<?xml version='1.0'?><rss version="2.0" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:georss="http://www.georss.org/georss" xmlns:atom="http://www.w3.org/2005/Atom" >
<channel>
	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/26303?offset=970</link>
	<atom:link href="https://bioinformaticsonline.com/related/26303?offset=970" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/39881/apollo-a-sequence-annotation-editor</guid>
	<pubDate>Tue, 27 Aug 2019 08:08:47 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/39881/apollo-a-sequence-annotation-editor</link>
	<title><![CDATA[Apollo: a sequence annotation editor]]></title>
	<description><![CDATA[<p><span>The well-established inaccuracy of purely computational methods for annotating genome sequences necessitates an interactive tool to allow biological experts to refine these approximations by viewing and independently evaluating the data supporting each annotation. Apollo was developed to meet this need, enabling curators to inspect genome annotations closely and edit them</span></p><p>Address of the bookmark: <a href="https://genomebiology.biomedcentral.com/articles/10.1186/gb-2002-3-12-research0082" rel="nofollow">https://genomebiology.biomedcentral.com/articles/10.1186/gb-2002-3-12-research0082</a></p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42035/pannzer-a-fully-automated-service-for-functional-annotation-of-prokaryotic-and-eukaryotic-proteins-of-unknown-function</guid>
	<pubDate>Thu, 13 Aug 2020 09:57:24 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42035/pannzer-a-fully-automated-service-for-functional-annotation-of-prokaryotic-and-eukaryotic-proteins-of-unknown-function</link>
	<title><![CDATA[PANNZER: a fully automated service for functional annotation of prokaryotic and eukaryotic proteins of unknown function.]]></title>
	<description><![CDATA[<p><strong>PANNZER</strong>&nbsp;(Protein ANNotation with Z-scoRE) is a fully automated service for functional annotation of prokaryotic and eukaryotic proteins of unknown function.</p>
<p><strong>PANNZER</strong>&nbsp;(Protein ANNotation with Z-scoRE) is a fully automated service for functional annotation of prokaryotic and eukaryotic proteins of unknown function. The tool is designed to predict the functional description (DE) and GO classes.</p>
<p>PANNZER2 processes bacterial proteomes in minutes and eukaryotic proteomes in an hour. You can use&nbsp;<a href="http://ekhidna2.biocenter.helsinki.fi/AAI/">AAI-profiler</a>&nbsp;to summarize a proteome's species neighbors and reveal taxonomic identity or contamination.</p><p>Address of the bookmark: <a href="http://ekhidna2.biocenter.helsinki.fi/sanspanz/#" rel="nofollow">http://ekhidna2.biocenter.helsinki.fi/sanspanz/#</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43254/quasr-quantification-and-annotation-of-short-reads-in-r</guid>
	<pubDate>Fri, 13 Aug 2021 07:44:05 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43254/quasr-quantification-and-annotation-of-short-reads-in-r</link>
	<title><![CDATA[QuasR: Quantification and annotation of short reads in R]]></title>
	<description><![CDATA[<p>The <em><a href="https://bioconductor.org/packages/3.14/QuasR">QuasR</a></em> package (short for <em>Qu</em>antify and <em>a</em>nnotate <em>s</em>hort reads in <em>R</em>) integrates the functionality of several <strong>R</strong> packages (such as <em><a href="https://bioconductor.org/packages/3.14/IRanges">IRanges</a></em> <span>(Lawrence et al. 2013)</span> and <em><a href="https://bioconductor.org/packages/3.14/Rsamtools">Rsamtools</a></em>) and external software (e.g.&nbsp;<code>bowtie</code>, through the <em><a href="https://bioconductor.org/packages/3.14/Rbowtie">Rbowtie</a></em> package, and <code>HISAT2</code>, through the <em><a href="https://bioconductor.org/packages/3.14/Rhisat2">Rhisat2</a></em> package). The package aims to cover the whole analysis workflow of typical high throughput sequencing experiments, starting from the raw sequence reads, over pre-processing and alignment, up to quantification. A single <strong>R</strong> script can contain all steps of a complete analysis, making it simple to document, reproduce or share the workflow containing all relevant details.</p><p>Address of the bookmark: <a href="https://www.bioconductor.org/packages/devel/bioc/vignettes/QuasR/inst/doc/QuasR.html" rel="nofollow">https://www.bioconductor.org/packages/devel/bioc/vignettes/QuasR/inst/doc/QuasR.html</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/33219/dbcan-a-web-server-and-database-for-automated-carbohydrate-active-enzyme-annotation</guid>
