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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/37584?offset=240</link>
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	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/file/view/22053/binc-sample-question-paper</guid>
	<pubDate>Thu, 16 Apr 2015 09:16:18 -0500</pubDate>
	<link>https://bioinformaticsonline.com/file/view/22053/binc-sample-question-paper</link>
	<title><![CDATA[BINC Sample Question Paper !!!]]></title>
	<description><![CDATA[<p>BINC sample question paper. Wish you all the best for BINC examination.</p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
	<enclosure url="https://bioinformaticsonline.com/file/download/22053" length="4041" type="text/plain" />
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/22569/reverse-complement-problem-solved-with-perl</guid>
	<pubDate>Tue, 09 Jun 2015 23:37:23 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/22569/reverse-complement-problem-solved-with-perl</link>
	<title><![CDATA[Reverse Complement Problem Solved with Perl]]></title>
	<description><![CDATA[<p>Question at http://rosalind.info/problems/1b/</p><p>#Find the reverse complement of a DNA string.<br />#Given: A DNA string Pattern.<br />#Return: Pattern, the reverse complement of Pattern.<br /><br />use strict;<br />use warnings;<br /><br />my $string="AAAACCCGGT";<br />my $finalString="";<br />my %hash = (<br />&nbsp;&nbsp; &nbsp;"C" =&gt; "G", <br />&nbsp;&nbsp; &nbsp;"A" =&gt; "T", <br />&nbsp;&nbsp; &nbsp;"T" =&gt; "A", <br />&nbsp;&nbsp; &nbsp;"G" =&gt; "C",<br />);<br /><br />for (my $aa=0; $aa&lt;=(length($string)-1); $aa++) {<br />&nbsp;&nbsp; &nbsp;my $char=substr $string, $aa, 1;<br />&nbsp;&nbsp; &nbsp;#print $hash{$char};<br />&nbsp;&nbsp; &nbsp;$finalString="$hash{$char}"."$finalString";<br />}<br /><br />print $finalString;<br />print "\n";</p>]]></description>
	<dc:creator>Jit</dc:creator>
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<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/poll/view/22906/at-what-age-did-you-gain-passion-in-bioinformatics</guid>
	<pubDate>Tue, 23 Jun 2015 10:39:06 -0500</pubDate>
	<link>https://bioinformaticsonline.com/poll/view/22906/at-what-age-did-you-gain-passion-in-bioinformatics</link>
	<title><![CDATA[At what age did you gain passion in Bioinformatics?]]></title>
	<description><![CDATA[<p>Most of the bioinformatician were biologist ( yeah ... not all ;), and at later stage they gain a passion in Bioinformatics and learn it. When did you get inclined towards computational analysis of biological data?</p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/23892/bioinformatics-made-easy-search-bioinformatics-tools-and-run-genomic-analysis-in-the-cloud</guid>
	<pubDate>Thu, 20 Aug 2015 02:21:20 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/23892/bioinformatics-made-easy-search-bioinformatics-tools-and-run-genomic-analysis-in-the-cloud</link>
	<title><![CDATA[Bioinformatics Made Easy Search: Bioinformatics tools and run genomic analysis in the cloud]]></title>
	<description><![CDATA[<p>InsideDNA makes hundreds of bioinformatics tools immediately available to run via an easy-to-use web interface and allows an accurate search across all functions, tools and pipelines.</p>
<p>With InsideDNA, you can upload and store your own genomic/genetic datasets in a limitless cloud space, and instantly analyze it with a powerful compute instance, without any tool installation or set up hassle.</p>
<p>More at https://insidedna.me/</p><p>Address of the bookmark: <a href="https://insidedna.me/" rel="nofollow">https://insidedna.me/</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/42810/bioinformatics-in-africa-part3-mali</guid>
	<pubDate>Sat, 06 Feb 2021 13:28:44 -0600</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/42810/bioinformatics-in-africa-part3-mali</link>
	<title><![CDATA[Bioinformatics in Africa: Part3 - Mali]]></title>
