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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/45278?</link>
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	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/videolist/watch/20454/comparative-genomics-in-ensembl</guid>
	<pubDate>Wed, 21 Jan 2015 08:31:11 -0600</pubDate>
	<link>https://bioinformaticsonline.com/videolist/watch/20454/comparative-genomics-in-ensembl</link>
	<title><![CDATA[Comparative Genomics in Ensembl]]></title>
	<description><![CDATA[<iframe width="" height="" src="https://www.youtube-nocookie.com/embed/dDRdCnZOMCM" frameborder="0" allowfullscreen></iframe>The Ensembl browser provides viewable whole-genome alignments, homologues and phylogenetic gene trees, protein families, and ancestral sequences.  Learn how to view and export these data in this video.]]></description>
	
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<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/26525/ensembl-comparative-genomics-resources</guid>
	<pubDate>Sun, 28 Feb 2016 17:10:20 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/26525/ensembl-comparative-genomics-resources</link>
	<title><![CDATA[Ensembl comparative genomics resources]]></title>
	<description><![CDATA[<div>
<p>The Ensembl comparative genomics resources are one such reference set that facilitates comprehensive and reproducible analysis of chordate genome data. Ensembl computes pairwise and multiple whole-genome alignments from which large-scale synteny, per-base conservation scores and constrained elements are obtained. Gene alignments are used to define Ensembl Protein Families, GeneTrees and homologies for both protein-coding and non-coding RNA genes. These resources are updated frequently and have a consistent informatics infrastructure and data presentation across all supported species. Specialized web-based visualizations are also available including synteny displays, collapsible gene tree plots, a gene family locator and different alignment views. The Ensembl comparative genomics infrastructure is extensively reused for the analysis of non-vertebrate species by other projects including Ensembl Genomes and Gramene and much of the information here is relevant to these projects. The consistency of the annotation across species and the focus on vertebrates makes Ensembl an ideal system to perform and support vertebrate comparative genomic analyses. We use robust software and pipelines to produce reference comparative data and make it freely available.</p>
<p><strong>Database URL:</strong> <a href="http://www.ensembl.org" target="pmc_ext">http://www.ensembl.org</a>.</p>
</div><p>Address of the bookmark: <a href="http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4761110/" rel="nofollow">http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4761110/</a></p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/29683/method-in-comparative-genomics</guid>
	<pubDate>Wed, 09 Nov 2016 16:29:24 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/29683/method-in-comparative-genomics</link>
	<title><![CDATA[Method in Comparative genomics !!]]></title>
	<description><![CDATA[<p>We present methods for the automatic determination of genome correspondence. The algorithms enabled the automatic identification of orthologs for more than 90% of genes and intergenic regions across the four species despite the large number of duplicated genes in the yeast genome. The remaining ambiguities in the gene correspondence revealed recent gene family expansions in regions of rapid genomic change.</p>
<p>We present methods for the identification of protein-coding genes based on their patterns of nucleotide conservation across related species. We observed the pressure to conserve the reading frame of functional proteins and developed a test for gene identification with high sensitivity and specificity. We used this test to revisit the genome of S. cerevisiae, reducing the overall gene count by 500 genes (10% of previously annotated genes) and refining the gene structure of hundreds of genes. We present novel methods for the systematic de novo identification of regulatory motifs. The methods do not rely on previous knowledge of gene function and in that way differ from the current literature on computational motif discovery. Based on the genome-wide conservation patterns of known motifs, we developed three conservation criteria that we used to discover novel motifs. We used an enumeration approach to select strongly conserved motif cores, which we extended and collapsed into a small number of candidate regulatory motifs. These include most previously known regulatory motifs as well as several noteworthy novel motifs. The majority of discovered motifs are enriched in functionally related genes, allowing us to infer a candidate function for novel motifs.</p>