	<pubDate>Mon, 29 May 2017 05:39:29 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/33219/dbcan-a-web-server-and-database-for-automated-carbohydrate-active-enzyme-annotation</link>
	<title><![CDATA[dbCAN: a web server and DataBase for automated Carbohydrate-active enzyme ANnotation]]></title>
	<description><![CDATA[<p><a href="http://csbl.bmb.uga.edu/dbCAN/index.php">dbCAN</a>&nbsp;is a web server and&nbsp;<span style="text-decoration: underline;">D</span>ata<span style="text-decoration: underline;">B</span>ase for&nbsp;<a href="http://csbl.bmb.uga.edu/dbCAN/annotate.php"><strong>automated&nbsp;<span style="text-decoration: underline;">C</span>arbohydrate-active enzyme&nbsp;<span style="text-decoration: underline;">AN</span>notation</strong></a>, funded by the&nbsp;<a href="http://bioenergycenter.org/">BioEnergy Science Center of the DOE</a>. Similar resources on the web include&nbsp;<a href="http://www.cazy.org/" target="_blank">CAZy database</a>&nbsp;and&nbsp;<a href="http://cricket.ornl.gov/cgi-bin/cat.cgi" target="_blank">CAT</a>. All data in dbCAN are generated based on the family classification from&nbsp;<a href="http://www.cazy.org/" target="_blank">CAZy database</a>&nbsp;while it has the following&nbsp;<strong><span style="text-decoration: underline;">unique features</span></strong>&nbsp;compared with CAZy database and CAT:</p>
<ul>
<li>dbCAN provides the capability of&nbsp;<a href="http://csbl.bmb.uga.edu/dbCAN/annotate.php">automated and comprehensive CAZyme annotation</a>&nbsp;of a given genome submitted by the user;</li>
<li>dbCAN provides an explicitly defined&nbsp;<span style="text-decoration: underline;">signature domain</span>&nbsp;for each and every CAZyme family along with its location in all the relevant full-length CAZyme proteins in all sequenced&nbsp;<a href="http://csbl.bmb.uga.edu/dbCAN/genome.php">genomes</a>;</li>
<li>dbCAN provides the most complete set of&nbsp;<span style="text-decoration: underline;">metagenomic CAZyme</span>&nbsp;genes published so far and represents the first step towards discovering novel CAZyme catalysts in metagenomes;</li>
<li>dbCAN provides a&nbsp;<span style="text-decoration: underline;">subfamily classification</span>&nbsp;of the existing CAZyme families based on sequence similarities;</li>
<li>dbCAN make all pre-computed data freely available to the public, including sequence alignments,&nbsp;<a href="http://csbl.bmb.uga.edu/dbCAN/download/">hidden markov models (HMMs)</a>&nbsp;and phylogenies of the signature domain regions in each and every CAZyme family and subfamily.</li>
</ul>
<p><a href="http://csbl.bmb.uga.edu/dbCAN/help.php">dbCAN</a>&nbsp;is updated regularly when&nbsp;<a href="http://www.cazy.org/" target="_blank">CAZy database</a>&nbsp;created new families based on latest literature.</p><p>Address of the bookmark: <a href="http://csbl.bmb.uga.edu/dbCAN/index.php" rel="nofollow">http://csbl.bmb.uga.edu/dbCAN/index.php</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36456/alpaca-a-hybrid-strategy-for-assembly-of-genomic-dna-shotgun-sequencing-reads</guid>
	<pubDate>Mon, 30 Apr 2018 04:38:40 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36456/alpaca-a-hybrid-strategy-for-assembly-of-genomic-dna-shotgun-sequencing-reads</link>
	<title><![CDATA[ALPACA: A hybrid strategy for assembly of genomic DNA shotgun sequencing reads.]]></title>
	<description><![CDATA[<p><span>ALPACA requires Celera Assembler 8.3 or later. It is recommended to build Celera Assembler from source. (Why? The pre-built binaries CA_8.3rc1 and CA8.3rc2 will work for any large data set.&nbsp;</span></p>
<p><span>Detail paper at&nbsp;https://bmcgenomics.biomedcentral.com/articles/10.1186/s12864-017-3927-8</span></p><p>Address of the bookmark: <a href="https://github.com/VicugnaPacos/ALPACA" rel="nofollow">https://github.com/VicugnaPacos/ALPACA</a></p>]]></description>
	<dc:creator>Seema Singh</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36865/perga-a-paired-end-read-guided-de-novo-assembler-for-extending-contigs-using-svm-and-look-ahead-approach</guid>
	<pubDate>Tue, 05 Jun 2018 09:57:11 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36865/perga-a-paired-end-read-guided-de-novo-assembler-for-extending-contigs-using-svm-and-look-ahead-approach</link>
	<title><![CDATA[PERGA: A Paired-End Read Guided De Novo Assembler for Extending Contigs Using SVM and Look Ahead Approach]]></title>
	<description><![CDATA[PERGA - Paired End Reads Guided Assembler

