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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/41009?offset=430</link>
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	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/42329/10-ngs-services-companies-around-the-globe</guid>
	<pubDate>Sun, 22 Nov 2020 23:56:17 -0600</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/42329/10-ngs-services-companies-around-the-globe</link>
	<title><![CDATA[10 NGS services companies around the globe !]]></title>
	<description><![CDATA[<p><strong>The global&nbsp;NGS services market&nbsp;is expected to reach USD 13.1 billion by 2025.&nbsp;</strong>Here are the&nbsp;<strong style="font-size: 12.8px;">top 10 NGS services companies to look for &ndash;</strong></p><p><strong>1.&nbsp;<a href="https://www.illumina.com/">Illumina, Inc. (U.S.)</a></strong></p><p>Illumina, Inc. was founded in 1998 and is headquartered at San Diego, U.S. Illumina, Inc. is one of the leading players in DNA sequencing and array-based technologies, serving customers in the research, clinical, and applied markets. The company offers products for applications in the life sciences, oncology, reproductive health, agriculture, and other emerging segments. The company serves government laboratories, genomic research centers, academics institutions as well as pharmaceutical, biotechnology, agrigenomics, commercial molecular diagnostics laboratories and consumer genomics companies. Illumina, Inc. has its geographic presence in North America, Europe, Latin America, Asia-pacific, and others.</p><p><strong>2.&nbsp;<a href="https://www.qiagen.com/us/">QIAGEN N.V. (Netherlands)</a></strong></p><p>QIAGEN N.V. was incorporated in 1986 and is headquartered at Venlo, The Netherlands. The Company is engaged in providing Sample to Insight solutions that transform biological samples into molecular insights. QIAGEN provides its workflow to customers in molecular diagnostics, assay technologies, bioservices and automation systems.&nbsp; The company&rsquo;s genome services are suitable for custom/tailored projects that allow access to genomic sequence information.&nbsp; The Company market its products in more than 100 countries across the Americas, Europe, Asia, Australia, and the Middle-East &amp;Africa through its subsidiaries and channel partners.</p><p><strong>3.&nbsp;<a href="https://www.perkinelmer.com/">PerkinElmer, Inc. (U.S.)</a></strong></p><p>PerkinElmer, Inc. was founded in 1947 and is headquartered in Waltham, Massachusetts, the U.S. PerkinElmer, Inc. offers its products &amp; services and solutions for the diagnostics, food, environmental, industrial, life sciences research and laboratory services markets. The company offer comprehensive genetic testing solutions that help to provide insight into the complex nature of rare and inherited diseases. Some of the subsidiaries of the company are Caliper Life Sciences, Improvision, Viacell Inc., ViaCord LLC, among many others. The company has its facilities located in Europe (France, Germany, and Belgium), U.S. and Asia (China, India, and Japan).</p><p><strong>4.&nbsp;<a href="https://www.eurofins.com/">Eurofins Scientific SE (Luxembourg)</a></strong></p><p>Eurofins Scientific SE was founded in 1987 and is headquartered in Luxembourg, Europe. The company offers a portfolio of over 130,000 analytical methods and more than 150 million assays performed each year to establish the safety, identity, composition, authenticity, origin, traceability, and purity of biological substances and products, as well as carry out human diagnostic services. The company has its geographic presence across 39 countries in Europe, North and South America, and Asia-Pacific.</p><p><strong>5.