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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/44900?offset=30</link>
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	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36927/restrictiondigest-a-powerful-perl-module-for-simulating-genomic-restriction-digests</guid>
	<pubDate>Tue, 12 Jun 2018 13:17:13 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36927/restrictiondigest-a-powerful-perl-module-for-simulating-genomic-restriction-digests</link>
	<title><![CDATA[RestrictionDigest: A powerful Perl module for simulating genomic restriction digests]]></title>
	<description><![CDATA[RestrictionDigest can simulate the reference genome digestion and generate comprehensive information of the simulation. It can simulate single-enzyme digestion, double-enzyme digestion and size selection process. It can also analyze multiple genomes at one run and generates concise comparison of enzyme(s) performance across the genomes.

For more information, please see the academic paper published online (http://www.sciencedirect.com/science/article/pii/S071734581630001X).<p>Address of the bookmark: <a href="https://github.com/JINPENG-WANG/RestrictionDigest" rel="nofollow">https://github.com/JINPENG-WANG/RestrictionDigest</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38420/regioner-an-r-package-for-the-management-and-comparison-of-genomic-regions</guid>
	<pubDate>Tue, 11 Dec 2018 08:43:51 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38420/regioner-an-r-package-for-the-management-and-comparison-of-genomic-regions</link>
	<title><![CDATA[regioneR: an R package for the management and comparison of genomic regions]]></title>
	<description><![CDATA[<p><span>Regioner is an R package for the management and comparison of genomic regions. It offers a set of function for basic manipulation of region sets extending the functionality of GenomicRanges and a powerful and customizable permutation test framework. With it, it's possible to study the association of a set of regions with other sets of regions, functions defined over the genome or essentially any user defined function.</span></p>
<p><span>http://gattaca.imppc.org/regioner/</span></p><p>Address of the bookmark: <a href="http://gattaca.imppc.org/regioner/" rel="nofollow">http://gattaca.imppc.org/regioner/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/39450/apollo-first-instantaneous-collaborative-genomic-annotation-editor-available-on-the-web</guid>
	<pubDate>Fri, 31 May 2019 19:55:39 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/39450/apollo-first-instantaneous-collaborative-genomic-annotation-editor-available-on-the-web</link>
	<title><![CDATA[Apollo: First instantaneous, collaborative genomic annotation editor available on the Web]]></title>
	<description><![CDATA[<ul>
<li>Apollo is a plug-in for the&nbsp;<a href="http://jbrowse.org/">JBrowse</a>&nbsp;Genome Viewer.</li>
<li>In addition to genes and pseudogenes, users can annotate ncRNAs (snRNA, snoRNA, tRNA, rRNA), miRNAs, repeat regions, and transposable elements; each annotation type has its own configuration of the &lsquo;Information Editor&rsquo;.</li>
<li>History tracking with undo/redo functions is available.</li>
<li>Users are able to directly set an annotation to a specific state, choosing from the &lsquo;History&rsquo; display.</li>
<li>Adding and updating PubMed IDs will prompt users with a publication title to confirm their submission.</li>
<li>Gene Ontology (GO) terms are supported and GO ID auto-completion has been incorporated.</li>
<li>Users may access a &lsquo;Recent Changes&rsquo; page.</li>
<li>Help page with Apollo specific content is available.</li>
</ul><p>Address of the bookmark: <a href="http://genomearchitect.github.io/" rel="nofollow">http://genomearchitect.github.io/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41464/phytozome-v121-plant-science-community-hub-for-accessing-palnts-genomic-data</guid>
	<pubDate>Tue, 17 Mar 2020 07:30:17 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41464/phytozome-v121-plant-science-community-hub-for-accessing-palnts-genomic-data</link>
