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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/36997?offset=100</link>
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	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/30976/brig</guid>
	<pubDate>Thu, 16 Feb 2017 13:14:25 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/30976/brig</link>
	<title><![CDATA[BRIG]]></title>
	<description><![CDATA[<p>BRIG is a free cross-platform (Windows/Mac/Unix) application that can display circular comparisons between a large number of genomes, with a focus on handling genome assembly data. The application is available at:<a href="http://sourceforge.net/projects/brig">http://sourceforge.net/projects/brig</a></p>
<p>If you have any questions or comments, post them on&nbsp;<a href="http://sourceforge.net/tracker/?group_id=328245">one of the trackers</a>&nbsp;on BRIG&rsquo;s SourceForge page:<a href="http://sourceforge.net/tracker/?group_id=328245">http://sourceforge.net/tracker/?group_id=328245</a>.</p>
<p>Features:</p>
<ul>
<li>Images show similarity between a central reference sequence and other sequences as concentric rings.</li>
<li>BRIG will perform all BLAST comparisons and file parsing automatically via a simple GUI.</li>
<li>Contig boundaries and read coverage can be displayed for draft genomes; customized graphs and annotations can be displayed.</li>
<li>Using a user-defined set of genes as input, BRIG can display gene presence, absence, truncation or sequence variation in a set of complete genomes, draft genomes or even raw, unassembled sequence data.</li>
<li>BRIG also accepts SAM-formatted read-mapping files enabling genomic regions present in unassembled sequence data from multiple samples to be compared simultaneously</li>
</ul>
<p>&nbsp;</p><p>Address of the bookmark: <a href="http://brig.sourceforge.net/" rel="nofollow">http://brig.sourceforge.net/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/31064/cgaln</guid>
	<pubDate>Wed, 22 Feb 2017 05:14:15 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/31064/cgaln</link>
	<title><![CDATA[Cgaln]]></title>
	<description><![CDATA[<p>Cgaln (Coarse grained alignment) is a program designed to align a pair of whole genomic sequences of not only bacteria but also entire chromosomes of vertebrates on a nominal desktop computer. Cgaln performs an alignment job in two steps, at the block level and then at the nucleotide level. The former "coarse-grained" alignment can explore genomic rearrangements and reduce the regions to be analyzed in the next step. The latter is devoted to detailed alignment within the limited regions found in the first stage. The output of Cgaln is 'glocal' in the sense that rearrangements are taken into consideration while each alignable region is extended as long as possible. Thus, Cgaln is not only fast and memory-efficient, but also can filter noisy outputs without missing the most important homologous segment pairs.</p>
<p>http://www.iam.u-tokyo.ac.jp/chromosomeinformatics/rnakato/cgaln/</p><p>Address of the bookmark: <a href="http://www.iam.u-tokyo.ac.jp/chromosomeinformatics/rnakato/cgaln/" rel="nofollow">http://www.iam.u-tokyo.ac.jp/chromosomeinformatics/rnakato/cgaln/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/31137/finishersc-a-repeat-aware-and-scalable-tool-for-upgrading-de-novo-assembly-using-long-reads</guid>
	<pubDate>Mon, 27 Feb 2017 09:49:45 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/31137/finishersc-a-repeat-aware-and-scalable-tool-for-upgrading-de-novo-assembly-using-long-reads</link>
	<title><![CDATA[FinisherSC: a repeat-aware and scalable tool for upgrading de novo assembly using long reads]]></title>
	<description><![CDATA[<p><span>FinisherSC, a repeat-aware and scalable tool for upgrading&nbsp;</span><em>de novo</em><span>&nbsp;assembly using long reads. Experiments with real data suggest that FinisherSC can provide longer and higher quality contigs than existing tools while maintaining high concordance.</span></p><p>Address of the bookmark: <a href="http://kakitone.github.io/finishingTool/" rel="nofollow">http://kakitone.github.io/finishingTool/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/31302/multi-metagenome-assembly</guid>
	<pubDate>Fri, 03 Mar 2017 10:14:18 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/31302/multi-metagenome-assembly</link>
	<title><![CDATA[Multi-metagenome 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<br><br>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>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>Radha Agarkar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/31371/phenogram</guid>
	<pubDate>Tue, 07 Mar 2017 08:35:12 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/31371/phenogram</link>
	<title><![CDATA[PhenoGram]]></title>
	<description><![CDATA[<p><span>With PhenoGram researchers can create chomosomal ideograms annotated with lines in color at specific base-pair locations, or colored base-pair to base-pair regions, with or without other annotation. PhenoGram allows for annotation of chromosomal locations and/or regions with shapes in different colors, gene identifiers, or other text. PhenoGram also allows for creation of plots showing expanded chromosomal locations, providing a way to show results for specific chromosomal regions in greater detail.</span></p><p>Address of the bookmark: <a href="http://ritchielab.psu.edu/software/phenogram-downloads" rel="nofollow">http://ritchielab.psu.edu/software/phenogram-downloads</a></p>]]></description>