&nbsp;<a href="https://www.gatc-biotech.com/en/index.html">GATC Biotech AG (Germany)</a></strong></p><p>GATC Biotech AG was founded in 1990 and is headquartered in Constance, Germany. The company provides DNA and RNA sequencing and bioservices solutions to academics and industrial areas. It also provides next generation sequencing services including genomes, targeted (re)-sequencing, human sample sequencing, transcriptomes, metagenomes, regulomes, pre-sequencing, NGS barcode labels, and next generation sequencing technologies; and bioservices services, including bioservices tools, pipelines and workflows, compute resources, data analysis reports, and case studies. GATC Biotech AG operates as a subsidiary of Eurofins Scientific SE. It offers its products through distributors in Italy, Japan, Portugal, Spain, and the Czech Republic.</p><p><strong>6.<a href="https://www.macrogen.com/">&nbsp;Macrogen, Inc. (South Korea)</a></strong></p><p>Macrogen, Inc. was founded in 1997 and is headquartered in Seoul, South Korea. Macrogen, Inc. provides next generation sequencing services such as whole genome, de novo, exome, targeted, transcriptomics, metagenome, and epigenome sequencing.&nbsp; The company also provides a variety of services such as oligo synthesis, database construction, genome research, and bioservices analysis system consulting services. Macrogen, Inc. provides genome research services in Korea and internationally.</p><p><strong>7.&nbsp;<a href="https://www.genotypic.co.in/">Genotypic Technology Pvt. Ltd. (India)</a></strong></p><p>Genotypic Technology Pvt. Ltd. was incorporated in 1998 and is headquartered in Bangalore, India. Genotypic Technology is the first Genomics service provider in India providing Microarray, Next Generation Sequencing (NGS), Bioservices and solutions to domestic/ international pharma, biotech companies and academia. The company provides its services for protocol optimization, probe designing, array layouts, project designing, and nucleic acid analysis to in-depth analysis. Genotypic Technology has its geographic presence in North America, Europe, Asia Pacific, Middle East &amp; Africa, and Latin America.</p><p><strong>8.&nbsp;<a href="https://www.genewiz.com/">GENEWIZ, Inc. (U.S.)</a></strong></p><p>GENEWIZ, Inc. was founded in 1999 and is headquartered in South Plainfield, New Jersey, the U.S.; The company is a leading provider of research service in the field of Next Generation Sequencing, Sanger DNA sequencing, sequencing of bacteria and phage, gene synthesis, DNA cloning, genomics including mutation analysis, single nucleotide polymorphism, and bioservices. GENEWIZ, Inc. has its geographic presence in U.S., China, Germany, France, Japan, and the U.K.</p><p><strong>9.&nbsp;<a href="https://www.genomics.cn/">Beijing Genomics Institute (China)</a></strong></p><p>Beijing Genomics Institute (BGI) is the world&rsquo;s largest genomics organization and non-profit research institution that was founded in 1999 and is headquartered in Shenzhen, China. The Company provides a wide range of commercial next generation sequencing services and genetic tests for medical institutions, agricultural and environmental applications. The Company operates all across the globe through its subsidiaries, namely, BGI China (Mainland), BGI Asia Pacific, BGI Americas (North and South America) and BGI Europe (Europe and Africa).</p><p><strong>10.&nbsp;<a href="https://www.scigenom.com/">SciGenom Labs Pvt. Ltd (India)</a></strong></p><p>SciGenom Labs Pvt. Ltd was founded in 2010 and is headquartered in Cochin, India with offices in Chennai &amp; Hyderabad in India, and San Francisco in the U.S. It is a Genomics R&amp;D services company that provides genomic sequencing and NGS services to life sciences and healthcare businesses globally as well as academic and government institutions in India.</p><p>Popular mentions &ndash; MedGenome (India), DNA Link, Inc. (South Korea), Otogenetics Corporation (U.S.), Novogene Corporation (China), LGC Limited (U.K.), CD Genomics (U.S.), SeqLL, LLC (U.S.)</p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/44229/common-steps-for-reads-mapping</guid>
