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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/28290?offset=780</link>
	<atom:link href="https://bioinformaticsonline.com/related/28290?offset=780" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34324/orthognc-a-software-for-accurate-identification-of-orthologs-based-on-gene-neighborhood-conservation</guid>
	<pubDate>Tue, 14 Nov 2017 09:30:35 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34324/orthognc-a-software-for-accurate-identification-of-orthologs-based-on-gene-neighborhood-conservation</link>
	<title><![CDATA[OrthoGNC: A Software for Accurate Identification of Orthologs Based on Gene Neighborhood Conservation]]></title>
	<description><![CDATA[<div>
<p id="sp0005">Orthology relations can be used to transfer annotations from one gene (or protein) to another. Hence, detecting orthology relations has become an important task in the post-genomic era. Various genomic events, such as duplication and horizontal gene transfer, can cause erroneous assignment of orthology relations. In closely-related species, gene neighborhood information can be used to resolve many ambiguities in orthology inference. Here we present OrthoGNC, a software for accurately predicting pairwise orthology relations based on gene neighborhood conservation. Analyses on simulated and real data reveal the high accuracy of OrthoGNC. In addition to orthology detection, OrthoGNC can be employed to investigate the conservation of genomic context among potential orthologs detected by other methods. OrthoGNC is freely available online at http://bs.ipm.ir/softwares/orthognc and http://tinyurl.com/orthoGNC.</p>
<p>http://www.comp.nus.edu.sg/~wongls/projects/orthoGNC/</p>
</div><p>Address of the bookmark: <a href="http://www.sciencedirect.com/science/article/pii/S1672022917301663" rel="nofollow">http://www.sciencedirect.com/science/article/pii/S1672022917301663</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/8317/new-version-of-modeller-913</guid>
	<pubDate>Thu, 13 Feb 2014 09:07:57 -0600</pubDate>
	<link>https://bioinformaticsonline.com/news/view/8317/new-version-of-modeller-913</link>
	<title><![CDATA[New version of Modeller, 9.13]]></title>
	<description><![CDATA[<p>The new version of Modeller, 9.13, is now available for download! Please see the download page at <a href="http://www.facebook.com/l.php?u=http%3A%2F%2Fsalilab.org%2Fmodeller%2F&amp;h=mAQG5wo_Z&amp;enc=AZOoq2B7BxT95AT3Mw3za3VlbmRFke43YMI5vAjCAbBlIcf3bptn8pmFC1Idxrssy98117S03IgdcNmEWcQBi9bmi8Or_ut1D1yybt1ZonvPoCT3_LOglcYV7o6bEaa442_6LhbjefEaelkq0aq6dl0w&amp;s=1" target="_blank">http://salilab.org/modeller/</a> for more information.</p><p><img src="http://salilab.org/modeller/gifs/modeller.jpg" alt="image" width="848" height="272" style="border: 0px; border: 0px;"><br /> <br /> If you have a license key for Modeller 8 or 9, there is no need to reregister for Modeller 9.13 - the same license key will work. (It won't <span>do any harm to reregister if you want to, though!)<br /> <br /> 9.13 is primarily a bugfix release relative to the last public release(9.12). Major user-visible changes include:<br /> <br /> # Modeller now includes a variety of SOAP (statistically optimized atomic potential) scores for assessing proteins, loops, and interfaces.<br /> <br /> # The Lennard-Jones interaction energy is now artificially truncated at very short distance; this makes simulations with poor starting conditions much less likely to 'blow up'.<br /> <br /> # model.get_insertions(), model.get_deletions() and model.loops() now have an include_termini option; if False, residue ranges that include chain termini are excluded from the output.<br /> <br /> See the Modeller manual for a full change log: <a href="http://salilab.org/modeller/9.13/manual/node39.html" target="_blank">http://salilab.org/modeller/9.13/manual/node39.html</a><br /> <br /> If you encounter bugs in Modeller 9.13, please see <a href="http://salilab.org/modeller/9.13/manual/node10.html" target="_blank">http://salilab.org/modeller/9.13/manual/node10.html</a> for information on how to report them.</span></p><p><span>Reference:</span></p><p><span>http://salilab.org/modeller/</span></p>]]></description>
