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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/45270?offset=50</link>
	<atom:link href="https://bioinformaticsonline.com/related/45270?offset=50" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
	
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/42326/edanchin-lab</guid>
  <pubDate>Thu, 19 Nov 2020 08:00:07 -0600</pubDate>
  <link></link>
  <title><![CDATA[Edanchin Lab]]></title>
  <description><![CDATA[
<p>My main topics of interest are:</p>

<p>The impact of non tree-like evolution such as horizontal gene transfers and hybridization on species biology<br />Evolution and adaptation of animals in the absence of sexual reproduction and the underlying mechanisms<br />Genomic signatures of adaptation to a parasitic life-style</p>

<p>More at https://edanchin.org/</p>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/44700/professorsenior-lecturer-of-comparative-genomics-university-of-glasgow</guid>
  <pubDate>Fri, 06 Dec 2024 05:16:09 -0600</pubDate>
  <link></link>
  <title><![CDATA[Professor/Senior Lecturer of Comparative Genomics @ University of Glasgow]]></title>
  <description><![CDATA[
<p>University of Glasgow<br />College of Medical, Veterinary and Life Sciences<br />School of Biodiversity, One Health and Veterinary Medicine</p>

<p>Professor/Senior Lecturer of Comparative Genomics<br />Vacancy Ref: 153610<br />Salary: Professor, Grade 10 will be within the Professorial range and<br />subject to negotiation<br />Senior Lecturer, Grade 9, 57,696 - 64,914 per annum</p>

<p>The School of Biodiversity, One Health and Veterinary Medicine has an<br />exciting opportunity to appoint a Professor/Senior Lecturer in Comparative<br />Genomics. You will make a substantial and positive contribution to the<br />strategic direction of the School/College through leading and contributing<br />to research of international standard, high quality teaching at both<br />undergraduate and postgraduate level, securing research funding, and<br />providing academic leadership and management within the School/College.</p>

<p>Applications are invited from candidates of international standing with<br />an appropriate record of academic achievement in comparative genomics<br />and associated omics technologies. We are looking for a candidate who<br />will complement our existing strengths in clinical veterinary medicine,<br />evolutionary biology, and animal physiology, with a demonstrable interest<br />in using domestic mammals among their study systems. We are particularly<br />interested in applications from candidates with a track record of<br />studying health related traits and their underlying genomic basis in<br />companion animals. Traits of specific interest include those related<br />to metabolism, ageing, and disease (e.g. cancer, autoimmune diseases,<br />neuromuscular disorders).</p>

<p>The School of Biodiversity, One Health and Veterinary Medicine is home to<br />researchers studying organismal biology and animal health across a diverse<br />range of systems, approaches and disciplines with existing strengths<br />in infectious disease, physiology, ageing, veterinary epidemiology, and<br />evolution among others. You will be based on the University of Glasgow's<br />Garscube campus, where the majority of veterinary teaching and research<br />infrastructure is located. This includes the Small Animal Hospital (a<br />recent 15M investment) and our Veterinary Diagnostic Services, offering<br />excellent opportunities for collaborative research at the clinical and<br />translational interface, especially with respect to companion animals.</p>

<p>We welcome applications from candidates with a Scottish Credit and<br />Qualification Framework level 12 (PhD) in animal biology, genomics and<br />health or related discipline with an extensive and established reputation<br />in research and significant teaching experience within the subject area.</p>

<p>This post is full time and open ended.</p>

<p>Visit our website for further information on The University of<br />Glasgow's, School of Biodiversity, One Health &amp; Veterinary Medicine,<br />https://www.gla.ac.uk/schools/bohvm/</p>

<p>Informal Enquiries should be directed to Professor Roman Biek,<br />Roman.Biek@glasgow.ac.uk</p>