	<pubDate>Thu, 09 Mar 2023 02:48:02 -0600</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/44229/common-steps-for-reads-mapping</link>
	<title><![CDATA[Common steps for reads mapping !]]></title>
	<description><![CDATA[<div><div><div><div><div><div><div><div><div><div><p>Mapping reads to a reference genome is an essential step in many types of genomic analysis, such as variant calling and gene expression analysis. Here are some general steps to follow for mapping reads to a genome:</p><ol>
<li>
<p>Choose a read mapper: There are many read mappers available, such as BWA, Bowtie, and HISAT2. Choose a mapper that is appropriate for your type of data and research question.</p>
</li>
<li>
<p>Index the reference genome: Before mapping reads, the reference genome needs to be indexed. This involves creating an index of the genome sequence that allows the mapper to quickly find matches to the reads. Most mappers have their own indexing tools.</p>
</li>
<li>
<p>Prepare the read data: The reads should be in a format that is compatible with the mapper. Most mappers accept FASTQ or BAM files. Depending on the quality of the data, it may need to be filtered or trimmed before mapping.</p>
</li>
<li>
<p>Run the mapper: The mapper is run with the command-line interface or using a graphical user interface. The specific command depends on the mapper being used, but typically involves specifying the input data, reference genome, and output file format.</p>
</li>
<li>
<p>Evaluate the mapping results: After the mapping is complete, the results should be evaluated. This includes assessing the quality of the mapping, such as the mapping rate, the number of mapped reads, and the mapping quality score.</p>
</li>
<li>
<p>Post-processing: Depending on the analysis being performed, post-processing of the mapped reads may be necessary. This can include filtering reads based on quality, removing duplicate reads, and calling variants.</p>
</li>
</ol><p>Overall, mapping reads to a reference genome is a complex process that requires careful consideration of the type of data, the research question, and the specific mapper being used.</p></div></div></div></div></div></div></div></div></div></div>]]></description>
	<dc:creator>BioStar</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/42972/list-of-bioinformatics-workflow-management-tools</guid>
	<pubDate>Sat, 20 Mar 2021 00:15:25 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/42972/list-of-bioinformatics-workflow-management-tools</link>
	<title><![CDATA[List of bioinformatics workflow management tools !]]></title>
	<description><![CDATA[<h3>Here are list of&nbsp;Workflow Managers</h3><ul>
<li><span><a href="https://github.com/pcingola/BigDataScript">BigDataScript</a></span>&nbsp;&ndash; A cross-system scripting language for working with big data pipelines in computer systems of different sizes and capabilities. [&nbsp;<a href="https://pubmed.ncbi.nlm.nih.gov/25189778">paper-2014</a>&nbsp;|&nbsp;<a href="https://pcingola.github.io/BigDataScript">web</a>&nbsp;]</li>
<li><span><a href="https://github.com/ssadedin/bpipe">Bpipe</a></span>&nbsp;&ndash; A small language for defining pipeline stages and linking them together to make pipelines. [&nbsp;<a href="http://docs.bpipe.org/">web</a>&nbsp;]</li>
<li><span><a href="https://github.com/common-workflow-language/common-workflow-language">Common Workflow Language</a></span>&nbsp;&ndash; a specification for describing analysis workflows and tools that are portable and scalable across a variety of software and hardware environments, from workstations to cluster, cloud, and high performance computing (HPC) environments. [&nbsp;<a href="http://www.commonwl.org/">web</a>&nbsp;]</li>
<li><span><a href="https://github.com/broadinstitute/cromwell">Cromwell</a></span>&nbsp;&ndash; A Workflow Management System geared towards scientific workflows. [&nbsp;<a href="https://cromwell.readthedocs.io/">web</a>&nbsp;]</li>