	<dc:creator>Radha Agarkar</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/fun/view/8509/the-best-bioinformatics-computational-biology-quotes</guid>
	<pubDate>Wed, 26 Feb 2014 17:50:59 -0600</pubDate>
	<link>https://bioinformaticsonline.com/fun/view/8509/the-best-bioinformatics-computational-biology-quotes</link>
	<title><![CDATA[The Best Bioinformatics / Computational Biology Quotes]]></title>
	<description><![CDATA[<p><img src="http://bioinformaticsonline.com/mod//photo/hahaha.png" style="border: 0; border: 0px;" alt="image"></p><p>Bioinformatician are not anti-social; We are just genome friendly.</p><p>Bioinformatician would love to change the biological world, but they won't give us the genetic code :P</p><p>If at first you don't succeed; call it version 1.0</p><p>The glass is neither half-full nor half-empty: it's actually have several genomes.</p><p>I'm BioGeek.</p><p>Fedup with LIPS, try God script.</p><p>Idiot, Go ahead, make my data!</p><p>Thank god, my genome just compiled.</p><p>Error message: "Out of space on genome drive:"</p><p>Shut up mobile elements, or i'll flush you out.</p><p>Never underestimate the internet bandwidth, u gotta incomplete.</p><p>Applied fuzzy logic to understand God's logic?</p><p>Warning! Overflow, delete chromosome !</p><p>Be nice to the BioGeek, for all you know they might be the next curator!</p><p>Beware of computational biologist they screw genes and protein.</p><p>Warning! Your genome is full of garbage, delete it !</p><p>Bad or missing mouse genome. Spank the cat? (Y/N)</p><p>Genome make very fast, very accurate mistakes.</p><p>Let's BLAST it.</p><p>Some genome never has transposons. It just develops random features.</p><p>Go watch CINEMA and have BLAST.</p>]]></description>
	<dc:creator>Jit</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41678/gridss-the-genomic-rearrangement-identification-software-suite</guid>
	<pubDate>Sun, 17 May 2020 10:27:44 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41678/gridss-the-genomic-rearrangement-identification-software-suite</link>
	<title><![CDATA[GRIDSS: the Genomic Rearrangement IDentification Software Suite]]></title>
	<description><![CDATA[<p>GRIDSS is a module software suite containing tools useful for the detection of genomic rearrangements. GRIDSS includes a genome-wide break-end assembler, as well as a structural variation caller for Illumina sequencing data. GRIDSS calls variants based on alignment-guided positional de Bruijn graph genome-wide break-end assembly, split read, and read pair evidence.</p><p>Address of the bookmark: <a href="https://github.com/PapenfussLab/gridss" rel="nofollow">https://github.com/PapenfussLab/gridss</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/8987/the-dna-of-a-successful-bioinformatician-decoded</guid>
	<pubDate>Wed, 12 Mar 2014 13:41:26 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/8987/the-dna-of-a-successful-bioinformatician-decoded</link>
	<title><![CDATA[The DNA of a Successful Bioinformatician decoded !!!]]></title>
	<description><![CDATA[<p>Many blogs exist about successful bioinformatician, but this blog so far now is my personal view on characteristics of successful bioinformatician or computational biologist. &nbsp;Hmm &hellip; of course these views are subjective to my own personal experiences and therefore I don't claim that the view listed here is complete. As a human, I don&rsquo;t take them too serious. The success must not be the only target of your work. The target is to work on your own virtues; some of those virtues are the topic of this blog.