<p>Apply online at:<br />https://my.corehr.com/pls/uogrecruit/erq_jobspec_version_4.jobspec?p_id=153610</p>
]]></description>
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<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27333/satsuma-highly-sensitive-whole-genome-synteny-alignments</guid>
	<pubDate>Fri, 13 May 2016 05:25:26 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27333/satsuma-highly-sensitive-whole-genome-synteny-alignments</link>
	<title><![CDATA[SATSUMA : Highly sensitive whole-genome synteny alignments.]]></title>
	<description><![CDATA[<p>Satsuma is a whole-genome synteny alignment program. It takes two genomes, computes alignments, and then keeps only the parts that are orthologous, i.e. following the conserved order and orientation of features, such as protein coding genes, non-coding genes, or neutral sequences. Satsuma does not require any pre-processing, such as repeat masking, since it will automatically detect ambiguous mappings.<br> <br> Satsuma has parallelization built-in and is designed to run on multi-core architectures. The run-time for aligning two bird-size genomes (~1.2 Gb) is around two days on 24 CPUs. <br> <br> You can find the manual <a href="http://satsuma.sourceforge.net/manual.html">here</a>.<br> Download the latest source code from <a href="https://sourceforge.net/projects/satsuma/">here.</a><br> Stable versions can also be downloaded from the <a href="https://www.broadinstitute.org/science/programs/genome-biology/spines">Broad Institute's</a> web site.<br> <br> An incomplete list of questions and answers (yes, these have really been asked by our users! Please feel free to add your own by e-mailing us) is <a href="http://satsuma.sourceforge.net/faq.html">here</a>.<br> <br> If you use Satsuma in your research, please cite:<br> <a href="http://bioinformatics.oxfordjournals.org/content/26/9/1145.long">Grabherr, M. G., Russell, P., Meyer, M., Mauceli, E., Alf&ouml;ldi, J., Di Palma, F., &amp; Lindblad-Toh, K. (2010). Genome-wide synteny through highly sensitive sequence alignment: Satsuma. Bioinformatics, 26(9), 1145-51</a>.</p>
<p><strong>Tutorial at http://evomics.org/learning/genomics/satsuma/</strong></p><p>Address of the bookmark: <a href="http://satsuma.sourceforge.net/" rel="nofollow">http://satsuma.sourceforge.net/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/30102/prism</guid>
	<pubDate>Sat, 10 Dec 2016 15:19:40 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/30102/prism</link>
	<title><![CDATA[PRISM]]></title>
	<description><![CDATA[<p><span>PRISM is a software for split read (reads which span across a structrual variant -- SV ) mapping and SV calling from the mapping result. PRISM is able to detect small insertions and abitrary size deletions, inversions and tandom duplications with the direction of discordant read pairs. PRISM_CTX is a tool for detecting inter-chromosome trans-location events.&nbsp;</span><br><br><span>PRISM and PRISM_CTX were originally designed and written by&nbsp;</span><a href="http://www.cs.toronto.edu/~brudno">Michael Brudno</a><span>&nbsp;and Yue Jiang, The original PRISM publication can be found&nbsp;</span><a href="http://bioinformatics.oxfordjournals.org/content/early/2012/07/31/bioinformatics.bts484.abstract">here</a><span>.&nbsp;</span><br><br><span>The authors may be contacted via e-mail at:&nbsp;</span><em>prism at cs.toronto.edu</em><span>.&nbsp;</span><br><br><span>Additional information is available in the&nbsp;</span><a href="http://compbio.cs.toronto.edu/prism/PRISM_README">PRISM README</a><span>&nbsp;file and&nbsp;</span><a href="http://compbio.cs.toronto.edu/prism/PRISM_CTX_README">PRISM_CTX README</a><span>&nbsp;file.&nbsp;</span></p>
<p>http://compbio.cs.toronto.edu/prism/</p><p>Address of the bookmark: <a href="http://compbio.cs.toronto.edu/prism/" rel="nofollow">http://compbio.cs.toronto.edu/prism/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/45278/the-day-we-began-reading-the-dna-of-the-world</guid>
	<pubDate>Sat, 05 Sep 2026 01:43:21 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/45278/the-day-we-began-reading-the-dna-of-the-world</link>