PERGA is a novel sequence reads guided de novo assembly approach which adopts greedy-like prediction strategy for assembling reads to contigs and scaffolds. Instead of using single-end reads to construct contig, PERGA uses paired-end reads and different read overlap sizes from O ≥ Omax to Omin to resolve the gaps and branches. Moreover, by constructing a decision model using machine learning approach based on branch features, PERGA can determine the correct extension in 99.7% of cases. PERGA will try to extend the contigs by all feasible nucleotides and determine if these multiple extensions due to sequencing errors or repeats by using looking ahead technology, and it also try to separate the different repeats of nearby genomic regions to make the assembly result more longer and accurate.

The simulated E.coli paired-end reads data are generated using GemSim (KE McElroy, F Luciani, T Thomas. Gemsim: General, Error-Model Based Simulator of Next-Generation Sequencing Data. BMC Genomics 2012, 13:74), with coverage 50x, 60x, 100x, read lengths 100-bp, and can be downloaded from https://github.com/zhuxiao/data_PERGA.<p>Address of the bookmark: <a href="https://github.com/hitbio/PERGA" rel="nofollow">https://github.com/hitbio/PERGA</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37221/asplice-a-scalable-and-memory-efficient-algorithm-for-de-novo-transcriptome-assembly</guid>
	<pubDate>Tue, 03 Jul 2018 04:09:46 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37221/asplice-a-scalable-and-memory-efficient-algorithm-for-de-novo-transcriptome-assembly</link>
	<title><![CDATA[ASplice: a scalable and memory-efficient algorithm for de novo transcriptome assembly]]></title>
	<description><![CDATA[With increased availability of de novo assembly algorithms, it is feasible to study entire transcriptomes of non-model organisms. While algorithms are available that are specifically designed for performing transcriptome assembly from high-throughput sequencing data, they are very memory-intensive, limiting their applications to small data sets with few libraries.

Texas A&amp;M University researchers develop a transcriptome assembly algorithm that recovers alternatively spliced isoforms and expression levels while utilizing as many RNA-Seq libraries as possible that contain hundreds of gigabases of data. New techniques are developed so that computations can be performed on a computing cluster with moderate amount of physical memory.

Availability – A software program that implements the algorithm is available at: http://faculty.cse.tamu.edu/shsze/asplice.