</p><p><img src="http://bioinformaticsonline.com/mod/photo/genome_decode.png" alt="image" width="509" height="458" style="border: 0px; border: 0px;"><br /> <br /> <strong>1. Update new things continuously<br /></strong>As per my personal experience, it&rsquo;s not always easy to work as a bioinformatician! &nbsp;There are couple of reasons to say that; First computational part of biology make our life&rsquo;s a little harder compared to other professional categories. The fact - for instance - that the technology cycle in the bioinformatics world is very short, the actual knowledge becomes outdated in a few months or years. Therefore, we need to learn continuously - new things get important. Second, to stay on top of things we really need the strong will to be good at our job. That's probably the most important characteristic to bioinformatician. They are usually an excellent knowledge worker with great technical abilities, and have the will to be that over decades!<br /> <br /> <strong>2. Avoid the sentence </strong><strong>"I did not know what to do!"</strong><br /> In our computational biology lab, we generally face lots of technical problems. But as you know, it's impossible to know everything to do the computational biology jobs ( Yup.. because you need diverse and multidisciplinary knowledge to understand biological problems and resolve their respective solutions), therefore it's absolutely necessary that a bioinformatician finds its way through a new topic. How I typically do that is I use google and I talk to other experts in our laboratory or online biostar community to find out what they think. "I did not know what to do!" should not be an argument for us.<strong><br /><br /> <strong>3. To make oneself useful</strong></strong><br /> Several time it does happen, you finished our task earlier than expected; in such cases if you have some time left then: Take a coffee and play chess; reversi, etc. In my case I take a rest. Afterwards I think about what I could do that helps the team to achieve its targets, 'cause some of my team mates probably didn't finish! (at least if I didn't met them at coffee bar !!)</p><p><strong>4. Care for all</strong><br /> During my rigorous research duration; I attended several workshop organized by my University departments. I had a discussion with other research fellow, professors; I generally ask &hellip; what it really takes to make a team successful or to be a successful research leader. They always said: "Well, you need some caring people!" I think there is a lot truth in that statement. If we do not care about quality, timelines, good team culture, respectful communication (!!), clean code, if all this doesn&rsquo;t matter to us, then I believe the probability is higher that we fail in research and analysis. <br /> <br /> <strong>5. Be good with people</strong><br /> Because bioinformatician and computational biologist jobs typically involves to work in a (most wanted J cross-departmental!) team, therefore it's important that we're (more or less) good in dealing with other individuals. Everyone have their own strengths and weaknesses, just like us. It's important to treat all the research team mates with respect, regardless of their technical competence or contributions. Of course, sometimes people deserve a clear statement (!!!), but try to do these things one-on-one. Make sure nobody loses his face. Attend the meetings at the coffee bar; be good at table top soccer and go out once in a while to have a beer with your team. You know what I'm talking about.</p><p>At the end of a week I look back and I ask myself what I have produced. This could be paperwork, community days or (best!!) programming code. Always remember there is always a solution to a problem. Most of the times there are at least three solutions. So, don&rsquo;t just blame, suggest a solution.<br /> <br /> That's it. I am looking forward to your thoughts and comments!</p>]]></description>
	<dc:creator>Jit</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/33842/awesome-perl-frameworks-libraries-and-software-part-5</guid>
	<pubDate>Fri, 07 Jul 2017 04:12:47 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/33842/awesome-perl-frameworks-libraries-and-software-part-5</link>
	<title><![CDATA[Awesome perl frameworks, libraries and software - PART 5]]></title>
	<description><![CDATA[<ul>