	<dc:creator>Jit</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/32154/decostar-detection-of-co-evolution</guid>
	<pubDate>Fri, 14 Apr 2017 06:27:25 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/32154/decostar-detection-of-co-evolution</link>
	<title><![CDATA[DeCoSTAR - Detection of Co-evolution]]></title>
	<description><![CDATA[<p><span>DeCoSTAR is a software which aims at reconstructing ancestral gene or genome organizations, in the form of sets of neighborhood relations -adjacencies- between pairs of ancestral genes or gene domains.</span><br><span>Ancestral genes or domains are deduced from reconciled gene trees in a context of birth, speciation, duplication, loss, transfer, which are either given as input or computed with the&nbsp;</span><a href="http://mbb.univ-montp2.fr/MBB/download_sources/16__TERA">ecceTERA package</a><span>, to which DeCoSTAR is integrated. DeCoSTAR constructs parsimonious scenarios of gains and breakages of adjacencies, and contains in particular all the features of previous software DeCo, DeCoLT, ArtDeCo and DeClone. It provides statistical supports on ancestral adjacencies, or the possibility to handle badly assembled genomes.&nbsp;</span><br><span>DeCoSTAR is able to reconstruct the histories of domains inside genes, including gene fusion and fission events, as well as ancestral genome structures for dozens of whole genomes from all kingdoms of life in a few minutes.</span></p><p>Address of the bookmark: <a href="http://pbil.univ-lyon1.fr/software/DeCoSTAR/" rel="nofollow">http://pbil.univ-lyon1.fr/software/DeCoSTAR/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/32713/salzberg-lab</guid>
  <pubDate>Mon, 15 May 2017 05:14:01 -0500</pubDate>
  <link></link>
  <title><![CDATA[Salzberg lab]]></title>
  <description><![CDATA[
<p>We are a computational biology lab that develops novel methods for analysis of DNA and RNA sequences. Our research includes software for aligning and assembling RNA-seq data, whole-genome assembly, and microbiome analysis. We work closely with biomedical scientists to apply these methods to current problems arising in a broad spectrum of biological and medical research areas. We’re also part of the Center for Computational Biology, a group of 20+ faculty members and their labs at Johns Hopkins working on computational, statistical, and mathematical methods that can turn massive genomic data sets into biologically and clinically useful information.</p>

<p>https://salzberg-lab.org/</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/32948/simba-a-web-tool-for-managing-bacterial-genome-assembly-generated-by-ion-pgm-sequencing-technology</guid>
	<pubDate>Tue, 23 May 2017 05:28:56 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/32948/simba-a-web-tool-for-managing-bacterial-genome-assembly-generated-by-ion-pgm-sequencing-technology</link>
	<title><![CDATA[SIMBA: a web tool for managing bacterial genome assembly generated by Ion PGM sequencing technology]]></title>
	<description><![CDATA[<p><span>SIMBA</span><span>, SImple Manager for Bacterial Assemblies, is a Web interface for managing assembly projects of bacterial genomes. SIMBA was created to assist bioinformaticians to assemble bacterial genomes sequenced with NextGeneration Sequencing (NGS) platforms quickly, easily and effectively. SIMBA also is open source tool, i.e., can be freely downloaded, shared and modified.</span></p>
<p>https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-016-1344-7</p><p>Address of the bookmark: <a href="http://ufmg-simba.sourceforge.net/" rel="nofollow">http://ufmg-simba.sourceforge.net/</a></p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34216/meraculous-de-novo-genome-assembly-with-short-paired-end-reads</guid>
	<pubDate>Tue, 07 Nov 2017 04:36:10 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34216/meraculous-de-novo-genome-assembly-with-short-paired-end-reads</link>
	<title><![CDATA[Meraculous: De Novo Genome Assembly with Short Paired-End Reads]]></title>
	<description><![CDATA[<p><span>We describe a new algorithm, meraculous, for whole genome assembly of deep paired-end short reads, and apply it to the assembly of a dataset of paired 75-bp Illumina reads derived from the 15.4 megabase genome of the haploid yeast&nbsp;</span><em>Pichia stipitis</em><span>. More than 95% of the genome is recovered, with no errors; half the assembled sequence is in contigs longer than 101 kilobases and in scaffolds longer than 269 kilobases. Incorporating fosmid ends recovers entire chromosomes. Meraculous relies on an efficient and conservative traversal of the subgraph of the&nbsp;</span><em>k</em><span>-mer (deBruijn) graph of oligonucleotides with unique high quality extensions in the dataset, avoiding an explicit error correction step as used in other short-read assemblers. A novel memory-efficient hashing scheme is introduced. The resulting contigs are ordered and oriented using paired reads separated by &sim;280 bp or &sim;3.2 kbp, and many gaps between contigs can be closed using paired-end placements. Practical issues with the dataset are described, and prospects for assembling larger genomes are discussed.</span></p><p>Address of the bookmark: <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3158087/" rel="nofollow">https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3158087/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

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