	<title><![CDATA[The Day We Began Reading the DNA of the World]]></title>
	<description><![CDATA[<div>Picture waking up and knowing that in one lab, a scientist is reading the DNA of a whale. In another, a team is sequencing a rare plant. Meanwhile, researchers in India are decoding the genomes of different human populations.</div><div>&nbsp;</div><div>Many organisms. Many countries. All share one remarkable goal: to understand the genetic story of life.</div><div>DNA is nature's instruction manual, written with just four letters: A, T, C, and G. For years, scientists could only read small sections of this huge book. Now, new sequencing technology lets us read entire genomes like never before.</div><div>&nbsp;</div><div>One of the most ambitious projects is the Earth BioGenome Project (EBP). Its goal is to create reference genomes for about 1.5 million known eukaryotic species. This project links genome research across continents, species, and scientific fields.</div><div>&nbsp;</div><div>But this story goes beyond just animals and plants.</div><div>&nbsp;</div><div><strong>A New Chapter in Human Genomics</strong></div><div>&nbsp;</div><div>Large human genome projects are changing how we understand our own genetic diversity.</div><div>India's GenomeIndia project has sequenced thousands of people from different populations. This work is uncovering genetic variation that global databases have often missed.</div><div>&nbsp;</div><div>Similar population-scale effSimilar large-scale projects are happening worldwide. The All of Us Research Program in the United States, Europe's 1+ Million Genomes initiative, South Korea's national genomic data program, and projects in Saudi Arabia, Australia, and Singapore are all building huge genomic resources.collect DNA.</div><div>&nbsp;</div><div>The real goal is to link genomes with health, disease, and other biological information. This creates a base for more accurate research and, in time, more personalized medicine.</div><div>&nbsp;</div><div><strong>A Race Against Time</strong></div><div>&nbsp;</div><div>There is also an important twist.</div><div>&nbsp;</div><div>We are sequencing Earth's biodiversity even as many species face growing environmental threats.</div><div>A genome alone cannot save a species, but it does keep important information about its biology, evolution, and genetic diversity. This knowledge helps scientists understand risks, guide conservation, and find traits that could help agriculture or medicine.</div><div>&nbsp;</div><div>Projects like the Darwin Tree of Life, which studies species in Britain and Ireland, and the African BioGenome Project, which is growing genomics work across Africa, are key parts of this worldwide effort.</div><div>&nbsp;</div><div>Projects to Watch</div><ol>
<li>Earth BioGenome Project (EBP) - A global effort to sequence and annotate roughly 1.5 million known eukaryotic species and create a comprehensive reference library of Earth's biodiversity.</li>
<li>Vertebrate Genomes Project (VGP) - Focuses on producing high-quality reference genomes for vertebrate species, providing a major foundation for the wider Tree of Life.</li>
<li>Darwin Tree of Life - A UK and Ireland initiative aiming to sequence approximately 70,000 species, creating a detailed genomic map of regional biodiversity.</li>
<li>African BioGenome Project (AfricaBP) - A pan-African initiative focused on sequencing Africa's biodiversity while strengthening genomics and bioinformatics capacity across the continent.</li>
<li>European Reference Genome Atlas (ERGA) - A European effort to generate high-quality reference genomes for Europe's biodiversity and connect national sequencing efforts.</li>
<li>Canada BioGenome Project - Building reference genomes for Canadian biodiversity, supporting conservation, research and the study of ecosystems.</li>
<li>California Conservation Genomics Project - Uses genomics to understand and protect California's biodiversity and help inform conservation decisions.</li>
<li>Bat1K - An ambitious global effort to sequence the genomes of all known bat species, helping scientists study their evolution, longevity, immunity and unique biology.</li>