<li><a href="https://github.com/robelix/sub2srt">robelix/sub2srt</a>&nbsp;- subtitle converter</li>
<li><a href="https://github.com/reyjrar/graphite-scripts">reyjrar/graphite-scripts</a>&nbsp;- A Collections of Scripts for Working with Graphite</li>
<li><a href="https://github.com/regilero/check_nginx_status">regilero/check_nginx_status</a>&nbsp;- Nagios check for nginx status report</li>
<li><a href="https://github.com/omniti-labs/resmon">omniti-labs/resmon</a>&nbsp;- resmon</li>
<li><a href="https://github.com/motemen/App-htmlcat">motemen/App-htmlcat</a>&nbsp;- redirect stdin to web browser</li>
<li><a href="https://github.com/moose/Moo">moose/Moo</a>&nbsp;- Minimalist Object Orientation (with Moose compatibility)</li>
<li><a href="https://github.com/miyagawa/fastpass">miyagawa/fastpass</a>&nbsp;- Tiny, XS free, standalone and preforking FastCGI daemon for PSGI</li>
<li><a href="https://github.com/miyagawa/Filesys-Notify-Simple">miyagawa/Filesys-Notify-Simple</a>&nbsp;- Simple and dumb file system watcher</li>
<li><a href="https://github.com/mhop/fhem-mirror">mhop/fhem-mirror</a>&nbsp;- Branch 'master' is a read-only-mirror of svn://svn.code.sf.net/p/fhem/code which is updated once a day. On branch 'enocean' I am going to add some Enocean-Devices</li>
<li><a href="https://github.com/lopnor/Plack-App-DAV">lopnor/Plack-App-DAV</a>&nbsp;- simple DAV server for Plack</li>
<li><a href="https://github.com/kazuho/url_compress">kazuho/url_compress</a>&nbsp;- a static PPM-based URL compressor / decompressor</li>
<li><a href="https://github.com/jnthn/6model">jnthn/6model</a>&nbsp;- Just a place that I'm keeping some meta-model prototyping; anything that matters will make it to another repo (e.g. nqp-rx one or Rakudo one) at some point.</li>
<li><a href="https://github.com/jasonhancock/nagios-puppetdb">jasonhancock/nagios-puppetdb</a>&nbsp;- Nagios plugins and pnp4nagios templates related to Puppetlab's PuppetDB project.</li>
<li><a href="https://github.com/goccy/p5-Compiler-Parser">goccy/p5-Compiler-Parser</a>&nbsp;- Create Abstract Syntax Tree for Perl5</li>
<li><a href="https://github.com/cgutteridge/Grinder">cgutteridge/Grinder</a>&nbsp;- Create RDF data from spreadsheets or CSV</li>
<li><a href="https://github.com/c9s/Plack-Middleware-OAuth">c9s/Plack-Middleware-OAuth</a>&nbsp;- Plack Middleware for OAuth1 and OAuth2</li>
<li><a href="https://github.com/bzip2-cuda/bzip2-cuda">bzip2-cuda/bzip2-cuda</a>&nbsp;- Parallel implementation of bzip2 using cuda</li>
<li><a href="https://github.com/alanstevens/ChocoPackages">alanstevens/ChocoPackages</a>&nbsp;- Chocolatey Nuget Packages</li>
<li><a href="https://github.com/SoylentNews/slashcode">SoylentNews/slashcode</a>&nbsp;- The slashcode repository for SoylentNews. The initial code base was uploaded as it appeared on Sourceforge as of the last commit in September 2009</li>
<li><a href="https://github.com/Miserlou/XSS-Harvest">Miserlou/XSS-Harvest</a>&nbsp;- XSS Weaponization</li>
</ul>]]></description>
	<dc:creator>Neel</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36019/ewas-epigenome-wide-association-study-software-20</guid>
	<pubDate>Wed, 21 Mar 2018 18:14:00 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36019/ewas-epigenome-wide-association-study-software-20</link>
	<title><![CDATA[EWAS: epigenome-wide association study software 2.0]]></title>
	<description><![CDATA[<p><span>EWAS2.0 can analyze EWAS data and identify the association between epigenetic variations and disease/phenotype. On the basis of EWAS1.0, we have added more distinctive features. EWAS2.0 software was developed based on our &ldquo;population epigenetic framework&rdquo; and can perform: (1) epigenome-wide single marker association study; (2) epigenome-wide methylation haplotype (meplotype) association study; and (3) epigenome-wide association meta-analysis.</span></p><p>Address of the bookmark: <a href="http://www.bioapp.org/ewas/" rel="nofollow">http://www.bioapp.org/ewas/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/9204/keep-your-important-ssh-session-running-when-you-disconnect-from-server</guid>