	<description><![CDATA[<p>International&nbsp;Center&nbsp;for&nbsp;Excellence&nbsp;in&nbsp;Research&nbsp;(ICER):</p><p>The&nbsp;ICER&nbsp;is&nbsp;a&nbsp;research&nbsp;center&nbsp;composed&nbsp;of&nbsp;the&nbsp;following&nbsp;three&nbsp;programs: 1. The&nbsp;Malaria&nbsp;Research&nbsp;and&nbsp;Training&nbsp;Center&nbsp;&shy;&nbsp;Parasitology&nbsp;Group,&nbsp; 2. The&nbsp;Malaria&nbsp;Research&nbsp;and&nbsp;Training&nbsp;Center&nbsp;&shy;&nbsp;Entomology&nbsp;Group&nbsp; 3. The&nbsp;SEREFO&nbsp;Group.</p><p>The&nbsp;first&nbsp;two&nbsp;programs&nbsp;develop&nbsp;biomedical&nbsp;researches&nbsp;in&nbsp;malaria,&nbsp;Filariasis&nbsp;and&nbsp;Leishmaniasis.&nbsp;The&nbsp; third&nbsp;program&nbsp;develops&nbsp;biomedical&nbsp;researches&nbsp;in&nbsp;tuberculosis&nbsp;and&nbsp;HIV.</p><p>Bioinformatics&nbsp;was&nbsp;introduced&nbsp;recently&nbsp;to&nbsp;the&nbsp;ICER&nbsp;and&nbsp;is&nbsp;constantly&nbsp;growing.&nbsp;The&nbsp;ICER&nbsp;has&nbsp;one&nbsp; team,&nbsp;headed&nbsp;by&nbsp;Sidy&nbsp;SOUMARE,&nbsp;which&nbsp;supports&nbsp;the&nbsp;three&nbsp;programmes&nbsp;in&nbsp;all&nbsp;their&nbsp;needs&nbsp;in&nbsp; informatics&nbsp;and&nbsp;bioinformatics.&nbsp;This&nbsp;team&nbsp;can&nbsp;beneficiate&nbsp;from&nbsp;some&nbsp;computational&nbsp;facilities&nbsp;(4&nbsp; blast&nbsp;servers,&nbsp;15&nbsp;other&nbsp;servers&nbsp;and&nbsp;around&nbsp;200&nbsp;terminals),&nbsp;but&nbsp;the&nbsp;ICER&nbsp;staff&nbsp;needs&nbsp;some&nbsp;training&nbsp;in&nbsp; order&nbsp;to&nbsp;be&nbsp;able&nbsp;to&nbsp;administrate&nbsp;these&nbsp;facilities.</p><p>Research&nbsp;Interest&nbsp;and&nbsp;Activities: The&nbsp;following&nbsp;are&nbsp;the&nbsp;present&nbsp;areas&nbsp;of&nbsp;research&nbsp;interest: 1. Functional&nbsp;genomics 2. Analysis&nbsp;of&nbsp;microarray&nbsp;data 3. Interaction&nbsp;between&nbsp;the&nbsp;vector&nbsp;and&nbsp;the&nbsp;parasite.</p>]]></description>
	<dc:creator>BioStar</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42012/phewas-r-package-is-designed-to-provide-an-accessible-interface-to-the-phenome-wide-association-study</guid>
	<pubDate>Thu, 30 Jul 2020 22:06:37 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42012/phewas-r-package-is-designed-to-provide-an-accessible-interface-to-the-phenome-wide-association-study</link>
	<title><![CDATA[PheWAS: R package is designed to provide an accessible interface to the phenome wide association study]]></title>
	<description><![CDATA[<p>The PheWAS R package is designed to provide an accessible interface to the phenome wide association study. For a description of the methods available and some simple examples, please see the&nbsp;<a href="https://github.com/PheWAS/PheWAS/blob/master/inst/doc/PheWAS-package.pdf?raw=true">package vignette</a>&nbsp;or the R documentation. For installation help, see below. ##Installing the PheWAS Package The PheWAS package can be installed using the devtools package. The following code when executed in R will get you started:</p>
<pre><code>install.packages("devtools")
#It may be necessary to install required as not all package dependencies are installed by devtools:
install.packages(c("dplyr","tidyr","ggplot2","MASS","meta","ggrepel","DT"))
devtools::install_github("PheWAS/PheWAS")
library(PheWAS)</code></pre><p>Address of the bookmark: <a href="https://github.com/PheWAS/PheWAS" rel="nofollow">https://github.com/PheWAS/PheWAS</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/12944/orione-%E2%80%93-a-web-based-framework-for-ngs-analysis-in-microbiology</guid>
	<pubDate>Wed, 23 Jul 2014 06:43:03 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/12944/orione-%E2%80%93-a-web-based-framework-for-ngs-analysis-in-microbiology</link>
	<title><![CDATA[Orione – a web-based framework for NGS analysis in microbiology]]></title>
	<description><![CDATA[<p>End-to-end NGS microbiology data analysis requires a diversity of tools covering bacterial resequencing, de novo assembly, scaffolding, bacterial RNA-Seq, gene annotation and metagenomics. However, the construction of computational pipelines that use different software packages is difficult due to a lack of interoperability, reproducibility, and transparency. To overcome these limitations researchers at <a href="http://www.crs4.it/" target="_blank">CRS4</a>, Italy have developed Orione, a Galaxy-based framework consisting of publicly available research software and specifically designed pipelines to build complex, reproducible workflows for NGS microbiology data analysis. Enabling microbiology researchers to conduct their own custom analysis and data manipulation without software installation or programming, Orione provides new opportunities for data-intensive computational analyses in microbiology and metagenomics.</p>
