<?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/41686?offset=190</link>
	<atom:link href="https://bioinformaticsonline.com/related/41686?offset=190" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37980/csbfinder-discovery-of-colinear-syntenic-blocks-across-thousands-of-prokaryotic-genomes</guid>
	<pubDate>Wed, 24 Oct 2018 22:12:27 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37980/csbfinder-discovery-of-colinear-syntenic-blocks-across-thousands-of-prokaryotic-genomes</link>
	<title><![CDATA[CSBFinder: Discovery of colinear syntenic blocks across thousands of prokaryotic genomes]]></title>
	<description><![CDATA[<p>CSBFinder is a standalone Desktop java application with a graphical user interface, that can also be executed via command line.</p>
<p>CSBFinder implements a novel methodology for the discovery, ranking, and taxonomic distribution analysis of colinear syntenic blocks (<span>CSBs</span>) - groups of genes that are consistently located close to each other, in the same order, across a wide range of taxa. CSBFinder incorporates an efficient algorithm that identifies CSBs in large genomic datasets. The discovered CSBs are ranked according to a probabilistic score and clustered to families according to their gene content similarity.</p><p>Address of the bookmark: <a href="https://github.com/dinasv/CSBFinder" rel="nofollow">https://github.com/dinasv/CSBFinder</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/39869/mfannot-a-program-for-the-annotation-of-mitochondrial-and-plastid-genomes</guid>
	<pubDate>Mon, 26 Aug 2019 11:47:56 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/39869/mfannot-a-program-for-the-annotation-of-mitochondrial-and-plastid-genomes</link>
	<title><![CDATA[MFannot : a program for the annotation of mitochondrial and plastid genomes]]></title>
	<description><![CDATA[<p><span>MFannot is a program for the annotation of mitochondrial and plastid genomes</span></p>
<p>MFannot is a program for the annotation of mitochondrial and plastid genomes. It is a PERL wrapper around a set of diverse, external independent tools.</p>
<p>It makes intense use of RNA/intron detection tools including&nbsp;<a href="http://hmmer.org/">HMMER</a>,&nbsp;<a href="https://github.com/nathanweeks/exonerate">Exonerate</a>,&nbsp;<a href="https://bioinformatics.ca/links_directory/tool/9822/erpin">Erpin</a>&nbsp;and others.</p>
<p><a href="http://megasun.bch.umontreal.ca/cgi-bin/mfannot/mfannotInterface.pl">http://megasun.bch.umontreal.ca/cgi-bin/mfannot/mfannotInterface.pl</a></p><p>Address of the bookmark: <a href="https://github.com/BFL-lab/Mfannot" rel="nofollow">https://github.com/BFL-lab/Mfannot</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41592/refka-a-fast-and-efficient-long-read-genome-assembly-approach-for-large-and-complex-genomes</guid>
	<pubDate>Fri, 01 May 2020 03:00:40 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41592/refka-a-fast-and-efficient-long-read-genome-assembly-approach-for-large-and-complex-genomes</link>
	<title><![CDATA[RefKA: A fast and efficient long-read genome assembly approach for large and complex genomes]]></title>
	<description><![CDATA[<p><span>RefKA, a reference-based approach for long read genome assembly. This approach relies on breaking up a closely related reference genome into bins, aligning k-mers unique to each bin with PacBio reads, and then assembling each bin in parallel followed by a final bin-stitching step.</span></p>
<p>&nbsp;</p><p>Address of the bookmark: <a href="https://github.com/AppliedBioinformatics/RefKA" rel="nofollow">https://github.com/AppliedBioinformatics/RefKA</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/42325/published-a-dataset-of-363-genomes-from-approximately-92-percent-of-bird-families</guid>
	<pubDate>Thu, 19 Nov 2020 07:04:41 -0600</pubDate>
	<link>https://bioinformaticsonline.com/news/view/42325/published-a-dataset-of-363-genomes-from-approximately-92-percent-of-bird-families</link>
	<title><![CDATA[Published a dataset of 363 genomes from approximately 92 percent of bird families]]></title>