	<pubDate>Sat, 15 Mar 2014 21:39:17 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/9204/keep-your-important-ssh-session-running-when-you-disconnect-from-server</link>
	<title><![CDATA[Keep Your Important SSH Session Running when You Disconnect from Server !!!]]></title>
	<description><![CDATA[<p>As a Bioinformatician/ Computational biologist we swim in the ocean of genomic/proteomics data, and play with them with an ease. In our day to day simulation, analysis, comparative study we do need to run exhaustive programs, which might take more than a week. In such cases we do need to disconnect from sever in a way that our program/session should not get terminated. To do so there are lots of software, tools such as tmux ( <a href="http://tmux.sourceforge.net/">http://tmux.sourceforge.net/</a>, nohup (<a href="http://ss64.com/bash/nohup.html">http://ss64.com/bash/nohup.html</a>) , byobu (<a href="https://help.ubuntu.com/10.04/serverguide/byobu.html">https://help.ubuntu.com/10.04/serverguide/byobu.html</a>) and other commands (disown -a &amp;&amp; exit), but following are the ones I use the most.</p><p>Screen is like a window manager for your console. It will allow you to keep multiple terminal sessions running and easily switch between them. It also protects you from disconnection, because the screen session doesn&rsquo;t end when you get disconnected.<br /><br />You&rsquo;ll need to make sure that screen is installed on the server you are connecting to. If that server is Ubuntu or Debian, just use this command:<br /><br />sudo apt-get install screen<br /><br />Now you can start a new screen session by just typing screen at the command line. You&rsquo;ll be shown some information about screen. Hit enter, and you&rsquo;ll be at a normal prompt.<br /><br /><strong>To disconnect (but leave the session running)</strong><br /><br />Hit Ctrl + A and then Ctrl + D in immediate succession. You will see the message [detached]<br /><br /><strong>To reconnect to an already running session</strong><br /><br />screen -r<br /><br /><strong>To reconnect to an existing session, or create a new one if none exists</strong><br /><br />screen -D -r<br /><br /><strong>To create a new window inside of a running screen session</strong><br /><br />Hit Ctrl + A and then C in immediate succession. You will see a new prompt.<br /><br /><strong>To switch from one screen window to another</strong><br /><br />Hit Ctrl + A and then Ctrl + A in immediate succession.<br /><br /><strong>To list open screen windows</strong><br /><br />Hit Ctrl + A and then W in immediate succession</p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/9242/check-the-size-of-a-directory-free-disk-space</guid>
	<pubDate>Mon, 17 Mar 2014 02:35:32 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/9242/check-the-size-of-a-directory-free-disk-space</link>
	<title><![CDATA[Check the Size of a directory &amp; Free disk space.]]></title>
	<description><![CDATA[<p>The amount of databases we bioinformatician deal are just HUGE &hellip; In such cases, we always need to check our server for free spaces etc. I planned this article to explains 2 simple commands that most bioinformatician want to know when they start using Linux / BioLinux. First: Size of a directory (du) and and second: free disk space that exists on your machine (df).</p><p><br /><strong>'du' &ndash; Check the size of a directory</strong></p><p><br />$ du<br />This command ( du) gives you a list of directories that exist in the current working directory along with their sizes in kilobytes (default). The last line of the output gives you the total size of the current directory including its subdirectories. <br /><br />$ du /home/jin1<br />The above command would give you the directory size of the directory /home/david<br /><br />$ du -h<br />The same &ldquo;du&rdquo;command with some flag gives you a better output than the default one. The option '-h' stands for human readable format. Therefore, in order to print the sizes of the files / directories in your desire notation use this time suffixed with a 'k' if its kilobytes and 'M' if its Megabytes and 'G' if its Gigabytes.