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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/41033?offset=150</link>
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	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42160/vicuna-a-software-tool-that-enables-consensus-assembly-of-ultra-deep-sequence-derived-from-diverse-viral-or-other-heterogeneous-populations</guid>
	<pubDate>Tue, 25 Aug 2020 03:40:17 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42160/vicuna-a-software-tool-that-enables-consensus-assembly-of-ultra-deep-sequence-derived-from-diverse-viral-or-other-heterogeneous-populations</link>
	<title><![CDATA[VICUNA: a software tool that enables consensus assembly of ultra-deep sequence derived from diverse viral or other heterogeneous populations.]]></title>
	<description><![CDATA[<p><span>VICUNA</span><span>&nbsp;is a&nbsp;</span><em>de novo</em><span>&nbsp;assembly program targeting populations with high mutation rates. It creates a single linear representation of the mixed population on which intra-host variants can be mapped. For clinical samples rich in contamination (e.g., &gt;95%), VICUNA can leverage existing genomes, if available, to assemble only target-alike reads. After initial assembly, it can also use existing genomes to perform guided merging of contigs. For each data set (e.g., Illumina paired read, 454), VICUNA outputs consensus sequence(s) and the corresponding multiple sequence alignment of constituent reads. VICUNA efficiently handles ultra-deep sequence data with tens of thousands fold coverage.</span></p>
<p><a href="http://software.broadinstitute.org/viral/docs/vicuna_v1.0.pdf">http://software.broadinstitute.org/viral/docs/vicuna_v1.0.pdf</a></p><p>Address of the bookmark: <a href="https://www.broadinstitute.org/viral-genomics/vicuna" rel="nofollow">https://www.broadinstitute.org/viral-genomics/vicuna</a></p>]]></description>
	<dc:creator>biogeek</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44529/contigextender-a-new-approach-to-improving-de-novo-sequence-assembly-for-viral-metagenomics-data</guid>
	<pubDate>Wed, 08 May 2024 07:32:45 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44529/contigextender-a-new-approach-to-improving-de-novo-sequence-assembly-for-viral-metagenomics-data</link>
	<title><![CDATA[ContigExtender: a new approach to improving de novo sequence assembly for viral metagenomics data]]></title>
	<description><![CDATA[<p dir="auto">ContigExtender, was developed to extend contigs, complementing de novo assembly. ContigExtender employs a novel recursive Overlap Layout Candidates (r-OLC) strategy that explores multiple extending paths to achieve longer and highly accurate contigs. ContigExtender is effective for extending contigs significantly in in silico synthesized and real metagenomics datasets.</p>
<p dir="auto">More at&nbsp;https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7953547/</p>
<p dir="auto"><a href="https://camo.githubusercontent.com/72dc78177cd84dd0c667a2922a9fd984fb548b5ec94b11f9a547211a4adba3b1/68747470733a2f2f692e696d6775722e636f6d2f7734516944496a2e706e67" target="_blank"><img src="https://camo.githubusercontent.com/72dc78177cd84dd0c667a2922a9fd984fb548b5ec94b11f9a547211a4adba3b1/68747470733a2f2f692e696d6775722e636f6d2f7734516944496a2e706e67" alt="extension process" title="extension process" style="border: 0px;"></a></p><p>Address of the bookmark: <a href="https://github.com/dengzac/contig-extender" rel="nofollow">https://github.com/dengzac/contig-extender</a></p>]]></description>
	<dc:creator>LEGE</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/35920/mesquite-a-modular-system-for-evolutionary-analysis</guid>
	<pubDate>Tue, 13 Mar 2018 06:54:32 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/35920/mesquite-a-modular-system-for-evolutionary-analysis</link>
	<title><![CDATA[Mesquite: A modular system for evolutionary analysis]]></title>
	<description><![CDATA[<p><span>Mesquite is modular, extendible software for evolutionary biology, designed to help biologists organize and analyze comparative data about organisms. Its emphasis is on phylogenetic analysis, but some of its modules concern population genetics, while others do non-phylogenetic multivariate analysis. Because it is modular, the analyses available depend on the modules installed.</span></p>
<p><span>https://github.com/MesquiteProject/MesquiteCore</span></p><p>Address of the bookmark: <a href="http://mesquiteproject.org/" rel="nofollow">http://mesquiteproject.org/</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34579/moss-a-system-for-detecting-software-similarity</guid>
	<pubDate>Sat, 09 Dec 2017 08:59:07 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34579/moss-a-system-for-detecting-software-similarity</link>
	<title><![CDATA[MOSS: A System for Detecting Software Similarity]]></title>
	<description><![CDATA[<p><span>Moss (for a Measure Of Software Similarity) is an automatic system for determining the similarity of programs. To date, the main application of Moss has been in detecting plagiarism in programming classes. Since its development in 1994, Moss has been very effective in this role. The algorithm behind moss is a significant improvement over other cheating detection algorithms (at least, over those known to us).</span></p>
<p><span><span>Moss can currently analyze code written in the following languages:</span></span></p>
<p>C, C++, Java, C#, Python, Visual Basic, Javascript, FORTRAN, ML, Haskell, Lisp, Scheme, Pascal, Modula2, Ada, Perl, TCL, Matlab, VHDL, Verilog, Spice, MIPS assembly, a8086 assembly, a8086 assembly, MIPS assembly, HCL2.</p><p>Address of the bookmark: <a href="https://theory.stanford.edu/~aiken/moss/" rel="nofollow">https://theory.stanford.edu/~aiken/moss/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/42263/data-steward-research-development-specialist-at-at-the-luxembourg-centre-for-systems-biomedicine-lcsb</guid>
  <pubDate>Sun, 25 Oct 2020 22:36:38 -0500</pubDate>
  <link></link>
  <title><![CDATA[Data Steward / Research &amp; Development Specialist at at the Luxembourg Centre for Systems Biomedicine (LCSB)]]></title>
  <description><![CDATA[
<p>Applications should be addressed online to: Prof. Dr. Reinhard Schneider, Head of the Bioinformatics Core Facility</p>

