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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/27090?offset=310</link>
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	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36812/porechop-tool-for-finding-and-removing-adapters-from-oxford-nanopore-reads</guid>
	<pubDate>Tue, 29 May 2018 07:33:44 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36812/porechop-tool-for-finding-and-removing-adapters-from-oxford-nanopore-reads</link>
	<title><![CDATA[Porechop:  tool for finding and removing adapters from Oxford Nanopore reads]]></title>
	<description><![CDATA[<p>Porechop is a tool for finding and removing adapters from <a href="https://nanoporetech.com/">Oxford Nanopore</a> reads. Adapters on the ends of reads are trimmed off, and when a read has an adapter in its middle, it is treated as chimeric and chopped into separate reads. Porechop performs thorough alignments to effectively find adapters, even at low sequence identity.</p>
<p>Porechop also supports demultiplexing of Nanopore reads that were barcoded with the <a href="https://store.nanoporetech.com/native-barcoding-kit-1d.html">Native Barcoding Kit</a>, <a href="https://store.nanoporetech.com/pcr-barcoding-kit-96.html">PCR Barcoding Kit</a> or <a href="https://store.nanoporetech.com/rapid-barcoding-sequencing-kit.html">Rapid Barcoding Kit</a>.</p><p>Address of the bookmark: <a href="https://github.com/rrwick/Porechop" rel="nofollow">https://github.com/rrwick/Porechop</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/19636/google-genomics</guid>
	<pubDate>Thu, 18 Dec 2014 11:05:42 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/19636/google-genomics</link>
	<title><![CDATA[Google Genomics]]></title>
	<description><![CDATA[<ul>
<li>
<p><strong>Explore genetic variation interactively.</strong> Compare entire cohorts in seconds with SQL-like queries. Compute transition/transversion ratios, genome-wide association, allelic frequency and more.</p>
</li>
<li>
<p><strong>Process big genomic data easily.</strong> Run batch analyses like principal component analysis and Hardy-Weinberg equilibrium on as many samples as you like, in minutes or hours, with just a little code.</p>
</li>
<li>
<p><strong>Use Google's infrastructure and big data expertise.</strong> Store one genome or a million using Google Genomics and take advantage of the same infrastructure that powers Search, Maps, YouTube, Gmail and Drive.</p>
</li>
<li>
<p><strong>Support emerging global standards.</strong> Google Genomics is implementing the API defined by the Global Alliance for Genomics and Health for visualization, analysis and more. Compliant software can access Google Genomics, local servers, or any other implementation.</p>
</li>
</ul><p>Address of the bookmark: <a href="https://cloud.google.com/genomics/" rel="nofollow">https://cloud.google.com/genomics/</a></p>]]></description>
	<dc:creator>Tenzin Paul</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/19980/seqloc-06</guid>
	<pubDate>Sun, 28 Dec 2014 12:51:29 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/19980/seqloc-06</link>
	<title><![CDATA[seqloc 0.6]]></title>
	<description><![CDATA[<p>The <code>Bio.SeqLoc</code> modules in <code>seqloc</code> are designed to represent positions and locations (ranges of positions) on sequences, particularly nucleotide sequences. My original motivation for writing these packages was handing the locations of genes in eukaryotic genomes.</p>
<p>Handle sequence locations for bioinformatics http://www.ingolia-lab.org/seqloc-tutorial.html</p><p>Address of the bookmark: <a href="http://www.stackage.org/snapshot/nightly-2014-12-28/package/seqloc-0.6" rel="nofollow">http://www.stackage.org/snapshot/nightly-2014-12-28/package/seqloc-0.6</a></p>]]></description>
	<dc:creator>Gudiya Pal</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/22403/ryan-e-mills-lab</guid>
  <pubDate>Tue, 26 May 2015 09:29:24 -0500</pubDate>
  <link></link>
  <title><![CDATA[Ryan E. Mills Lab]]></title>
  <description><![CDATA[
<p>Our research group is primarily focused on the analysis of whole genome sequence data to identify genetic variation (primarily structural variation) and examine their potential functional impact in disease phenotypes. We are particularly interested in analyzing complex regions of the genome that are not easily resolved through modern sequencing approaches and which may exhibit interesting mechanistic origins.</p>

<p>We are also interested in the large-scale integration of genomic, expression, methylation and proteomic data sets, as well as the application of whole genome sequence analysis in clinical diagnostics. </p>

<p>More at http://millslab.ccmb.med.umich.edu/index.html</p>
]]></description>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/23149/raphael-lab</guid>
  <pubDate>Sat, 04 Jul 2015 19:05:29 -0500</pubDate>
  <link></link>
  <title><![CDATA[Raphael Lab]]></title>
  <description><![CDATA[
<p>Raphael Lab research is focused on Bioinformatics and Computational Biology.</p>

<p>Current research interests include next-generation DNA sequencing, structural variation, genome rearrangements in cancer and evolution, and network analysis of somatic mutations in cancer. Earlier research included topics in comparative genomics, multiple sequence alignment, and motif finding.</p>