Sze SH, Pimsler ML, Tomberlin JK, Jones CD, Tarone AM. (2017) A scalable and memory-efficient algorithm for de novo transcriptome assembly of non-model organisms. BMC Genomics 18(Suppl 4):387.<p>Address of the bookmark: <a href="http://faculty.cse.tamu.edu/shsze/asplice/" rel="nofollow">http://faculty.cse.tamu.edu/shsze/asplice/</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37554/finishersca-repeat-aware-tool-for-upgrading-de-novo-assembly-using-long-reads</guid>
	<pubDate>Mon, 20 Aug 2018 04:08:50 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37554/finishersca-repeat-aware-tool-for-upgrading-de-novo-assembly-using-long-reads</link>
	<title><![CDATA[FinisherSC:a repeat-aware tool for upgrading de novo assembly using long reads]]></title>
	<description><![CDATA[<p><br>Here is the command to run the tool:</p>
<pre><code>python finisherSC.py destinedFolder mummerPath
</code></pre>
<p>If you are running on server computer and would like to use multiple threads, then the following commands can generate 20 threads to run FinisherSC.</p>
<pre><code>python finisherSC.py -par 20 destinedFolder mummerPath
</code></pre>
<p>Sometimes, if the names of raw reads and contigs consists of special characters/formats, FinisherSC/MUMmer may not parse them correctly. In that case, you want to have a quick renaming of the names of contigs/reads in contigs.fasta or raw_reads.fasta using the following command.</p>
<pre><code>    perl -pe 's/&gt;[^\$]*$/"&gt;Seg" . ++$n ."\n"/ge' raw_reads.fasta &gt; newRaw_reads.fasta
    cp newRaw_reads.fasta raw_reads.fasta
    perl -pe 's/&gt;[^\$]*$/"&gt;Seg" . ++$n ."\n"/ge' contigs.fasta &gt; newContigs.fasta
    cp newContigs.fasta contigs.fasta</code></pre><p>Address of the bookmark: <a href="https://github.com/kakitone/finishingTool" rel="nofollow">https://github.com/kakitone/finishingTool</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/29479/how-to-install-perl-modules-on-mac-os-x-in-easy-steps</guid>
	<pubDate>Thu, 20 Oct 2016 07:26:29 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/29479/how-to-install-perl-modules-on-mac-os-x-in-easy-steps</link>
	<title><![CDATA[How to install Perl modules on Mac OS X in easy steps !!]]></title>
	<description><![CDATA[<p>Today at work, I learned how to install Perl modules using&nbsp;<a href="http://en.wikipedia.org/wiki/CPAN">CPAN</a>. It&rsquo;s a lot easier than I thought.</p><p>You see, for the past couple of years, I&rsquo;ve been a bit frustrated because OS X does not come with a whole lot of Perl modules pre-installed, and for all I googled, I couldn&rsquo;t find an &ldquo;idiot&rsquo;s&rdquo; guide for moderately-savvy-but-not-expert users like myself to install modules and dependencies on demand.</p><p>The only instructions I could find point to&nbsp;<a href="http://fink.sourceforge.net/">Fink</a>, which basically installs modules in a path that isn&rsquo;t included in the Perl @INC variable, meaning you have to manually specify the full path to the modules in every script &mdash; which is not a lot of fun if you&rsquo;re developing on OS X and deploying on Red Hat, for instance.</p><p>Moreover, Fink doesn&rsquo;t seem to make every module available, and it&rsquo;s not very easy to determine which Fink package you need to install if you need a particular module.</p><p>So, with a script that called on several apparently unavailable modules, and a deadline looming, I finally decided to suck it up and figure out how to use CPAN to install them:</p><h4>1) Make sure you have the Apple Developer Tools (XCode) installed.</h4><p>These are on one of your install discs, or available as a huge but free download from the&nbsp;<a href="https://developer.apple.com/xcode/">Apple Developer Connection</a>&nbsp;[free registration required] or the Mac App Store. I thought I had them, but apparently when we upgraded that computer to Tiger, they went missing.</p><p>If you don&rsquo;t have this stuff installed, your installation will fail with errors about unavailable commands.</p><h4>1.5) Install Command Line Tools (Recent XCode versions only)</h4><p>(Thank you to Tom Marchioro for informing me about this step.)</p><p>Older versions of XCode installed the command line tools (which are required to properly install CPAN modules) by default, but apparently newer ones do not. To check whether you have the command line tools already installed, run the following from the Terminal:</p><p><code>$ which make</code></p><p>This command checks the system for the &ldquo;<code>make</code>&rdquo; tool. If it spits out something like&nbsp;<code>/usr/bin/make</code>&nbsp;you&rsquo;re golden and can skip ahead to Step 2. If you just get a new prompt and no output, you&rsquo;ll need to install the tools:</p><ol>