<li><span><a href="https://github.com/galaxyproject">Galaxy</a></span>&nbsp;&ndash; a popular open-source, web-based platform for data intensive biomedical research. Has several features, from data analysis to workflow management to visualization tools. [&nbsp;<a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6030816">paper-2018</a>&nbsp;|&nbsp;<a href="https://galaxyproject.org/">web</a>&nbsp;]</li>
<li><span><a href="https://github.com/nextflow-io/nextflow">Nextflow</a>&nbsp;(recommended)</span>&nbsp;&ndash; A fluent DSL modelled around the UNIX pipe concept, that simplifies writing parallel and scalable pipelines in a portable manner. [&nbsp;<a href="https://pubmed.ncbi.nlm.nih.gov/29412134">paper-2018</a>&nbsp;|&nbsp;<a href="http://nextflow.io/">web</a>&nbsp;]</li>
<li><span><a href="https://github.com/cgat-developers/ruffus">Ruffus</a></span>&nbsp;&ndash; Computation Pipeline library for python widely used in science and bioinformatics. [&nbsp;<a href="https://pubmed.ncbi.nlm.nih.gov/20847218">paper-2010</a>&nbsp;|&nbsp;<a href="http://www.ruffus.org.uk/">web</a>&nbsp;]</li>
<li><span><a href="https://github.com/SeqWare/seqware">SeqWare</a></span>&nbsp;&ndash; Hadoop Oozie-based workflow system focused on genomics data analysis in cloud environments. [&nbsp;<a href="https://pubmed.ncbi.nlm.nih.gov/21210981">paper-2010</a>&nbsp;|&nbsp;<a href="https://seqware.github.io/">web</a>&nbsp;]</li>
<li><span><a href="https://bitbucket.org/snakemake">Snakemake</a></span>&nbsp;&ndash; A workflow management system in Python that aims to reduce the complexity of creating workflows by providing a fast and comfortable execution environment. [&nbsp;<a href="https://pubmed.ncbi.nlm.nih.gov/29788404">paper-2018</a>&nbsp;|&nbsp;<a href="https://snakemake.readthedocs.io/">web</a>&nbsp;]</li>
<li><span><a href="https://github.com/broadinstitute/wdl">Workflow Descriptor Language</a></span>&nbsp;&ndash; Workflow standard developed by the Broad. [&nbsp;<a href="https://software.broadinstitute.org/wdl">web</a>&nbsp;]</li>
</ul>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37674/qualimap2-evaluating-next-generation-sequencing-alignment-data</guid>
	<pubDate>Tue, 11 Sep 2018 04:44:29 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37674/qualimap2-evaluating-next-generation-sequencing-alignment-data</link>
	<title><![CDATA[Qualimap2: Evaluating next generation sequencing alignment data]]></title>
	<description><![CDATA[<p><strong>Qualimap 2</strong><span>&nbsp;is a platform-independent application written in Java and R that provides both a Graphical User Inteface (GUI) and a command-line interface to facilitate the quality control of alignment sequencing data and its derivatives like feature counts.&nbsp;</span><br><br><span>Supported types of experiments include:</span></p>
<ul>
<li>Whole-genome sequencing</li>
<li>Whole-exome sequencing</li>
<li>RNA-seq (speical mode available)</li>
<li>ChIP-seq</li>
</ul><p>Address of the bookmark: <a href="http://qualimap.bioinfo.cipf.es/" rel="nofollow">http://qualimap.bioinfo.cipf.es/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38199/pacasus-correction-of-palindromes-in-long-reads-from-pacbio-and-nanopore</guid>
	<pubDate>Mon, 12 Nov 2018 05:26:48 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38199/pacasus-correction-of-palindromes-in-long-reads-from-pacbio-and-nanopore</link>
	<title><![CDATA[Pacasus: Correction of palindromes in long reads from PacBio and Nanopore]]></title>
	<description><![CDATA[<p><br>Tool for detecting and cleaning PacBio / Nanopore long reads after whole genome amplification. Check the poster from the Revolutionizing Next-Generation Sequencing (2nd edition) conference in the source folder:&nbsp;<a href="https://github.com/swarris/Pacasus/blob/master/vib2017.pdf">https://github.com/swarris/Pacasus/blob/master/vib2017.pdf</a>.</p>
<p>The prepint version is found on&nbsp;<a href="http://www.biorxiv.org/content/early/2017/08/09/173872">http://www.biorxiv.org/content/early/2017/08/09/173872</a></p>
