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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/31087?offset=1480</link>
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	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/30680/easybuild</guid>
	<pubDate>Fri, 27 Jan 2017 16:00:43 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/30680/easybuild</link>
	<title><![CDATA[EasyBuild]]></title>
	<description><![CDATA[<p><a href="https://github.com/hpcugent/easybuild">EasyBuild</a><span>&nbsp;is a software build and installation framework that allows you to manage (scientific) software on High Performance Computing (HPC) systems in an efficient way.</span><br><span>A full list of supported software packages is available&nbsp;</span><a href="http://easybuild.readthedocs.io/en/latest/version-specific/Supported_software.html">here</a><span>.</span></p><p>Address of the bookmark: <a href="https://hpcugent.github.io/easybuild/" rel="nofollow">https://hpcugent.github.io/easybuild/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34618/mashmap-a-fast-and-approximate-software-for-mapping-long-reads-pacbioont-or-assembly-to-reference-genomes</guid>
	<pubDate>Tue, 12 Dec 2017 17:23:31 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34618/mashmap-a-fast-and-approximate-software-for-mapping-long-reads-pacbioont-or-assembly-to-reference-genomes</link>
	<title><![CDATA[MashMap: a fast and approximate software for mapping long reads (PacBio/ONT) or assembly to reference genome(s)]]></title>
	<description><![CDATA[<p><span>MashMap is a fast and approximate software for mapping long reads (PacBio/ONT) or assembly to reference genome(s). It maps a query sequence against a reference region if and only if its estimated alignment identity is above a specified threshold. It does not compute the alignments explicitly, but rather estimates a&nbsp;</span><em>k</em><span>-mer based&nbsp;</span><a href="https://en.wikipedia.org/wiki/Jaccard_index">Jaccard similarity</a><span>&nbsp;using a combination of&nbsp;</span><a href="http://www.cs.princeton.edu/courses/archive/spr05/cos598E/bib/p76-schleimer.pdf">Winnowing</a><span>&nbsp;and&nbsp;</span><a href="https://en.wikipedia.org/wiki/MinHash">MinHash</a><span>. This is then converted to an estimate of sequence identity using the&nbsp;</span><a href="http://mash.readthedocs.org/">Mash</a><span>&nbsp;distance. An appropriate&nbsp;</span><em>k</em><span>-mer sampling rate is automatically determined given minimum local alignment length and identity thresholds. The efficiency of the algorithm improves as both of these thresholds are increased.</span></p><p>Address of the bookmark: <a href="https://github.com/marbl/MashMap" rel="nofollow">https://github.com/marbl/MashMap</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/30747/11th-international-joint-conference-on-biomedical-engineering-systems-and-technologies</guid>
  <pubDate>Wed, 01 Feb 2017 17:39:27 -0600</pubDate>
  <link></link>
  <title><![CDATA[11th International Joint Conference on Biomedical Engineering Systems and Technologies]]></title>
  <description><![CDATA[
<p>BIOSTEC, the 11th International Joint Conference on Biomedical Engineering Systems and Technologies.<br /> Registration to BIOINFORMATICS allows free access to all other BIOSTEC conferences. </p>

<p>Upcoming Deadlines<br />Regular Paper Submission: July 31, 2017 <br />Regular Paper Authors Notification: October 16, 2017 <br />Regular Paper Camera Ready and Registration: October 30, 2017 </p>