<li>Launch XCode and bring up the Preferences panel.</li>
<li>Click on the Downloads tab</li>
<li>Click to install the Command Line Tools</li>
</ol><p>If you like, you can run&nbsp;<code>which make</code>&nbsp;again to confirm that everything&rsquo;s installed correctly.</p><h4>2) Configure CPAN.</h4><p><code>$ sudo perl -MCPAN -e shell</code></p><p><code>perl&gt; o conf init</code></p><p>This will prompt you for some settings. You can accept the defaults for almost everything (just hit &ldquo;return&rdquo;). The two things you must fill in are the path to&nbsp;<code>make</code>&nbsp;(which should be&nbsp;<code>/usr/bin/make</code>&nbsp;or the value returned when you run&nbsp;<code>which make</code>&nbsp;from the command line) and your choice of CPAN mirrors (which you actually choose don&rsquo;t really matter, but it won&rsquo;t let you finish until you select at least one). If you use a proxy or a very restrictive firewall, you may have to configure those settings as well.</p><p>If you skip Step 2, you may get errors about&nbsp;<code>make</code>&nbsp;being unavailable.</p><h4>3) Upgrade CPAN</h4><p><code>$ sudo perl -MCPAN -e 'install Bundle::CPAN'</code></p><p>Don&rsquo;t forget the&nbsp;<code>sudo</code>, or it&rsquo;ll fail with permissions errors, probably when doing something relatively unimportant like installing&nbsp;<code>man</code>&nbsp;files.</p><p>This will spend a long time downloading, testing, and compiling various files and dependencies. Bear with it. It will prompt you a few times about dependencies. You probably want to enter &ldquo;yes&rdquo;. I agreed to everything it asked me, and everything turned out fine. YMMV of course. If everything installs properly, it&rsquo;ll give you an &ldquo;OK&rdquo; at the end.</p><h4>4) Install your modules. For each module&hellip;.</h4><p><code>$ sudo perl -MCPAN -e 'install Bundle::Name'</code></p><p>or</p><p><code>$ sudo perl -MCPAN -e 'install Module::Name'</code></p><p>This will install the module&nbsp;<em>and</em>&nbsp;its dependencies. Nice, eh? Again, don&rsquo;t forget the&nbsp;<code>sudo</code>.</p><p>The first time you run this after upgrading CPAN, it may prompt you to configure again (see Step 2). If you accept its offer to try to configure itself automatically, it may just run through everything without a problem.</p><p>There are a couple of potential pitfalls with specific modules (such as the<code>LWP::UserAgent</code>&nbsp;/&nbsp;<code>HEAD</code>&nbsp;issue), but most have workarounds, and I haven&rsquo;t run into anything that wasn&rsquo;t easily recoverable.</p><p>And that&rsquo;s it!</p><p>Did you find this useful? Is there anything I missed?</p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/29953/traineeship-at-jawaharlal-nehru-tropical-botanic-garden-and-research-institute</guid>
  <pubDate>Fri, 25 Nov 2016 08:07:59 -0600</pubDate>
  <link></link>
  <title><![CDATA[Traineeship at JAWAHARLAL NEHRU TROPICAL BOTANIC GARDEN AND RESEARCH INSTITUTE]]></title>
  <description><![CDATA[
<p>JAWAHARLAL NEHRU TROPICAL BOTANIC GARDEN AND RESEARCH INSTITUTE</p>

<p>THIRUVANANTHAPURAM - 695 562</p>

<p>Traineeship on Bioinformatics(2)</p>

<p>First class M.Sc. Bioinformatics/ Agriculture/ Botany/ Biotechnology @ Rs.8000</p>

<p>Those candidates who fulfill the above criteria may attend a walk PCC Coordinator in-interview on 28th November 2016 at Saraswathy Thangavelu center, JNTBGRI, Puthenthope, Thiruvananthapuram between at 10.00 am and 2.00 pm with all the relevant document and testimonials.</p>

<p>No TA/DA will be given to candidates for attending the interview.</p>

<p>More Info : http://jntbgri.res.in/downloads/traineeship_notification.pdf</p>
]]></description>
</item>

</channel>
</rss>