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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/44902?offset=150</link>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/file/view/18653/genetic-code-amino-acid</guid>
	<pubDate>Sun, 26 Oct 2014 07:45:58 -0500</pubDate>
	<link>https://bioinformaticsonline.com/file/view/18653/genetic-code-amino-acid</link>
	<title><![CDATA[Genetic code - Amino Acid]]></title>
	<description><![CDATA[<p>The genetic code consists of 64 triplets of nucleotides. These triplets are called codons.With three exceptions, each codon encodes for one of the 20 amino acids used in the synthesis of proteins. That produces some redundancy in the code: most of the amino acids being encoded by more than one codon.</p><p>The image summarise all in one.</p><p>More at http://users.rcn.com/jkimball.ma.ultranet/BiologyPages/C/Codons.html</p>]]></description>
	<dc:creator>Poonam Mahapatra</dc:creator>
	<enclosure url="https://bioinformaticsonline.com/file/download/18653" length="226605" type="image/jpeg" />
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<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/19631/rosalind-bioinformatics-problems</guid>
	<pubDate>Thu, 18 Dec 2014 10:32:48 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/19631/rosalind-bioinformatics-problems</link>
	<title><![CDATA[Rosalind Bioinformatics problems !!!]]></title>
	<description><![CDATA[<p>Rosalind is a platform for learning bioinformatics and programming through problem solving. <a href="http://rosalind.info/problems/list-view/">Take a tour</a> to get the hang of how Rosalind works.</p>
<p>http://rosalind.info/problems/list-view/</p><p>Address of the bookmark: <a href="http://rosalind.info/problems/list-view/" rel="nofollow">http://rosalind.info/problems/list-view/</a></p>]]></description>
	<dc:creator>Abhi</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/19980/seqloc-06</guid>
	<pubDate>Sun, 28 Dec 2014 12:51:29 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/19980/seqloc-06</link>
	<title><![CDATA[seqloc 0.6]]></title>
	<description><![CDATA[<p>The <code>Bio.SeqLoc</code> modules in <code>seqloc</code> are designed to represent positions and locations (ranges of positions) on sequences, particularly nucleotide sequences. My original motivation for writing these packages was handing the locations of genes in eukaryotic genomes.</p>
<p>Handle sequence locations for bioinformatics http://www.ingolia-lab.org/seqloc-tutorial.html</p><p>Address of the bookmark: <a href="http://www.stackage.org/snapshot/nightly-2014-12-28/package/seqloc-0.6" rel="nofollow">http://www.stackage.org/snapshot/nightly-2014-12-28/package/seqloc-0.6</a></p>]]></description>
	<dc:creator>Gudiya Pal</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/file/view/23838/scripted-dna</guid>
	<pubDate>Mon, 17 Aug 2015 17:44:04 -0500</pubDate>
	<link>https://bioinformaticsonline.com/file/view/23838/scripted-dna</link>
	<title><![CDATA[Scripted DNA !!!]]></title>
	<description><![CDATA[<p>As per bioinformatician DNA is partially scripted ;) You dont believe in it. Please have a look at image carefully:)</p>]]></description>
	<dc:creator>Jit</dc:creator>
	<enclosure url="https://bioinformaticsonline.com/file/download/23838" length="13498" type="image/gif" />
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/26525/ensembl-comparative-genomics-resources</guid>
	<pubDate>Sun, 28 Feb 2016 17:10:20 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/26525/ensembl-comparative-genomics-resources</link>
	<title><![CDATA[Ensembl comparative genomics resources]]></title>
	<description><![CDATA[<div>
<p>The Ensembl comparative genomics resources are one such reference set that facilitates comprehensive and reproducible analysis of chordate genome data. Ensembl computes pairwise and multiple whole-genome alignments from which large-scale synteny, per-base conservation scores and constrained elements are obtained. Gene alignments are used to define Ensembl Protein Families, GeneTrees and homologies for both protein-coding and non-coding RNA genes. These resources are updated frequently and have a consistent informatics infrastructure and data presentation across all supported species. Specialized web-based visualizations are also available including synteny displays, collapsible gene tree plots, a gene family locator and different alignment views. The Ensembl comparative genomics infrastructure is extensively reused for the analysis of non-vertebrate species by other projects including Ensembl Genomes and Gramene and much of the information here is relevant to these projects. The consistency of the annotation across species and the focus on vertebrates makes Ensembl an ideal system to perform and support vertebrate comparative genomic analyses. We use robust software and pipelines to produce reference comparative data and make it freely available.</p>
