
  <link></link>
  <title><![CDATA[Sr.Bioinformatics Analyst (NGS) @ OcimumBio]]></title>
  <description><![CDATA[
<p>Sr.Bioinformatics Analyst (NGS)</p>

<p>Experience Required: 3-5 years of experience<br />No of Positions : Multiple<br />Qualifications: Candidates with minimum qualification as M.Sc Bioinformatics with 3-5  years of experience in Life sciences R&amp;D or Pharma Industry.<br />Ph.D candidates with research experience in Bioinformatics with publications in International journal and minimum 2 years of  industry experience in clinical genomics will be preferred for this position.</p>

<p>Requirement:</p>

<p>1.  Must have basic understanding of molecular biology and Genomics.<br />2. Experience in application development or must have expertise in programming using either of Perl/Python.<br />3.  Experience in statistical programming using R/Bioconductor/Matlab.<br />4. Strong concept in statistical and mathematical modelling.<br />5.  Experience in designing and developing the bioinformatics pipeline.<br />6.  Must have minimum 2+ years of hands on experience in NSG data analysis such as RNA-Seq,Exome-Seq ,Chip-Seq and downstream analysis.<br />7. Knowledge in WGS ,WES, Targeted re-sequencing,GWAS and population genomics will be preferred.<br />8. Must have experience working on opensource software/Framework and commercial software for NGS data analysis and reporting.<br />9. Should be aware of handling big data and guiding team members on multiple projects simultaneously.<br />More at http://www.ocimumbio.com/careers1/<br />10. Should have experience coordinating with different groups of clinical research scientist for various project requirements.<br />11. Ability to work as team as well as independently with minimal support.</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27261/segemehl</guid>
	<pubDate>Tue, 10 May 2016 08:10:15 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27261/segemehl</link>
	<title><![CDATA[segemehl]]></title>
	<description><![CDATA[<p><span>segemehl is a software to map short sequencer reads to reference genomes. Unlike other methods, segemehl is able to detect not only mismatches but also insertions and deletions. Furthermore, segemehl is not limited to a specific read length and is able to map&nbsp;primer- or polyadenylation contaminated reads correctly.&nbsp; segemehl implements a matching strategy based on enhanced suffix arrays (ESA).&nbsp;</span></p>
<p><span>More at&nbsp;http://www.bioinf.uni-leipzig.de/Software/segemehl/</span></p>
<p><span>Manual&nbsp;http://www.bioinf.uni-leipzig.de/Software/segemehl/segemehl_manual_0_1_7.pdf</span></p><p>Address of the bookmark: <a href="http://hoffmann.bioinf.uni-leipzig.de/LIFE/segemehl.html" rel="nofollow">http://hoffmann.bioinf.uni-leipzig.de/LIFE/segemehl.html</a></p>]]></description>
	<dc:creator>Anjana</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/29343/accnet</guid>
	<pubDate>Fri, 07 Oct 2016 05:22:11 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/29343/accnet</link>
	<title><![CDATA[AccNET]]></title>
	<description><![CDATA[<p><span>AccNET is a Perl application that presents a new way to study the accessory genome of a given set of organisms. Using the proteomes of these organisms, AccNET create a bipartite network compatible with common network analysis platforms. AccNET collects phylogenetic and functional information in a network improving the analysis capability. Networks offer a new perspective of organism organization through elements acquired by horizontal gene transfers and not constricted by hierarchical structures.</span></p>
<p><span>More at&nbsp;https://www.youtube.com/watch?v=vdGuy1GAJrQ</span></p><p>Address of the bookmark: <a href="https://sourceforge.net/projects/accnet/" rel="nofollow">https://sourceforge.net/projects/accnet/</a></p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
</item>

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