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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/38762?offset=250</link>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/17843/pathway-analysis</guid>
	<pubDate>Fri, 03 Oct 2014 08:51:13 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/17843/pathway-analysis</link>
	<title><![CDATA[Pathway Analysis]]></title>
	<description><![CDATA[<p>Pathway Analysis is usually performed with aim to enrich the genes with their functional information and reveal the underlying biological mechanisms pursue by genes. Pathway Analysis is not only limited to what biological pathways a particular set of expressed genes follow but also to disclose the relationships between these genes. With availability of more genomics, transcriptomics and proteomics data, interactions between genes involve in multiple pathways become more clear and also relationships between the genes, their transcripts, and their gene products. However, existing tools and dbs mainly based on knowledge driven approach in which pathways will be identified by finding the correlation between the&nbsp;<span>information in one of the pathway knowledge databases (KEGG,Reactome,Panther,BioCarta, Panther,GO,NCI,WikiPathways,etc) and gene expression result for a specific conditions for instance tumor, obesity , cold resistant crops/plants, etc.</span></p><p><span><strong>Introductory Articles/ppt/sources</strong>:</span></p><p><a href="http://www.ploscompbiol.org/article/info%3Adoi%2F10.1371%2Fjournal.pcbi.1002375"><span>http://www.ploscompbiol.org/article/info%3Adoi%2F10.1371%2Fjournal.pcbi.1002375</span></a></p><p><a href="http://bioinformatics.mdanderson.org/MicroarrayCourse/Lectures09/Pathway%20Analysis.pdf"><span>http://bioinformatics.mdanderson.org/MicroarrayCourse/Lectures09/Pathway%20Analysis.pdf</span></a></p><p><a href="http://gettinggeneticsdone.blogspot.de/2012/03/pathway-analysis-for-high-throughput.html"><span>http://gettinggeneticsdone.blogspot.de/2012/03/pathway-analysis-for-high-throughput.html</span></a></p><p><a href="http://davetang.org/muse/tag/pathway/"><span>http://davetang.org/muse/tag/pathway/</span></a></p><p><a href="https://www.biostars.org/p/42219/"><span>https://www.biostars.org/p/42219/</span></a></p><p><a href="http://bioinformatics.ca//files/public/Pathways_2014_Module4_v2.pdf"><span>http://bioinformatics.ca//files/public/Pathways_2014_Module4_v2.pdf</span></a></p><p><a href="http://bioinformatics.ca//files/public/Pathways_2014_Module2.pdf"><span>http://bioinformatics.ca//files/public/Pathways_2014_Module2.pdf</span></a></p><p><span><strong>Impotant Database and Tools</strong>:</span></p><p>GeneMANIA, Cytoscape,&nbsp;<a href="http://www.ingenuity.com/products/ipa">IPA</a>&nbsp;and <a href="http://thomsonreuters.com/metacore/">Metacore</a> (Commerical ),&nbsp;<span>Pathway Commons, Reactome ,Panther, BioCyc, WikiPathways, Pathvisio, KEGG, NCI, Stringdb, Amigo,&nbsp;<span>WebGestalt ,<span>ConsensusPathDB ,GSEA,Blast2go</span></span></span></p><p><span><strong>Popular R based tools</strong>:</span></p><p><span>Reactome.db, ReactomePA, ClusterProfiler, Gage, SPIA, topGO, Pathview,DOSE,GOStat</span></p><p><span><strong>More</strong>:</span></p><p><a href="http://www.bioconductor.org/help/search/index.html?q=Enrichment+analysis+"><span>http://www.bioconductor.org/help/search/index.html?q=Enrichment+analysis+</span></a></p><p>&nbsp;</p>]]></description>
	<dc:creator>Rahul Agarwal</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27841/covcal-coverage-read-count-calculator</guid>
	<pubDate>Wed, 15 Jun 2016 18:08:13 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27841/covcal-coverage-read-count-calculator</link>
	<title><![CDATA[CovCal: Coverage / Read Count Calculator]]></title>