<p>Reference</p>
<p>Cuccuru G1, Orsini M, Pinna A, Sbardellati A, Soranzo N, Travaglione A, Uva P, Zanetti G, Fotia G. (2014)<strong> Orione, a web-based framework for NGS analysis in microbiology.</strong> <em>Bioinformatics</em> [Epub ahead of print]. [<a href="http://bioinformatics.oxfordjournals.org/content/early/2014/03/10/bioinformatics.btu135.long" target="_blank">article</a>]</p><p>Address of the bookmark: <a href="http://orione.crs4.it/" rel="nofollow">http://orione.crs4.it/</a></p>]]></description>
	<dc:creator>Martin Jones</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/26927/phylographer-graph-visualization-tool</guid>
	<pubDate>Wed, 06 Apr 2016 19:06:48 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/26927/phylographer-graph-visualization-tool</link>
	<title><![CDATA[PhyloGrapher - Graph Visualization Tool]]></title>
	<description><![CDATA[<p><strong>PhyloGrapher</strong><span>&nbsp;is a program designed to visualize and study evolutionary relationships within families of homologous genes or proteins (elements).</span><strong>PhyloGrapher</strong><span>&nbsp;is a drawing tool that generates custom graphs for a given set of elements. In general, it is possible to use&nbsp;</span><strong>PhyloGrapher</strong><span>&nbsp;to visualize any type of relations between elements.&nbsp;</span></p>
<p><span>More at&nbsp;http://www.atgc.org/PhyloGrapher/PhyloGrapher_Welcome.html</span></p><p>Address of the bookmark: <a href="http://www.atgc.org/PhyloGrapher/PhyloGrapher_Welcome.html" rel="nofollow">http://www.atgc.org/PhyloGrapher/PhyloGrapher_Welcome.html</a></p>]]></description>
	<dc:creator>Jitendra Prajapati</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27821/blobsplorer</guid>
	<pubDate>Tue, 14 Jun 2016 10:28:58 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27821/blobsplorer</link>
	<title><![CDATA[Blobsplorer]]></title>
	<description><![CDATA[<p>Blobsplorer is a tool for interactive visualization of assembled DNA sequence data ("contigs") derived from (often unintentionally) mixed-species pools. It allows the simultaneous display of GC content, coverage, and taxonomic annotation for collections of contigs with a view to separating out those belonging to different taxa.</p>
<p>Blobsplorer is unlikely to be of use on its own as it requires contig data to be supplied in a format that involves considerable preprocessing (see below for a description). The easiest way to use Blobsplorer is as part of a workflow using scripts from <a href="https://github.com/blaxterlab/blobology">here</a>.</p><p>Address of the bookmark: <a href="http://nematodes.org/martin/blobsplorer/blobsplorer.html" rel="nofollow">http://nematodes.org/martin/blobsplorer/blobsplorer.html</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/28200/machine-learning</guid>
	<pubDate>Fri, 01 Jul 2016 12:57:12 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/28200/machine-learning</link>
	<title><![CDATA[Machine Learning !!!]]></title>
	<description><![CDATA[<p>In machine learning, computers apply&nbsp;<strong>statistical learning</strong>&nbsp;techniques to automatically identify patterns in data. These techniques can be used to make highly accurate predictions.</p>
<p><em>Keep scrolling.</em>&nbsp;Using a data set about homes, we will create a machine learning model to distinguish homes in New York from homes in San Francisco.</p><p>Address of the bookmark: <a href="http://www.r2d3.us/visual-intro-to-machine-learning-part-1/" rel="nofollow">http://www.r2d3.us/visual-intro-to-machine-learning-part-1/</a></p>]]></description>
	<dc:creator>Gudiya Pal</dc:creator>
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