<p>It uses the pyPaSWAS framework for sequence alignment (<a href="https://github.com/swarris/pyPaSWAS">https://github.com/swarris/pyPaSWAS</a>)</p><p>Address of the bookmark: <a href="https://github.com/swarris/Pacasus" rel="nofollow">https://github.com/swarris/Pacasus</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40531/shasta-long-read-assembler</guid>
	<pubDate>Tue, 14 Jan 2020 06:47:07 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40531/shasta-long-read-assembler</link>
	<title><![CDATA[Shasta long read assembler]]></title>
	<description><![CDATA[<p>The goal of the Shasta long read assembler is to rapidly produce accurate assembled sequence using as input DNA reads generated by&nbsp;<a href="https://nanoporetech.com/">Oxford Nanopore</a>&nbsp;flow cells.</p>
<p>Computational methods used by the Shasta assembler include:</p>
<ul>
<li>Using a&nbsp;<a href="https://en.wikipedia.org/wiki/Run-length_encoding">run-length</a>&nbsp;representation of the read sequence. This makes the assembly process more resilient to errors in homopolymer repeat counts, which are the most common type of errors in Oxford Nanopore reads.</li>
<li>Using in some phases of the computation a representation of the read sequence based on&nbsp;<em>markers</em>, a fixed subset of short k-mers (k &asymp; 10).</li>
</ul>
<p>More at&nbsp;<a href="https://chanzuckerberg.github.io/shasta/index.html">https://chanzuckerberg.github.io/shasta/index.html</a></p><p>Address of the bookmark: <a href="https://github.com/chanzuckerberg/shasta" rel="nofollow">https://github.com/chanzuckerberg/shasta</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40715/mutatrix-a-population-genome-simulator-which-generates-simulated-genomes</guid>
	<pubDate>Tue, 28 Jan 2020 04:06:58 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40715/mutatrix-a-population-genome-simulator-which-generates-simulated-genomes</link>
	<title><![CDATA[mutatrix: a population genome simulator which generates simulated genomes.]]></title>
	<description><![CDATA[<p><span>genome simulation across a population with zeta-distributed allele frequency, snps, insertions, deletions, and multi-nucleotide polymorphisms</span></p>
<p><span>More at&nbsp;<a href="https://github.com/ekg/mutatrix">https://github.com/ekg/mutatrix</a></span></p>
<pre>./mutatrix -S sample -P test/ -p 2 -n 10 reference.fasta</pre><p>Address of the bookmark: <a href="https://github.com/ekg/mutatrix" rel="nofollow">https://github.com/ekg/mutatrix</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/11611/ten-recommendations-for-creating-usable-bioinformatics-command-line-software</guid>
	<pubDate>Sun, 08 Jun 2014 10:06:26 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/11611/ten-recommendations-for-creating-usable-bioinformatics-command-line-software</link>
	<title><![CDATA[Ten recommendations for creating usable bioinformatics command line software]]></title>
	<description><![CDATA[<p><span>Bioinformatics software varies greatly in quality. In terms of usability, the command line interface is the first experience a user will have of a tool. Unfortunately, this is often also the last time a tool will be used. Here I present ten recommendations for command line software author&rsquo;s tools to follow, which I believe would greatly improve the uptake and usability of their products, waste less user&rsquo;s time, and improve the quality of scientific analyses.</span></p><p>Address of the bookmark: <a href="http://www.gigasciencejournal.com/content/2/1/15?utm_content=buffer25ee0&amp;utm_medium=social&amp;utm_source=twitter.com&amp;utm_campaign=buffer" rel="nofollow">http://www.gigasciencejournal.com/content/2/1/15?utm_content=buffer25ee0&amp;utm_medium=social&amp;utm_source=twitter.com&amp;utm_campaign=buffer</a></p>]]></description>
	<dc:creator>RAJESH DETROJA</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/27321/slurm-basics</guid>