<p>More athttp://compbio.cs.brown.edu/</p>
]]></description>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/23633/biorg</guid>
  <pubDate>Tue, 04 Aug 2015 20:52:52 -0500</pubDate>
  <link></link>
  <title><![CDATA[BioRG]]></title>
  <description><![CDATA[
<p>This research group works on problems from the fields of Bioinformatics, Biotechnology, Data Mining, and Information Retrieval. The group's research projects includes Comparative Genomics of Bacterial genomes, Metagenomics, Genomic databases, Pattern Discovery in sequences and structures, micro-array data analysis, prediction of regulatory elements, primer design, probe design, phylogenetic analysis, medical image processing, image analysis, data integration, data mining, information retrieval, knowledge discovery in electronic medical records, and more. </p>

<p>More at http://biorg.cis.fiu.edu/</p>
]]></description>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/25284/rajiv-gandhi-centre-for-biotechnology-rgcb-invites-applications-for-the-following-three-faculty-scientist</guid>
  <pubDate>Tue, 24 Nov 2015 22:13:16 -0600</pubDate>
  <link></link>
  <title><![CDATA[Rajiv Gandhi Centre for Biotechnology (RGCB) invites applications for the following three faculty scientist]]></title>
  <description><![CDATA[
<p>Scientist Positions<br />Advt. No.RGCB Advt./SCI 2015/1<br /> <br />November 11, 2015</p>

<p>Rajiv Gandhi Centre for Biotechnology (RGCB) invites applications for the following three faculty scientist positions:</p>

<p>Scientist E-II or F in Bioinformatics &amp; Computational Biology</p>

<p>SCIENTIST E-II OR F IN COMPUTATIONAL BIOLOGY &amp; BIOINFORMATICS</p>

<p>Highly motivated and innovative individual who will pursue basic research, solve biological problems with emphasis on computational and quantitative experimental methods and build active bridges to translational research. The scientist will also provide computational biology support to ongoing research programs in disease biology, provide assistance to analyze complex data sets generated by RGCB scientists and collaborators inclusive of including high dimensional “omics” data and next generation sequencing data, such as whole genome, exome, RNA-seq and ChIP-seq as well as provide leadership for high quality training for junior scientists and regular teaching programs of the institute. Areas of research of interest to RGCB include but are not limited to computational, systems, or quantitative biology with applications to cell biology, developmental biology, metabolism, genomics, proteomics, biophysics, biological information systems, network pharmacology, drug design and cancer research. The scientist’s responsibilities include efforts for the integration of DNA variant annotation with statistical genetic analysis methods including linkage, imputation and association methods, adopting novel and innovative methodologies to analyze, integrate and interpret high dimensional data sets, provision of annotation to robust genetics and genomics findings using several data sources and methods, data management of exploratory clinical and R&amp;D studies in partnership with other lines of genetic data generated from internal and external studies, delivery and documentation of genomic information to support genetic studies, ensuring high-quality genetic and genomic data is incorporated into exploratory- clinical research programs, developing tools that make maximum use of multiple data sources to support annotation of DNA variation and contributes to systems biology initiatives within RGCB </p>

<p>More at http://rgcb.res.in/scientist-positions/</p>

<p>Application Form http://rgcb.res.in/wp-content/uploads/2015/11/APPLICATION-FORMAT-FOR-SCIENTISTS.docx</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/26319/n50plottingtools</guid>
	<pubDate>Mon, 08 Feb 2016 15:39:04 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/26319/n50plottingtools</link>
	<title><![CDATA[n50PlottingTools]]></title>
	<description><![CDATA[<p><span>Tools to create plots showing N-statistics for genome assemblies </span></p>
<p><span>More at https://github.com/dentearl/n50PlottingTools</span></p><p>Address of the bookmark: <a href="https://github.com/dentearl/n50PlottingTools" rel="nofollow">https://github.com/dentearl/n50PlottingTools</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<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/26975/trimmomatic-a-flexible-read-trimming-tool-for-illumina-ngs-data</guid>
	<pubDate>Fri, 15 Apr 2016 05:58:53 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/26975/trimmomatic-a-flexible-read-trimming-tool-for-illumina-ngs-data</link>
	<title><![CDATA[Trimmomatic: A flexible read trimming tool for Illumina NGS data]]></title>
	<description><![CDATA[<h4>Paired End:</h4>
<p><code>java -jar trimmomatic-0.35.jar PE -phred33 input_forward.fq.gz input_reverse.fq.gz output_forward_paired.fq.gz output_forward_unpaired.fq.gz output_reverse_paired.fq.gz output_reverse_unpaired.fq.gz ILLUMINACLIP:TruSeq3-PE.fa:2:30:10 LEADING:3 TRAILING:3 SLIDINGWINDOW:4:15 MINLEN:36</code></p>
<p>This will perform the following:</p>
<ul>
<li>Remove adapters (ILLUMINACLIP:TruSeq3-PE.fa:2:30:10)</li>
<li>Remove leading low quality or N bases (below quality 3) (LEADING:3)</li>
<li>Remove trailing low quality or N bases (below quality 3) (TRAILING:3)</li>
<li>Scan the read with a 4-base wide sliding window, cutting when the average quality per base drops below 15 (SLIDINGWINDOW:4:15)</li>
<li>Drop reads below the 36 bases long (MINLEN:36)</li>
</ul>
<p>More at http://www.usadellab.org/cms/?page=trimmomatic</p><p>Address of the bookmark: <a href="http://www.usadellab.org/cms/?page=trimmomatic" rel="nofollow">http://www.usadellab.org/cms/?page=trimmomatic</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

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