<li>Bird 10,000 (B10K) - A global project aiming to create genome resources covering the world's bird diversity and reconstruct avian evolutionary history.</li>
<li>Global Invertebrate Genomics Alliance (GIGA) - Builds genomic resources for the enormous and genetically diverse world of invertebrates.</li>
<li>GenomeIndia - India's national human-genome initiative, designed to capture the country's extraordinary population diversity and create a reference resource for Indian genomics.</li>
<li>All of Us Research Program - A US national research program combining genomic information with health and lifestyle data at population scale.</li>
<li>1+ Million Genomes / Genome of Europe - A European effort to enable secure, cross-border use of genomic and health data and develop genome-scale resources involving more than one million people.</li>
<li>Korea National Integrated Bio Big Data Project - South Korea's large-scale national effort combining genomic and health information from a very large population cohort.</li>
<li>Saudi Genome Program - A national genomics initiative focused on genetic diseases, population genomics and precision medicine in Saudi Arabia.</li>
<li>Australian Genomics / Genomics Health Futures Mission - Australia's growing investment in genomic medicine, rare disease research and population-scale health genomics.</li>
</ol><div><strong>The Library of Life</strong></div><div>&nbsp;</div><div>The fuThe future of genomics is not just about sequencing one genome at a time. Now, it is about creating a worldwide network of genomes&mdash;human and non-human, individual and species&mdash;linked by powerful databases and advanced computational tools.ine a library without shelves.</div><div>&nbsp;</div><div>In this library, the books are genomes. The pages are made of DNA. Scientists and machines are the readers. And this library is still being written. Each genome sequenced today adds a new page to the story of life and helps us better understand our place in it.</div>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/19087/dcgor</guid>
	<pubDate>Sat, 08 Nov 2014 14:54:28 -0600</pubDate>
	<link>https://bioinformaticsonline.com/news/view/19087/dcgor</link>
	<title><![CDATA[dcGOR]]></title>
	<description><![CDATA[<p>An R package for analysing ontologies and protein domain annotations has been published in PLoS Computational Biology (http://dx.doi.org/10.1371/journal.pcbi.1003929). The package is distributed as part of CRAN (http://cran.r-project.org/package=dcGOR), and also at GitHub for version control.<br /><br />The dedicated website is available in http://supfam.org/dcGOR, from which several demos are also provided:<br /><br />1. Analysing SCOP domains: http://supfam.org/dcGOR/demo-Fang.html<br /><br />2. Analysing Pfam domains: http://supfam.org/dcGOR/demo-Basu.html<br /><br />3. Analysing InterPro domains: http://supfam.org/dcGOR/demo-Customisation.html<br /><br />&nbsp;</p>]]></description>
	<dc:creator>Martin Jones</dc:creator>
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<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27090/canu-assembling-large-genomes-with-single-molecule-sequencing-and-locality-sensitive-hashing</guid>
	<pubDate>Tue, 26 Apr 2016 11:38:10 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27090/canu-assembling-large-genomes-with-single-molecule-sequencing-and-locality-sensitive-hashing</link>
	<title><![CDATA[CANU: Assembling Large Genomes with Single-Molecule Sequencing and Locality Sensitive Hashing.]]></title>
	<description><![CDATA[<p>Canu is a fork of the&nbsp;<a href="http://wgs-assembler.sourceforge.net/wiki/index.php?title=Main_Page" title="Celera Assembler">Celera Assembler</a>&nbsp;designed for high-noise single-molecule sequencing (such as the PacBio RSII or Oxford Nanopore MinION). The software is currently alpha level, feel free to use and report issues encountered.</p>
<p>Canu is a hierachical assembly pipeline which runs in four steps:</p>
<ul>
<li>Detect overlaps in high-noise sequences using&nbsp;<a href="https://github.com/marbl/MHAP" title="MHAP">MHAP</a></li>
<li>Generate corrected sequence consensus</li>
<li>Trim corrected sequences</li>