<p>For further information, please contact: Dr. Pinar Alper (pinar.alper@uni.lu)</p>

<p>Applications should be submitted online and include:</p>

<p>A detailed curriculum vitae<br />Cover letter mentioning the reference number<br />List of publications/software projects<br />Description of past experience and future interests<br />Names and addresses of three referees<br />Early application is highly encouraged, as the applications will be processed upon reception. Please apply ONLINE formally through the HR system. Applications by email will not be considered.</p>

<p>*gn=gender neutral.</p>

<p>More at https://recruitment.uni.lu/en/details.html?nPostingId=54616&amp;nPostingTargetId=74219&amp;id=QMUFK026203F3VBQB7V7VV4S8&amp;LG=UK&amp;mask=karriereseiten&amp;sType=Social%20Recruiting</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/35543/genometools-the-versatile-open-source-genome-analysis-software</guid>
	<pubDate>Wed, 07 Feb 2018 10:44:18 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/35543/genometools-the-versatile-open-source-genome-analysis-software</link>
	<title><![CDATA[GenomeTools: The versatile open source genome analysis software]]></title>
	<description><![CDATA[<p>The&nbsp;<em>GenomeTools</em>&nbsp;genome analysis system is a&nbsp;<a href="http://genometools.org/license.html">free</a>&nbsp;collection of bioinformatics&nbsp;<a href="http://genometools.org/tools.html">tools</a>&nbsp;(in the realm of genome informatics) combined into a single binary named&nbsp;<em>gt</em>. It is based on a C library named &ldquo;libgenometools&rdquo; which consists of several modules.</p>
<p>If you are interested in gene prediction, have a look at&nbsp;<a href="http://genomethreader.org/" title="GenomeThreader gene prediction        software"><em>GenomeThreader</em></a>.</p><p>Address of the bookmark: <a href="http://genometools.org/" rel="nofollow">http://genometools.org/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42017/gromacs-a-versatile-package-to-perform-molecular-dynamics</guid>
	<pubDate>Thu, 06 Aug 2020 22:40:38 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42017/gromacs-a-versatile-package-to-perform-molecular-dynamics</link>
	<title><![CDATA[GROMACS: a versatile package to perform molecular dynamics]]></title>
	<description><![CDATA[<p><span>GROMACS is a versatile package to perform molecular dynamics, i.e simulate the Newtonian equations of motion for systems with hundreds to millions of particles. GROMACS is able to work with many biochemical molecules like proteins, lipids and nucleic acids. The WeNMR GROMACS web portal combines the versatility of this molecular dynamics package with the calculation power of the eNMR grid. This will enable you to perform many simulations from the comfort of your internet browser anywhere in the world. The server is furthermore aimed to provide a user friendly and efficient MD experience by performing many preparation and optimization steps automatically.</span></p>
<p>GROMACS conda&nbsp;<a href="https://bioconda.github.io/recipes/gromacs/README.html">https://bioconda.github.io/recipes/gromacs/README.html</a>&nbsp;</p><p>Address of the bookmark: <a href="http://haddock.science.uu.nl/enmr/services/GROMACS/main.php" rel="nofollow">http://haddock.science.uu.nl/enmr/services/GROMACS/main.php</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34528/cope-an-accurate-k-mer-based-pair-end-reads-connection-tool-to-facilitate-genome-assembly</guid>