<p><strong>Database URL:</strong> <a href="http://www.ensembl.org" target="pmc_ext">http://www.ensembl.org</a>.</p>
</div><p>Address of the bookmark: <a href="http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4761110/" rel="nofollow">http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4761110/</a></p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/26426/genome-browser-gbrowse</guid>
	<pubDate>Fri, 19 Feb 2016 09:22:43 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/26426/genome-browser-gbrowse</link>
	<title><![CDATA[Genome Browser : GBrowse]]></title>
	<description><![CDATA[<p>Generic Genome Browser Version 2: A Tutorial for Administrators</p>
<p>This is an extensive tutorial to take you through the main features and gotchas of configuring GBrowse as a server. This tutorial assumes that you have successfully set up Perl, GD, BioPerl and the other GBrowse dependencies. If you haven't, please see the <a href="http://gmod.org/wiki/GBrowse_2.0_HOWTO">GBrowse HOWTO</a> During most of the tutorial, we will be using the "in-memory" GBrowse database (no relational database required!) Later we will show how to set up a genome size database using the berkeleydb and MySQL adaptors.</p>
<p>More at http://elp.ucdavis.edu/tutorial/tutorial.html</p><p>Address of the bookmark: <a href="http://elp.ucdavis.edu/tutorial/tutorial.html" rel="nofollow">http://elp.ucdavis.edu/tutorial/tutorial.html</a></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>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/28809/kissplice</guid>
	<pubDate>Tue, 16 Aug 2016 08:34:19 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/28809/kissplice</link>
	<title><![CDATA[KisSplice]]></title>
	<description><![CDATA[<p>KisSplice is a software that enables to analyse RNA-seq data with or without a reference genome. It is an exact local transcriptome assembler that allows to identify SNPs, indels and alternative splicing events. It can deal with an arbitrary number of biological conditions, and will quantify each variant in each condition. It has been tested on Illumina datasets of up to 1G reads. Its memory consumption is around 5Gb for 100M reads.</p>
<p>KisSplice is not a full-length transcriptome assembler. This means that it will output the variable regions of the transcripts, not reconstruct them entirely.</p>
<p>KisSplice comes as a workflow, with several possible post-treatments meant to facilitate the analysis of the results. The choice of the post-treatment depends on the availability of a reference genome/transcriptome and on the need to perform a differential analysis, as summarised in the following table.</p><p>Address of the bookmark: <a href="http://kissplice.prabi.fr/" rel="nofollow">http://kissplice.prabi.fr/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/28269/4dgenome</guid>
	<pubDate>Mon, 04 Jul 2016 00:44:55 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/28269/4dgenome</link>
	<title><![CDATA[4DGenome]]></title>
	<description><![CDATA[<p><span>Records in 4DGenome are compiled through comprehensive literature curation of experimentally-derived and computationally-predicted interactions. The current release contains 4,433,071 experimentally-derived and 3,605,176 computationally-predicted interactions in 5 organisms. Experimental data cover both high throughput datasets and individiual focused studies.&nbsp;</span><br><br><span>All interaction data are freely available in a standardized file format. Records can be queried by genomic regions, gene names, organism, and detection technology.&nbsp;</span></p><p>Address of the bookmark: <a href="http://4dgenome.research.chop.edu/" rel="nofollow">http://4dgenome.research.chop.edu/</a></p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/28807/organellargenomedraw</guid>
	<pubDate>Tue, 16 Aug 2016 08:13:13 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/28807/organellargenomedraw</link>
	<title><![CDATA[OrganellarGenomeDRAW]]></title>
	<description><![CDATA[<p><span>O</span><span>rganellar</span><span>G</span><span>enome</span><span>DRAW</span><span>&nbsp;is dedicated to convert genetic information stored in GenBank entries to graphical maps. The input text file has to be in GenBank flat file format, whereas the output format can be chosen among several formats. The application is especially optimized and adapted for the creation of high-quality, detailed circular maps of organellar genomes like the plastid genome (plastome) or the mitochondrial genome (chondriome). Nevertheless, you can upload any GenBank entry. The workflow is devided into three steps.&nbsp;</span></p>
<p><span>More at&nbsp;http://ogdraw.mpimp-golm.mpg.de/cgi-bin/ogdraw.pl</span></p><p>Address of the bookmark: <a href="http://ogdraw.mpimp-golm.mpg.de/index.shtml" rel="nofollow">http://ogdraw.mpimp-golm.mpg.de/index.shtml</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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