	<description><![CDATA[<h2>Coverage / Read Count Calculator</h2>
<h4>Calculate how much sequencing you need to hit a target depth of coverage (or vice versa).</h4>
<p><span>Instructions:</span> set the read length/configuration and genome size, then select what you want to calculate.</p>
<p>Written by <a href="http://stephenturner.us/" target="blank">Stephen Turner</a>, based on the <a href="http://www.ncbi.nlm.nih.gov/pubmed/3294162" target="_blank">Lander-Waterman formula</a>, inspired by <a href="http://core-genomics.blogspot.com/2016/05/how-many-reads-to-sequence-genome.html" target="_blank">a similar calculator</a> written by James Hadfield. Coverage is calculated as <em>C=LN/G</em> and reads as <em>N=CG/L</em> where <em>C</em> = Coverage (X),<em>L</em> = Read length (bp), <em>G</em> = Haploid genome size (bp), and <em>N</em> = Number of reads. Source code <a href="https://github.com/stephenturner/covcalc" target="_blank">on GitHub</a>.</p><p>Address of the bookmark: <a href="http://apps.bioconnector.virginia.edu/covcalc/" rel="nofollow">http://apps.bioconnector.virginia.edu/covcalc/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/32948/simba-a-web-tool-for-managing-bacterial-genome-assembly-generated-by-ion-pgm-sequencing-technology</guid>
	<pubDate>Tue, 23 May 2017 05:28:56 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/32948/simba-a-web-tool-for-managing-bacterial-genome-assembly-generated-by-ion-pgm-sequencing-technology</link>
	<title><![CDATA[SIMBA: a web tool for managing bacterial genome assembly generated by Ion PGM sequencing technology]]></title>
	<description><![CDATA[<p><span>SIMBA</span><span>, SImple Manager for Bacterial Assemblies, is a Web interface for managing assembly projects of bacterial genomes. SIMBA was created to assist bioinformaticians to assemble bacterial genomes sequenced with NextGeneration Sequencing (NGS) platforms quickly, easily and effectively. SIMBA also is open source tool, i.e., can be freely downloaded, shared and modified.</span></p>
<p>https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-016-1344-7</p><p>Address of the bookmark: <a href="http://ufmg-simba.sourceforge.net/" rel="nofollow">http://ufmg-simba.sourceforge.net/</a></p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/35055/jabba-hybrid-error-correction-for-long-sequencing-reads</guid>
	<pubDate>Fri, 05 Jan 2018 03:58:14 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/35055/jabba-hybrid-error-correction-for-long-sequencing-reads</link>
	<title><![CDATA[Jabba: Hybrid Error Correction for Long Sequencing Reads]]></title>
	<description><![CDATA[<p>Jabba is a hybrid error correction tool to correct third generation (PacBio / ONT) sequencing data, using second generation (Illumina) data.</p>
<p>Input</p>
<p>Jabba takes as input a concatenated de Bruijn graph and a set of sequences:</p>
<p>the de Bruijn graph should appear in fasta format with 1 entry per node, the meta information should be in the format:<br>&gt;NODE <br>the set of sequences should be in fasta or fastq format. These sequences will be corrected (e.g. PacBio reads). The corrections will be written to a file Jabba fasta.<br>The output is a file in fasta format with corrections of the long reads, and additionally a file in the input format containing uncorrected reads.</p>
<p>https://github.com/biointec/jabba/wiki</p>
<p>https://almob.biomedcentral.com/articles/10.1186/s13015-016-0075-7</p><p>Address of the bookmark: <a href="https://github.com/biointec/jabba" rel="nofollow">https://github.com/biointec/jabba</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41691/genobuntu-package-for-next-generation-sequencing-and-genome-assembly</guid>
	<pubDate>Mon, 18 May 2020 16:47:56 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41691/genobuntu-package-for-next-generation-sequencing-and-genome-assembly</link>