<li>Assemble trimmed corrected sequences</li>
</ul>
<p>Read the&nbsp;<a href="http://canu.readthedocs.org/" title="docs">documentation</a></p>
<p>New release https://github.com/marbl/canu/releases</p><p>Address of the bookmark: <a href="https://github.com/marbl/canu" rel="nofollow">https://github.com/marbl/canu</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/27344/orffinder-with-smart-blast</guid>
	<pubDate>Tue, 17 May 2016 01:43:15 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/27344/orffinder-with-smart-blast</link>
	<title><![CDATA[ORFfinder with smart BLAST]]></title>
	<description><![CDATA[<p><span>ORF Finder</span></p><p><span><a href="http://www.ncbi.nlm.nih.gov/orffinder">ORFfinder</a><span>&nbsp;is a graphical analysis tool for finding open reading frames (ORFs). We&rsquo;ve been working on a few updates, and we&rsquo;d like to find out what you think about them. Read on to find out what you can do with the new ORFfinder.</span></span></p><p>Smart BLAST (https://ncbiinsights.ncbi.nlm.nih.gov/2015/07/29/smartblast/)</p><p>Select one or a group of ORFs and BLAST several databases at once, and use the newly developed&nbsp;<a href="http://blast.ncbi.nlm.nih.gov/smartblast/">SmartBLAST</a>&nbsp;to verify protein names.&nbsp;Looking for the traditional results from&nbsp;<a href="http://blast.ncbi.nlm.nih.gov/Blast.cgi">BLAST</a>? They&rsquo;re there too.</p>]]></description>
	<dc:creator>Jit</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/27799/bbmapbbtools-package-multipurpose-tool-designed-for-converting-reads-or-other-nucleotide-data-between-different-formats</guid>
	<pubDate>Mon, 13 Jun 2016 05:47:21 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/27799/bbmapbbtools-package-multipurpose-tool-designed-for-converting-reads-or-other-nucleotide-data-between-different-formats</link>
	<title><![CDATA[BBMap/BBTools package: Multipurpose tool designed for converting reads or other nucleotide data between different formats.]]></title>
	<description><![CDATA[<div id="post_message_148585"><a href="https://sourceforge.net/projects/bbmap/" target="_blank">Reformat</a>is a member of the <a href="https://sourceforge.net/projects/bbmap/" target="_blank">BBMap/BBTools package</a>. It is a multipurpose tool designed for converting reads or other nucleotide data between different formats. It supports, and can inter-convert:<br /> <br /> fastq<br /> fasta<br /> fasta+qual<br /> sam<br /> scarf (an old Illumina format)<br /> bam (if samtools is installed)<br /> gzip<br /> zip<br /> ascii-33 (sanger)<br /> ascii-64 (old Illumina)<br /> paired files<br /> interleaved files<br /> <br /> It is multithreaded and can process data at over 500 megabytes per second, and can accept streams from standard in and write to standard out, allowing it to be easily dropped into the middle of a pipeline for format conversion. Reformat autodetects formats based on file extensions and content, making it very easy to use; and the autodetection can be overridden, allowing flexibility for people who don't like to follow naming conventions, or out-of-spec fastq files with qualities values like -17 or 120.<br /> <br /> The program has been gradually expanded, and can now perform various other functions. None of these will break pairing, if the input is paired.<br /> <br /> Quality trimming (either or both ends)<br /> Quality filtering<br /> Fixed-length trimming<br /> Generation of histograms (base composition, quality, etc)<br /> Subsampling (to a fraction of input reads, or an exact number of reads or bases)<br /> Changing fasta line-wrapping length<br /> Reverse-complementing (all reads or only read 2)<br /> Adding /1 and /2 suffix to read names<br /> GC-content filtering<br /> Length-filtering<br /> Testing for corrupted interleaved files<br /> <br /> Reformat is compatible with any platform that supports Java 1.7 or higher. It also has a bash shellscript for simpler invocation. Typical usage examples:<br /> <br /> Reformat fastq into fasta:<br /> <strong>reformat.sh in=x.fq out=y.fa</strong><br /> <br /> Interleave paired reads:<br /> <strong>reformat.sh in1=x1.fq in2=x2.fq out=y.fq</strong><br /> <br /> Note - you can actually use