	<description><![CDATA[<div>A research team published a dataset of 363 genomes from approximately 92 percent of bird families and showed the significance of sampling dense organisms for biodiversity research. The study was jointly conducted by Chinese and international institutions and museums and was led by researchers from the Kunming Institute of Zoology (KIZ) of the Chinese Academy of Sciences (CAS). Total of 267 were newly published among the 363 sequenced genomes.&nbsp;They were mainly taken from samples of avian tissue kept in museums around the world, enabling researchers to sequence rare and endangered birds' genomes.</div><div>&nbsp;</div><div>Its descendants have adapted to a wide variety of ecological niches since the first bird formed more than 150 million years ago, giving rise to small, hovering hummingbirds, plunge-diving pelicans and showy paradise birds. More than 10,000 bird species live on the planet today - and now scientists are well on their way to capturing a full genetic image of that diversity.</div><div>&nbsp;</div><div>B10K is expanding its efforts to encompass the next stage of avian classification with 363 genomes complete. The team will sequence thousands of extra genomes in this process, attempting to represent each of the approximately 2,300 bird genera.</div><div>&nbsp;</div><div><img src="https://media.springernature.com/lw685/springer-static/image/art%3A10.1038%2Fs41586-020-2873-9/MediaObjects/41586_2020_2873_Fig1_HTML.png?as=webp" alt="image" style="border: 0px;"></div><div>&nbsp;</div><div>The genomic resource is expected to provide new insights on evolutionary processes in cross-species comparative studies and assist in efforts to protect species, according to the research findings reported as a cover story in the journal Nature.</div><div>&nbsp;</div><div>Ref at&nbsp;Dense sampling of bird diversity increases power of comparative genomics&nbsp;https://www.nature.com/articles/s41586-020-2873-9</div>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44313/orthovenn3-an-integrated-platform-for-exploring-and-visualizing-orthologous-data-across-genomes</guid>
	<pubDate>Tue, 02 May 2023 00:48:28 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44313/orthovenn3-an-integrated-platform-for-exploring-and-visualizing-orthologous-data-across-genomes</link>
	<title><![CDATA[OrthoVenn3: an integrated platform for exploring and visualizing orthologous data across genomes]]></title>
	<description><![CDATA[<p><span>OrthoVenn3 is a powerful tool for comparative genomics analysis, used as a web server for full genome comparisons, annotation, and evolutionary analysis of orthologous clusters across multiple species. It has already been used by thousands of users from over 60 countries.</span></p><p>Address of the bookmark: <a href="https://orthovenn3.bioinfotoolkits.net/" rel="nofollow">https://orthovenn3.bioinfotoolkits.net/</a></p>]]></description>
	<dc:creator>Abhi</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/31552/multigenome-assembly</guid>
	<pubDate>Tue, 14 Mar 2017 04:41:23 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/31552/multigenome-assembly</link>
	<title><![CDATA[Multigenome assembly]]></title>
	<description><![CDATA[<p>This project contains scripts and tutorials on how to assemble individual microbial genomes from metagenomes, as described in:</p>
<p>Genome sequences of rare, uncultured bacteria obtained by differential coverage binning of multiple metagenomes</p>
<p>Mads Albertsen, Philip Hugenholtz, Adam Skarshewski, Gene W. Tyson, K&aring;re L. Nielsen and Per .H. Nielsen</p>
<p>Nature Biotechnology 2013, doi:&nbsp;<a href="http://www.nature.com/nbt/journal/vaop/ncurrent/abs/nbt.2579.html">10.1038/nbt.2579</a></p>
<p>See the associated&nbsp;<a href="http://madsalbertsen.github.io/multi-metagenome/">online guide</a>&nbsp;for detailed information.</p>
<p>https://github.com/MadsAlbertsen/multi-metagenome</p><p>Address of the bookmark: <a href="https://github.com/MadsAlbertsen/multi-metagenome" rel="nofollow">https://github.com/MadsAlbertsen/multi-metagenome</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/33859/disco-multi-threaded-and-multiprocess-distributed-memory-overlap-layout-consensus-olc-metagenome-assembler</guid>