	<pubDate>Fri, 13 May 2016 04:42:24 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/27321/slurm-basics</link>
	<title><![CDATA[SLURM basics !]]></title>
	<description><![CDATA[<p><a href="http://bioinformaticsonline.com/bookmarks/view/27238/slurm" target="_blank">SLURM</a> is a queue management system and stands for Simple Linux Utility for Resource Management. SLURM was developed at the Lawrence Livermore National Lab and currently runs some of the largest compute clusters in the world.</p><p>SLURM is similar in many ways to most other queue systems. You write a batch script then submit it to the queue manager. The queue manager then schedules your job to run on the queue (or partition in SLURM parlance) that you designate. Below we will provide an outline of how to submit jobs to SLURM, how SLURM decides when to schedule your job and how to monitor progress.</p><p>SLURM has a number of valuable features compared to other job management systems:</p><ul>
<li><em>Kill and Requeue</em> SLURM&rsquo;s ability to kill and requeue is superior to that of other systems. It waits for jobs to be cleared before scheduling the high priority job. It also does kill and requeue on memory rather than just on core count.</li>
<li><em>Memory</em> Memory requests are sacrosanct in SLURM. Thus the amount of memory you request at run time is guaranteed to be there. No one can infringe on that memory space and you cannot exceed the amount of memory that you request.</li>
<li><em>Accounting Tools</em> SLURM has a back end database which stores historical information about the cluster. This information can be queried by the users who are curious about how much resources they have used.</li>
</ul><p><strong>Summary of SLURM commands</strong></p><p>The table below shows a summary of SLURM commands. These commands are described in more detail below along with links to the SLURM doc site.</p><table>
<tbody>
<tr><th>&nbsp;</th><th>SLURM</th><th>SLURM Example</th></tr>
<tr>
<td>Submit a batch serial job</td>
<td><a href="http://slurm.schedmd.com/sbatch.html">sbatch</a></td>
<td><code>sbatch runscript.sh</code></td>
</tr>
<tr>
<td>Run a script interatively</td>
<td><a href="http://slurm.schedmd.com/srun.html">srun</a></td>
<td><code>srun --pty -p interact -t 10 --mem 1000 /bin/bash /bin/hostname</code></td>
</tr>
<tr>
<td>Kill a job</td>
<td><a href="http://slurm.schedmd.com/scancel.html">scancel</a></td>
<td><code>scancel 999999</code></td>
</tr>
<tr>
<td>View status of queues</td>
<td><a href="http://slurm.schedmd.com/squeue.html">squeue</a></td>
<td><code>squeue -u akitzmiller</code></td>
</tr>
<tr>
<td>Check current job by id</td>
<td><a href="http://slurm.schedmd.com/squeue.html">sacct</a></td>
<td><code>sacct -j 999999</code></td>
</tr>
</tbody>
</table>]]></description>
	<dc:creator>Radha Agarkar</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38378/gwaspro-a-high-performance-genome-wide-association-analysis-server</guid>
	<pubDate>Fri, 07 Dec 2018 08:04:57 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38378/gwaspro-a-high-performance-genome-wide-association-analysis-server</link>
	<title><![CDATA[GWASpro: A High-Performance Genome-Wide Association Analysis Server]]></title>
	<description><![CDATA[<p>GWASpro supports building complex design matrices, by which complex experimental designs that may include replications, treatments, locations and times, can be accounted for in the linear mixed model (LMM). GWASpro is optimized to handle GWAS data that may consist of up to 10 million markers and 10,000 samples from replicable lines or hybrids. GWASpro provides an interface that significantly reduces the learning curve for new GWAS investigators.</p>
<p>&nbsp;</p><p>Address of the bookmark: <a href="https://bioinfo.noble.org/GWASPRO/" rel="nofollow">https://bioinfo.noble.org/GWASPRO/</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>

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