a shortcut if paired read files have the same name with a 1 and a 2. This is equivalent to the above command:<br /> <strong>reformat.sh in=x#.fq out=y.fq</strong><br /> <br /> De-interleave reads:<br /> <strong>reformat.sh in=x.fq out1=y1.fq out2=y2.fq</strong><br /> <br /> Verify that interleaving appears correct, assuming Illumina namimg conventions:<br /> <strong>reformat.sh in=x.fq vint</strong><br /> <br /> Convert ASCII-33 to ASCII-64:<br /> <strong>reformat.sh in=x.fq out=y.fq qin=33 qout=64</strong><br /> <br /> Quality-trim paired reads to Q10 on the left and right ends and discard reads shorter than 50bp after trimming:<br /> <strong>reformat.sh in1=x1.fq in2=x2.fq out1=y1.fq out2=y2.fq outsingle=singletons.fq qtrim=rl trimq=10 minlength=50</strong><br /> <br /> Subsample 10% of the first 20000 pairs in an interleaved file:<br /> <strong>reformat.sh in=x.fq out=y.fq reads=20000 samplerate=0.1 int=t</strong><br /> (in this case "int=t" overrides interleaving autodetection, to ensure reads are treated as pairs)<br /> <br /> Pipe in a gzipped sam file and pipe out fasta:<br /> <strong>reformat.sh in=stdin.sam.gz out=stdout.fa</strong><br /> <br /> Reverse-complement reads:<br /> <strong>reformat.sh in=x.fq out=y.fq rcomp</strong><br /> <br /> For reformatting a file with very long sequences, Reformat will need more memory; just add the additional flag "-Xmx2g". For example, to change the line-wrapping length on the human genome (which has individual sequences over 200Mbp long) to 70 characters:<br /> <strong>reformat.sh -Xmx2g in=HG19.fa.gz out=HG19_wrapped.fa.gz fastawrap=70</strong><br /> <br /> For additional functions, please run the shellscript with no arguments, or just read it with a text editor. If you have any questions, please post them in this thread.<br /> <br /> For people using a non-bash terminal, you may need to type "bash reformat.sh" instead of just "reformat.sh".<br /> For users of Windows or other platforms that do not support bash shellscripts, replace "reformat.sh" with "java -ea -Xmx200m /path/to/bbmap/current/ jgi.ReformatReads"<br /> for example,<br /> <strong>java -ea -Xmx200m C:\bbmap\current\ jgi.ReformatReads in=x.fq out=y.fa</strong><br /> <br /> Reformat can be downloaded with BBTools here:<br /> <a href="https://sourceforge.net/projects/bbmap/" target="_blank">https://sourceforge.net/projects/bbmap/</a></div>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/30375/mauve-a-system-for-constructing-multiple-genome-alignments-in-the-presence-of-large-scale-evolutionary-events-such-as-rearrangement-and-inversion</guid>
	<pubDate>Sat, 24 Dec 2016 09:20:53 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/30375/mauve-a-system-for-constructing-multiple-genome-alignments-in-the-presence-of-large-scale-evolutionary-events-such-as-rearrangement-and-inversion</link>
	<title><![CDATA[Mauve: a system for constructing multiple genome alignments in the presence of large-scale evolutionary events such as rearrangement and inversion]]></title>
	<description><![CDATA[<p>Mauve is a system for constructing multiple genome alignments in the presence of large-scale evolutionary events such as rearrangement and inversion. Multiple genome alignments provide a basis for research into comparative genomics and the study of genome-wide evolutionary dynamics.</p>
<p>Mauve has been developed with the idea that a multiple genome aligner should require only modest computational resources. It employs algorithmic techniques that scale well in the lengths of sequences being aligned. For example, a pair of&nbsp;<em>Y. pestis</em>&nbsp;genomes can be aligned in under a minute, while a group of 9 divergent Enterobacterial genomes can be aligned in a few hours. However, the current algorithm&rsquo;s compute time (progressiveMauve) scales cubically in the number of genomes to align, making it unsuitable for datasets containing more than 50-100 bacterial genomes.</p><p>Address of the bookmark: <a href="http://darlinglab.org/mauve/mauve.html" rel="nofollow">http://darlinglab.org/mauve/mauve.html</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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