<p>The purpose of the International Conference on Bioinformatics Models, Methods and Algorithms is to bring together researchers and practitioners interested in the application of computational systems, algorithmic concepts and information technologies to address challenging problems in Biomedical research with a particular focus on the emerging problems in Bioinformatics and computational biology. There is a tremendous need to explore how mathematical, statistical and computational models can be used to better understand biological processes and systems, while developing new methodologies and tools to analysis the massive currently-available biological data. Areas of interest to this community include systems biology, sequence analysis, biostatistics, image analysis, network and graph models, scientific data management and data mining, machine learning, pattern recognition, computational evolutionary biology, computational genomics and proteomics, and related areas.</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/35345/rgfa-powerful-and-convenient-handling-of-assembly-graphs</guid>
	<pubDate>Thu, 25 Jan 2018 05:47:53 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/35345/rgfa-powerful-and-convenient-handling-of-assembly-graphs</link>
	<title><![CDATA[RGFA: powerful and convenient handling of assembly graphs]]></title>
	<description><![CDATA[<p><span>RGFA, an implementation of the proposed GFA specification in Ruby. It allows the user to conveniently parse, edit and write GFA files. Complex operations such as the separation of the implicit instances of repeats and the merging of linear paths can be performed. A typical application of RGFA is the editing of a graph, to finish the assembly of a sequence, using information not available to the assembler. We illustrate a use case, in which the assembly of a repetitive metagenomic fosmid insert was completed using a script based on RGFA.</span></p>
<p><span>https://github.com/ggonnella/rgfa</span></p><p>Address of the bookmark: <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5103826/" rel="nofollow">https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5103826/</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/30897/finestructure-v2-globetrotter</guid>
	<pubDate>Mon, 13 Feb 2017 08:40:23 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/30897/finestructure-v2-globetrotter</link>
	<title><![CDATA[fineSTRUCTURE v2 &amp; GLOBETROTTER]]></title>
	<description><![CDATA[<p>Software available at this site</p>
<div>
<ul>
<li><a href="https://people.maths.bris.ac.uk/%7Emadjl/finestructure/finestructure_info.html">FineSTRUCTURE version 2</a>, a pipeline for running ChromoPainter and FineSTRUCTURE for population inference. A GUI is available for interpretation. Download from the <a href="https://people.maths.bris.ac.uk/%7Emadjl/finestructure/finestructure.html">Downloads</a> page.</li>
<li><a href="https://people.maths.bris.ac.uk/%7Emadjl/finestructure/finestructureR.html">FineSTRUCTURE R scripts</a>, a facility for exploring the results when the GUI is unavailable.</li>
<li><a href="https://people.maths.bris.ac.uk/%7Emadjl/finestructure/globetrotter.html">GLOBETROTTER</a>, the admixture dating method based on ChromoPainter. Download from the <a href="https://people.maths.bris.ac.uk/%7Emadjl/finestructure/finestructure.html">Downloads</a> page.</li>
<li><a href="https://people.maths.bris.ac.uk/%7Emadjl/finestructure/admixture.html">AdmixturePainting</a>, A set of R tools to inmterpret the results of ADMIXTURE and STRUCTURE-like mixture models.</li>
<li><a href="https://people.maths.bris.ac.uk/%7Emadjl/finestructure/radpainter.html">RADpainter</a>, finestructure and ChromoPainter for RAD tag data used for non-model organisms.</li>
<li>Scripts to perform many types of conversion. Included in the main software download from the <a href="https://people.maths.bris.ac.uk/%7Emadjl/finestructure/finestructure.html">Downloads</a> page.</li>
</ul>
What this page is This page provides information about and downloads for <strong>methodology for Chromosome Painting</strong>. It is not a facility to analyse your genome. Sorry if you were misled by the punchy name!<br> About Chromosome Painting Painting is an efficient way of identifying important haplotype information from dense genotype data. It describes ancestry in an efficient way suitable for a range of further analyses, including population identification and admixture dating.</div><p>Address of the bookmark: <a href="http://paintmychromosomes.com/" rel="nofollow">http://paintmychromosomes.com/</a></p>]]></description>
	<dc:creator>Shruti Paniwala</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/31123/biodownloader</guid>
	<pubDate>Sat, 25 Feb 2017 17:52:33 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/31123/biodownloader</link>
	<title><![CDATA[BioDownloader]]></title>
	<description><![CDATA[<p><strong><em>BioDownloader</em></strong> is a program for downloading and/or updating files from ftp/http servers. The program has unique features that are specifically designed to deal with bioinformatics data files and servers:</p>
<ul>
<li>optimized to work with vast amount of data and very large file sets (~ 10,000 - 100,000).</li>
<li>allows the selective retrieval of only the required files (file masks, ls-lR parsing, recursive search, updates)</li>
<li>has a built-in repository containing the settings for the most common bioinformatics download needs</li>
<li>built-in wizard for batch post-processing of downloaded files (archive extraction, file conversion, etc.)</li>
<li>capable of performing multiple download or update tasks simultaneously</li>
</ul>
<p>BioDownloader has a built-in repository containing the settings for common bioinformatics file-synchronization needs, including the Protein Data Bank (PDB) and National Center for Biotechnology Information (NCBI) databases. It can post-process downloaded files, including archive extraction and file conversions.</p>
<p>http://dunbrack.fccc.edu/BioDownloader/</p><p>Address of the bookmark: <a href="http://dunbrack.fccc.edu/BioDownloader/" rel="nofollow">http://dunbrack.fccc.edu/BioDownloader/</a></p>]]></description>
	<dc:creator>Surabhi Chaudhary</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36867/cerulean-a-hybrid-assembly-using-high-throughput-short-and-long-reads</guid>
	<pubDate>Tue, 05 Jun 2018 10:10:15 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36867/cerulean-a-hybrid-assembly-using-high-throughput-short-and-long-reads</link>
	<title><![CDATA[Cerulean: A hybrid assembly using high throughput short and long reads]]></title>
	<description><![CDATA[Cerulean extends contigs assembled using short read datasets like Illumina paired-end reads using long reads like PacBio RS long reads.