	<pubDate>Wed, 06 Dec 2017 02:08:14 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34528/cope-an-accurate-k-mer-based-pair-end-reads-connection-tool-to-facilitate-genome-assembly</link>
	<title><![CDATA[COPE: an accurate k-mer-based pair-end reads connection tool to facilitate genome assembly]]></title>
	<description><![CDATA[<p><span>An efficient tool called Connecting Overlapped Pair-End (COPE) reads, to connect overlapping pair-end reads using k-mer frequencies. We evaluated our tool on 30&times; simulated pair-end reads from Arabidopsis thaliana with 1% base error. COPE connected over 99% of reads with 98.8% accuracy, which is, respectively, 10 and 2% higher than the recently published tool FLASH. When COPE is applied to real reads for genome assembly, the resulting contigs are found to have fewer errors and give a 14-fold improvement in the N50 measurement when compared with the contigs produced using unconnected reads.</span></p><p>Address of the bookmark: <a href="ftp://ftp.genomics.org.cn/pub/cope" rel="nofollow">ftp://ftp.genomics.org.cn/pub/cope</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/40882/troyanskaya-lab</guid>
  <pubDate>Tue, 04 Feb 2020 06:40:36 -0600</pubDate>
  <link></link>
  <title><![CDATA[Troyanskaya Lab]]></title>
  <description><![CDATA[
<p>The goal of our research is to interpret and distill this complexity through accurate analysis and modeling of molecular pathways, particularly those in which malfunctions lead to the manifestation of disease. We are inventing integrative methods for systems-level pathway modeling through integrative analysis of genome-scale datasets. We apply these approaches in studying challenging biological problems, such as how pathways function in diverse cell types and how they change dynamically.</p>

<p>https://function.princeton.edu/</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/2518/genome-browsers</guid>
	<pubDate>Fri, 16 Aug 2013 19:04:47 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/2518/genome-browsers</link>
	<title><![CDATA[Genome Browsers]]></title>
	<description><![CDATA[<p>Genome Browser is the platform/database used for searching and retreiving sequences and annotation of genomes belong to various eukaryotes, prokaryotes, etc.</p><p>Following are the weblink for different available browsers:</p><p><a href="http://www.ensembl.org/index.html">http://www.ensembl.org/index.html</a></p><p><a href="http://ensemblgenomes.org/">http://ensemblgenomes.org/</a></p><p><a href="http://genome.ucsc.edu/">http://genome.ucsc.edu/</a></p><p><a href="http://www.ncbi.nlm.nih.gov/genome">http://www.ncbi.nlm.nih.gov/genome</a></p><p><a href="http://www.ebi.ac.uk/genomes/">http://www.ebi.ac.uk/genomes/</a></p><p><a href="http://flybase.org/">http://flybase.org/</a></p><p><a href="http://cmr.jcvi.org/tigr-scripts/CMR/CmrHomePage.cgi">http://cmr.jcvi.org/tigr-scripts/CMR/CmrHomePage.cgi</a></p><p><a href="http://www.sanger.ac.uk/resources/databases/">http://www.sanger.ac.uk/resources/databases/</a></p>]]></description>
	<dc:creator>Rahul Agarwal</dc:creator>
</item>

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