	<title><![CDATA[Phytozome  v12.1: plant science community hub for accessing palnts genomic data]]></title>
	<description><![CDATA[<p>Phytozome, the Plant Comparative Genomics portal of the Department of Energy's Joint Genome Institute, provides JGI users and the broader plant science community a hub for accessing, visualizing and analyzing JGI-sequenced plant genomes, as well as selected genomes and datasets that have been sequenced elsewhere. As of release v12.1.6, Phytozome hosts 93 assembled and annotated genomes, from 82 Viridiplantae species. More than half of these genomes have been sequenced, assembled and/or annotated with JGI Plant Science program resources. By integrating this large collection of plant genomes into a single resource and performing comprehensive and uniform annotation and analyses, Phytozome facilitates accurate and insightful comparative genomics studies.</p><p>Address of the bookmark: <a href="https://phytozome.jgi.doe.gov/pz/portal.html" rel="nofollow">https://phytozome.jgi.doe.gov/pz/portal.html</a></p>]]></description>
	<dc:creator>Surabhi Chaudhary</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44630/genofig-a-user-friendly-application-for-the-visualization-and-comparison-of-genomic-regions</guid>
	<pubDate>Mon, 05 Aug 2024 23:06:58 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44630/genofig-a-user-friendly-application-for-the-visualization-and-comparison-of-genomic-regions</link>
	<title><![CDATA[GenoFig: a user-friendly application for the visualization and comparison of genomic regions]]></title>
	<description><![CDATA[<p>Tool for graphical vizualisation of annotated genetic regions, and homologous regions comparison. It is an independent recoding of Easyfig 2 initially developped by at the S. Beatson Lab [<a href="https://mjsull.github.io/Easyfig/" target="_blank">https://mjsull.github.io/Easyfig/</a>]</p>
<p dir="auto">Download the GenoFig source code using the 'Download' button on top of this page. Cloning is currently not available for people not member of the INRAE French Institution. After decompression, open a terminal in the folder containing the decompressed files and run:</p>
<div>
<pre id="code-47"><code><span>conda env create -f extras/requirements.yml</span>
<span>extras/SETUP.sh</span></code></pre>
</div><p>Address of the bookmark: <a href="https://forgemia.inra.fr/public-pgba/genofig" rel="nofollow">https://forgemia.inra.fr/public-pgba/genofig</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/22570/frequent-words-problem-solution-by-perl</guid>
	<pubDate>Tue, 09 Jun 2015 23:38:44 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/22570/frequent-words-problem-solution-by-perl</link>
	<title><![CDATA[Frequent words problem solution by Perl]]></title>
	<description><![CDATA[<div><p>Solved with perl <a href="http://rosalind.info/problems/1a/">http://rosalind.info/problems/1a/</a></p><p>#Find the most frequent k-mers in a string.<br />#Given: A DNA string Text and an integer k.<br />#Return: All most frequent k-mers in Text (in any order).<br /><br />use strict;<br />use warnings;<br /><br />my $string="ACGTTGCATGTCGCATGATGCATGAGAGCT";<br />my $kmer=4; <br />my %myHash;<br />my $max=0;<br /><br />for (my $aa=0; $aa&lt;=(length($string)-4); $aa++) {<br />&nbsp;&nbsp; &nbsp;my $myStr=substr&nbsp; $string, $aa,$kmer;<br />&nbsp;&nbsp; &nbsp;#print "$myStr\n";<br />&nbsp;&nbsp; &nbsp;my $km=kmerMatch ($string, $myStr, $kmer);<br />&nbsp;&nbsp; &nbsp;if ($km &gt; $max) { $max = $km;}<br />&nbsp;&nbsp; &nbsp;#print "$km\t$myStr\n";<br />&nbsp;&nbsp; &nbsp;$myHash{$myStr}=$km;<br />&nbsp;&nbsp; &nbsp;<br />}<br /><br />#Print all key which have matching values<br />foreach my $name (keys %myHash){<br />&nbsp;&nbsp;&nbsp; print "$name " if $myHash{$name} == $max;<br />}<br /><br />sub kmerMatch { #Check the exact matching kmers with sliding window<br />my ($string, $myStr, $kmer)=@_;<br />my $count=0;<br />for (my $aa=0; $aa&lt;=(length($string)-4); $aa++) {<br />&nbsp;&nbsp; &nbsp;my $myWin=substr&nbsp; $string, $aa,$kmer;<br />&nbsp;&nbsp; &nbsp;if ($myWin eq $myStr) {<br />&nbsp;&nbsp; &nbsp;&nbsp;&nbsp; &nbsp;#print "$myWin eq $myStr\n";<br />&nbsp;&nbsp; &nbsp;&nbsp;&nbsp; &nbsp;$count++;<br />&nbsp;&nbsp; &nbsp;}<br />}<br />return $count;<br />}</p></div>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/22572/clump-finding-problem-solved-with-perl</guid>