<br /><br />$ du -ah<br />If you are interested in checking everything present in a folder use above mentioned command. It gives us not only the directories but also all the files that are present in the current directory. The &ldquo;-a&rdquo; flag displays the filenames along with the directory names in the output. <br /><br />$ du -c<br />This gives you a grand total as the last line of the output. So if your directory occupies 30MB the last 2 lines of the output would be 30M.<br /><br />$ du -s<br />Use this command to displays a summary of the directory size. It is the simplest way to know the total size of the current directory.<br /><br />$ du -S<br />This would display the size of the current directory excluding the size of the subdirectories that exist within that directory. So it basically shows you the total size of all the files that exist in the current directory.<br /><br />$ du --exculde=mp3<br />Several times it required to exclude some directory in our size calculation. In such cases the above command would display the size of the current directory along with all its subdirectories, but it would exclude all the files having the given pattern present in their filenames.</p><p><br /><strong>'df' - finding the disk free space / disk usage</strong><br /><br />$ df<br />Hmmm &hellip; now &ldquo;df&rdquo; command is really useful, and I guess you are going to use it over time. Typing the above command, outputs a table consisting of 6 columns. All the columns are very easy to understand. Remember that the 'Size', 'Used' and 'Avail' columns use kilobytes as the unit. The 'Use%' column shows the usage as a percentage which is also very useful.<br /><br />$ df -h<br />Displays the same output as the previous command but the '-h' indicates human readable format. Hence instead of kilobytes as the unit the output would have 'M' for Megabytes and 'G' for Gigabytes.<br /><br />Example: Linux installed on /dev/hda1<br />$ df -h | grep /dev/hda1</p><p><br />All right, this is not the only option to check the sizes and free spaces but there are a few more options that can be used with 'du' and 'df' . I will discuss it later.<br /><br /></p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42160/vicuna-a-software-tool-that-enables-consensus-assembly-of-ultra-deep-sequence-derived-from-diverse-viral-or-other-heterogeneous-populations</guid>
	<pubDate>Tue, 25 Aug 2020 03:40:17 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42160/vicuna-a-software-tool-that-enables-consensus-assembly-of-ultra-deep-sequence-derived-from-diverse-viral-or-other-heterogeneous-populations</link>
	<title><![CDATA[VICUNA: a software tool that enables consensus assembly of ultra-deep sequence derived from diverse viral or other heterogeneous populations.]]></title>
	<description><![CDATA[<p><span>VICUNA</span><span>&nbsp;is a&nbsp;</span><em>de novo</em><span>&nbsp;assembly program targeting populations with high mutation rates. It creates a single linear representation of the mixed population on which intra-host variants can be mapped. For clinical samples rich in contamination (e.g., &gt;95%), VICUNA can leverage existing genomes, if available, to assemble only target-alike reads. After initial assembly, it can also use existing genomes to perform guided merging of contigs. For each data set (e.g., Illumina paired read, 454), VICUNA outputs consensus sequence(s) and the corresponding multiple sequence alignment of constituent reads. VICUNA efficiently handles ultra-deep sequence data with tens of thousands fold coverage.</span></p>
<p><a href="http://software.broadinstitute.org/viral/docs/vicuna_v1.0.pdf">http://software.broadinstitute.org/viral/docs/vicuna_v1.0.pdf</a></p><p>Address of the bookmark: <a href="https://www.broadinstitute.org/viral-genomics/vicuna" rel="nofollow">https://www.broadinstitute.org/viral-genomics/vicuna</a></p>]]></description>
	<dc:creator>biogeek</dc:creator>
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