	<title><![CDATA[Genobuntu: Package for Next Generation Sequencing and Genome Assembly]]></title>
	<description><![CDATA[<div>
<p>Genobuntu is a software package containing more than 70 software and packages oriented towards NGS. In its current version, Genobuntu supports pre assembly tools, genome assemblers as well as post assembly tools.<br><br>Commonly used biological software and example script files for different assembly pipelines have also been provided, where the example script files can be updated to suit one&rsquo;s experimental needs. Genobuntu attempts to reduce the amount of time and energy needed to build software workstations and it can also act as a good teaching source for a class room setting.<br><br>Therefore, Genobuntu offers a well-tailored environment for both novices and experts working in the field of genome assembly.</p>
</div>
<div>
<h3>Features</h3>
<ul>
<li>Velvet</li>
<li>MiB</li>
<li>SSAKE</li>
<li>EULER</li>
<li>VCAKE</li>
<li>ABySS</li>
<li>ALLPATHS</li>
<li>Celera</li>
<li>SHARCGS</li>
<li>Allpaths</li>
<li>IDBA</li>
<li>TAIPAN</li>
<li>Edena</li>
<li>SOAPdenovo</li>
<li>Maq</li>
<li>IDBA-UD</li>
<li>No. of Reads present in the Ref. Seq.</li>
<li>ART NGS Reads Simulator</li>
<li>HiTEC, FASTQC</li>
<li>Minimum Description Length</li>
<li>SOAPaligner</li>
<li>Sequencing Read Archive Toolkit</li>
</ul>
</div><p>Address of the bookmark: <a href="https://sourceforge.net/projects/genobuntu/" rel="nofollow">https://sourceforge.net/projects/genobuntu/</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/4210/uni-computing-bergen-norway</guid>
  <pubDate>Tue, 03 Sep 2013 18:40:50 -0500</pubDate>
  <link></link>
  <title><![CDATA[Uni Computing Bergen Norway]]></title>
  <description><![CDATA[
<p>Info on Uni Computing (Webpage: http://www.bccs.uni.no/) :</p>

<p>Uni Computing (formerly Uni BCCS) is a department of Uni Research, affiliated with the University of Bergen.</p>

<p>5 groups in this lab works on computational resources, methods, algorithms, and software.</p>

<p>Following two bioinformatics groups are:</p>

<p>The Computational Biology Unit (CBU) provides education and research in bioinformatics focused on functional genomics.</p>

<p>The Computational Ecology Unit (CEU) is basically deal with population fluctuations, behavioural patterns and the ways life cycles emerge.</p>
]]></description>
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<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/2631/what-junk-dna-it%E2%80%99s-an-operating-system</guid>
	<pubDate>Mon, 19 Aug 2013 15:24:26 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/2631/what-junk-dna-it%E2%80%99s-an-operating-system</link>
	<title><![CDATA[What Junk DNA? It’s an Operating System]]></title>
	<description><![CDATA[<p>The report adds to growing experimental support for the idea that all that extra stuff in the human genes, once referred to as &ldquo;junk DNA,&rdquo; is more than functionless, space-filling material that happens to make up nearly 98% of the genome. The paper adds to a growing body of knowledge establishing a considerable role for this material in the regulation of gene expression and its potential role in human disease.</p><p>Address of the bookmark: <a href="http://www.genengnews.com/keywordsandtools/print/3/32115/" rel="nofollow">http://www.genengnews.com/keywordsandtools/print/3/32115/</a></p>]]></description>
	<dc:creator>Rahul Agarwal</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/2991/illumina-reveals-first-dataset-of-long-reads</guid>
	<pubDate>Fri, 23 Aug 2013 06:29:14 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/2991/illumina-reveals-first-dataset-of-long-reads</link>