	<pubDate>Mon, 10 Jul 2017 10:09:27 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/33859/disco-multi-threaded-and-multiprocess-distributed-memory-overlap-layout-consensus-olc-metagenome-assembler</link>
	<title><![CDATA[DISCO : multi threaded and multiprocess distributed memory overlap-layout-consensus (OLC) metagenome assembler]]></title>
	<description><![CDATA[<p><span>DISCO is a multi threaded and multiprocess distributed memory overlap-layout-consensus (OLC) metagenome assembler. Disco was developed as a&nbsp;scalable assembler to assemble large metagenomes from billions of Illumina sequencing reads of complex microbial communities. Disco was parallelized for computer clusters in a hybrid architecture that integrated shared-memory multi-threading, point-to-point message passing, and remote direct memory access. The assembly and scaffolding were performed using an iterative overlap graph approach.</span></p><p>Address of the bookmark: <a href="http://disco.omicsbio.org/" rel="nofollow">http://disco.omicsbio.org/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34420/rita-rapid-identification-of-high-confidence-taxonomic-assignments-for-metagenomic-data</guid>
	<pubDate>Mon, 27 Nov 2017 08:25:33 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34420/rita-rapid-identification-of-high-confidence-taxonomic-assignments-for-metagenomic-data</link>
	<title><![CDATA[RITA: Rapid identification of high-confidence taxonomic assignments for metagenomic data]]></title>
	<description><![CDATA[<p>RITA is a standalone software package and Web server for taxonomic assignment of metagenomic sequence reads. By combining homology predictions from BLAST or UBLAST with compositional classifications from a Naive Bayes classifier, RITA is able to achieve very high accuracy on short reads. Unlike other hybrid approaches which combine these predictions for all sequences to be classified, RITA uses a pipeline to first identify cases where both types of classifier are in agreement, which constitute the highest-confidence set. Sequences not classified in this manner are subjected to a series of downstream classification steps.</p>
<p>This work has been accepted for publication:</p>
<p>MacDonald NJ, Parks DH, and Beiko RG. Rapid identification of taxonomic assignments. Accepted to&nbsp;<em>Nucleic Acids Research</em>&nbsp;April 4, 2012.</p>
<p>If you have any questions or bug reports, please let us know at &lt;beiko@cs.dal.ca&gt;.</p><p>Address of the bookmark: <a href="http://kiwi.cs.dal.ca/Software/RITA" rel="nofollow">http://kiwi.cs.dal.ca/Software/RITA</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42491/eukulele-taxonomic-annotation-of-the-unsung-eukaryotic-microbes</guid>
	<pubDate>Sat, 26 Dec 2020 12:10:17 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42491/eukulele-taxonomic-annotation-of-the-unsung-eukaryotic-microbes</link>
	<title><![CDATA[EUKulele: Taxonomic annotation of the unsung eukaryotic microbes]]></title>
	<description><![CDATA[<p><span><span>&nbsp;</span>EUKulele, an open-source software tool designed to assign taxonomy to microeukaryotes detected in meta-omic samples, and complement analysis approaches in other domains by accommodating assembly output and providing concrete metrics reporting the taxonomic completeness of each sample.</span></p><p>Address of the bookmark: <a href="https://github.com/AlexanderLabWHOI/EUKulele" rel="nofollow">https://github.com/AlexanderLabWHOI/EUKulele</a></p>]]></description>
	<dc:creator>Shruti Paniwala</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27110/easyfig</guid>
	<pubDate>Fri, 29 Apr 2016 05:49:39 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27110/easyfig</link>
	<title><![CDATA[Easyfig]]></title>
	<description><![CDATA[<p>Easyfig has moved to github, for newer releases of Easyfig please visit our new webpage - https://mjsull.github.io/Easyfig.&nbsp; Easyfig is a Python application for creating linear comparison figures of multiple genomic loci with an easy-to-use graphical user interface (GUI).</p>
<p>More at http://easyfig.sourceforge.net/</p><p>Address of the bookmark: <a href="http://easyfig.sourceforge.net/" rel="nofollow">http://easyfig.sourceforge.net/</a></p>]]></description>
	<dc:creator>Poonam Mahapatra</dc:creator>
</item>

</channel>
</rss>