	<pubDate>Wed, 10 Jun 2015 00:17:17 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/22572/clump-finding-problem-solved-with-perl</link>
	<title><![CDATA[Clump Finding Problem Solved with Perl]]></title>
	<description><![CDATA[<p>The question at http://rosalind.info/problems/1d/</p><p>Script are moved to&nbsp;http://bioinformaticsonline.com/snippets/view/34633/clump-finding-problem-solved-with-perl</p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38212/megahit-an-ultra-fast-single-node-solution-for-large-and-complex-metagenomics-assembly-via-succinct-de-bruijn-graph</guid>
	<pubDate>Wed, 14 Nov 2018 04:50:27 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38212/megahit-an-ultra-fast-single-node-solution-for-large-and-complex-metagenomics-assembly-via-succinct-de-bruijn-graph</link>
	<title><![CDATA[MEGAHIT: an ultra-fast single-node solution for large and complex metagenomics assembly via succinct de Bruijn graph]]></title>
	<description><![CDATA[<p><span>MEGAHIT is a single node assembler for large and complex metagenomics NGS reads, such as soil. It makes use of succinct&nbsp;</span><em>de Bruijn</em><span>&nbsp;graph (SdBG) to achieve low memory assembly. MEGAHIT can&nbsp;</span><span>optionally</span><span>&nbsp;utilize a CUDA-enabled GPU to accelerate its SdBG contstruction. The GPU-accelerated version of MEGAHIT has been tested on NVIDIA GTX680 (4G memory) and Tesla K40c (12G memory) with CUDA 5.5, 6.0 and 6.5. MEGAHIT v1.0 or greater also supports IBM Power PC and has been tested on IBM POWER8.</span></p>
<p><span>https://academic.oup.com/bioinformatics/article/31/10/1674/177884</span></p><p>Address of the bookmark: <a href="https://github.com/voutcn/megahit" rel="nofollow">https://github.com/voutcn/megahit</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/13226/you-and-your-friend-have-similar-dna</guid>
	<pubDate>Sun, 27 Jul 2014 20:44:05 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/13226/you-and-your-friend-have-similar-dna</link>
	<title><![CDATA[You and your friend have similar DNA !!!]]></title>
	<description><![CDATA[<p>New research out of Massachusetts claims that people often choose friends that are similar to them in genetics and they are more accurate than you might suppose. A study published on PNAS&nbsp;http://www.pnas.org/content/111/Supplement_3/10796.full found that people are apt to pick friends who are genetically similar to themselves - so much so that friends tend to be as alike at the genetic level as a person's fourth cousin.</p><div style="text-align: center;"><img src="http://i.kinja-img.com/gawker-media/image/upload/s--CwLwHa43--/18fbmlokxcmqcjpg.jpg" alt="image" width="300" height="271" style="border: 0px; border: 0px;"></div><p>Scientists with a long-running Framingham Heart Study looked at 1,932 people (examination of about 1.5 million markers of genetic variations), comparing unrelated friends to unrelated strangers. They found that friends shared about 1% of their genes &mdash; a percentage much higher than those shared with strangers.This new findings made it clear that people have more DNA in common with those who are selected as friends than with strangers in the same population.&nbsp;</p><p>The genes that lined up the most were olfactory genes, which deal with smell. The ones that lined up the least were immune system genes. The researchers weren't sure why that happened :/. Olfactory genes might be a straightforward explanation: People who like the same smells tend to be drawn to similar environments, where they meet others with the same tendencies.</p><p>Reference:</p><p>http://www.pnas.org/content/111/Supplement_3/10796.full</p><p>Image : http://i.kinja-img.com</p>]]></description>
	<dc:creator>Jit</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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