	<title><![CDATA[Illumina reveals first dataset of long reads]]></title>
	<description><![CDATA[<p>With the help of Moleculo technology , acquired by Illumina releases new service for long reads sequencing i.e., &nbsp;<a href="http://www.illumina.com/services/long-read-sequencing-service.ilmn">FastTrack Long Reads</a>.</p><p>Average read length is around<span>&nbsp;8,500 base pairs in release dataset.</span>&nbsp;Best thing about this, there is not much effect on cost and quality of data.</p><p>You can also check following pages for publications on long reads and more:</p><p><a href="http://www.illumina.com/services/long-read-sequencing-service.ilmn">http://www.illumina.com/services/long-read-sequencing-service.ilmn</a></p><p><a href="http://blog.basespace.illumina.com/2013/07/22/first-data-set-from-fasttrack-long-reads-early-access-service/">http://blog.basespace.illumina.com/2013/07/22/first-data-set-from-fasttrack-long-reads-early-access-service/</a></p><p>&nbsp;</p><p>&nbsp;</p>]]></description>
	<dc:creator>Rahul Agarwal</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/4288/new-born-babies-get-ready-to-know-their-whole-genome-soon</guid>
	<pubDate>Thu, 05 Sep 2013 07:24:02 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/4288/new-born-babies-get-ready-to-know-their-whole-genome-soon</link>
	<title><![CDATA[New born babies get ready to know their whole genome soon!!!]]></title>
	<description><![CDATA[<p>USA launch a pilot projects to examine medical information of newborn baby, which are being funded by the Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD) and the National Human Genome Research Institute (NHGRI), both parts of the National Institutes of Health.</p><p>Awards of $5 million to four grantees have been made in fiscal year 2013 under the Genomic Sequencing and Newborn Screening Disorders research program. The program will be funded at $25 million over five years, as funds are made available.</p><p>"Hundreds of US babies will be pioneers in genomic medicine through a&nbsp;US$25-million programme to sequence their genomes&nbsp;soon after they are born."</p><p><strong>Source</strong>:</p><p><a href="http://blogs.nature.com/news/2013/09/scientists-to-sequence-hundreds-of-newborns-genomes.html">http://blogs.nature.com/news/2013/09/scientists-to-sequence-hundreds-of-newborns-genomes.html</a></p><p><a href="http://www.genome.gov/27554919">http://www.genome.gov/27554919</a></p>]]></description>
	<dc:creator>Rahul Agarwal</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/5166/role-of-microbes-in-forensic-science</guid>
	<pubDate>Sun, 29 Sep 2013 10:07:20 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/5166/role-of-microbes-in-forensic-science</link>
	<title><![CDATA[Role of microbes in forensic science]]></title>
	<description><![CDATA[<p>"<span>Studies on decomposing mice suggest that the microbial content of a corpse can offer clues as to how old a body is and the approximate time that death occurred."</span><span><br /><br />Read more:&nbsp;<a href="http://www.digitaljournal.com/article/359185#ixzz2gIJFVHRo">http://www.digitaljournal.com/article/359185#ixzz2gIJFVHRo</a></span></p><p><span><a href="http://www.colorado.edu/news/releases/2013/09/24/new-cu-boulder-led-study-finds-%E2%80%98microbial-clock%E2%80%99-may-help-determine-time">http://www.colorado.edu/news/releases/2013/09/24/new-cu-boulder-led-study-finds-%E2%80%98microbial-clock%E2%80%99-may-help-determine-time</a></span></p><p><span>Paper:</span></p><p><span><a href="http://www.elifesciences.org/wp-content/uploads/2013/09/eLife.01104_INPRESS.pdf">http://www.elifesciences.org/wp-content/uploads/2013/09/eLife.01104_INPRESS.pdf</a></span></p>]]></description>
	<dc:creator>Rahul Agarwal</dc:creator>
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