Cerulean v0.1 has been implemented with bacterial genomes in mind.

The method is fully described in Deshpande, V., Fung, E. D., Pham, S., &amp; Bafna, V. (2013). Cerulean: A hybrid assembly using high throughput short and long reads. arXiv preprint arXiv:1307.7933.
http://arxiv.org/abs/1307.7933<p>Address of the bookmark: <a href="https://sourceforge.net/projects/ceruleanassembler/" rel="nofollow">https://sourceforge.net/projects/ceruleanassembler/</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/31205/yasra-reference-based-assembler</guid>
	<pubDate>Wed, 01 Mar 2017 08:32:45 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/31205/yasra-reference-based-assembler</link>
	<title><![CDATA[YASRA: Reference based assembler]]></title>
	<description><![CDATA[<p>YASRA (Yet Another Short Read Assembler) performs comparative assembly of short reads using a reference genome, which can differ substantially from the genome being sequenced. Mapping reads to reference genomes makes use of LASTZ (Harris et al), a pairwise sequence aligner compatible with BLASTZ. Special scoring sets were derived to improve the performance, both in runtime and quality for 454 and Illumina sequence reads.</p>
<p>YASRA uses LASTZ (<a href="http://bx.psu.edu/miller_lab">http://bx.psu.edu/miller_lab</a> for released version and <a href="http://www.bx.psu.edu/%7Ersharris/lastz/newer">http://www.bx.psu.edu/~rsharris/lastz/newer</a> for newer version) for aligning the sequences to the reference genome. Please install LASTZ (the newest version on <a href="http://www.bx.psu.edu/%7Ersharris/lastz/newer">http://www.bx.psu.edu/~rsharris/lastz/newer</a>) and add the LASTZ binary in your executable/binary search path before installing YASRA.</p><p>Address of the bookmark: <a href="https://github.com/aakrosh/YASRA" rel="nofollow">https://github.com/aakrosh/YASRA</a></p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37291/transrate-understanding-your-transcriptome-assembly</guid>
	<pubDate>Fri, 13 Jul 2018 07:49:26 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37291/transrate-understanding-your-transcriptome-assembly</link>
	<title><![CDATA[transrate: Understanding your transcriptome assembly]]></title>
	<description><![CDATA[<p><span>Transrate is software for&nbsp;</span><em>de-novo</em><span>&nbsp;transcriptome assembly quality analysis. It examines your assembly in detail and compares it to experimental evidence such as the sequencing reads, reporting quality scores for contigs and assemblies. This allows you to choose between assemblers and parameters, filter out the bad contigs from an assembly, and help decide when to stop trying to improve the assembly.</span></p><p>Address of the bookmark: <a href="http://hibberdlab.com/transrate/index.html" rel="nofollow">http://hibberdlab.com/transrate/index.html</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/31564/htslib</guid>
	<pubDate>Wed, 15 Mar 2017 11:38:05 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/31564/htslib</link>
	<title><![CDATA[HTSlib]]></title>
	<description><![CDATA[<p>Samtools is a suite of programs for interacting with high-throughput sequencing data. It consists of three separate repositories:</p>
<dl><dt>Samtools</dt><dd>Reading/writing/editing/indexing/viewing SAM/BAM/CRAM format</dd><dt>BCFtools</dt><dd>Reading/writing BCF2/VCF/gVCF files and calling/filtering/summarising SNP and short indel sequence variants</dd><dt>HTSlib</dt><dd>A C library for reading/writing high-throughput sequencing data</dd></dl>
<p>Samtools and BCFtools both use HTSlib internally, but these source packages contain their own copies of htslib so they can be built independently.</p><p>Address of the bookmark: <a href="http://www.htslib.org/" rel="nofollow">http://www.htslib.org/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

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