<p>Our results demonstrate the power of comparative genomics to further our understanding of any species. Our methods are validated by the extensive experimental knowledge in yeast, and will be invaluable in the study of complex genomes like that of human.</p><p>Address of the bookmark: <a href="http://web.mit.edu/manoli/www/publications/Kellis_JCB_04.pdf" rel="nofollow">http://web.mit.edu/manoli/www/publications/Kellis_JCB_04.pdf</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34328/dfast-a-flexible-prokaryotic-genome-annotation-pipeline-for-faster-genome-publication</guid>
	<pubDate>Tue, 14 Nov 2017 10:26:16 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34328/dfast-a-flexible-prokaryotic-genome-annotation-pipeline-for-faster-genome-publication</link>
	<title><![CDATA[DFAST: a flexible prokaryotic genome annotation pipeline for faster genome publication]]></title>
	<description><![CDATA[<p>We developed a prokaryotic genome annotation pipeline, DFAST, that also supports genome submission to public sequence databases. DFAST was originally started as an on-line annotation server, and to date, over 7,000 jobs have been processed since its first launch in 2016. Here, we present a newly implemented background annotation engine for DFAST, which is also available as a standalone command-line program. The new engine can annotate a typical-sized bacterial genome within 10 minutes, with rich information such as pseudogenes, translation exceptions, and orthologous gene assignment between given reference genomes. In addition, the modular framework of DFAST allows users to customize the annotation workflow easily and will also facilitate extensions for new functions and incorporation of new tools in the future.</p>
<div>Availability and Implementation</div>
<p>The software is implemented in Python 3 and runs in both Python 2.7 and 3.4&ndash; on Macintosh and Linux systems. It is freely available at&nbsp;<a href="https://github.com/nigyta/dfast_core/" target="">https://github.com/nigyta/dfast_core/</a>&nbsp;under the GPLv3 license with external binaries bundled in the software distribution. An on-line version is also available at&nbsp;<a href="https://dfast.nig.ac.jp/" target="">https://dfast.nig.ac.jp/</a>.</p><p>Address of the bookmark: <a href="https://dfast.nig.ac.jp/" rel="nofollow">https://dfast.nig.ac.jp/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36954/mscaffolder-a-comparative-genome-scaffolding-tool</guid>
	<pubDate>Fri, 15 Jun 2018 04:48:01 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36954/mscaffolder-a-comparative-genome-scaffolding-tool</link>
	<title><![CDATA[mScaffolder: A comparative genome scaffolding tool]]></title>
	<description><![CDATA[<p>A comparative genome scaffolding tool based on MUMmer</p>
<p>mScaffolder scaffolds a genome using an existing high quality genome as the reference. It aligns the two genomes using nucmer utility from MUMmer and then orders and orients the contigs of the candidate genome guided by their alignments to the reference genome. Please send your questions and comments to&nbsp;<a href="mailto:mchakrab@uci.edu">mchakrab@uci.edu</a>.</p>
<p><span>Citation</span><span>&nbsp;</span><a href="https://www.nature.com/articles/s41588-017-0010-y">https://www.nature.com/articles/s41588-017-0010-y</a></p><p>Address of the bookmark: <a href="https://github.com/mahulchak/mscaffolder" rel="nofollow">https://github.com/mahulchak/mscaffolder</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43711/vcf-compare</guid>
	<pubDate>Wed, 19 Jan 2022 10:30:14 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43711/vcf-compare</link>
	<title><![CDATA[VCF Compare !]]></title>
	<description><![CDATA[<h2><span>compare two&nbsp;<strong>BWA</strong>&nbsp;mapping methods with the online hg18-mapped data</span></h2>
<p>We first operate a rapid inspection of the different BAM files using&nbsp;<strong>samtools flagstat</strong>. Illumina provided chr21 read mapping obtained with their&nbsp;<strong>GA IIx</strong>&nbsp;deep sequencing platform &lt;<a href="ftp://webdata:webdata@ussd-ftp.illumina.com/Data/SequencingRuns/NA18507_GAIIx_100_chr21.bam" target="_blank">ftp://webdata:webdata@ussd-ftp.illumina.com/Data/SequencingRuns/NA18507_GAIIx_100_chr21.bam</a>&gt;, aligned to the b36/hg18 reference genome)</p><p>Address of the bookmark: <a href="https://wiki.bits.vib.be/index.php/NGS_Exercise.6#compare_aln_.26_mem_results_with_vcf-compare" rel="nofollow">https://wiki.bits.vib.be/index.php/NGS_Exercise.6#compare_aln_.26_mem_results_with_vcf-compare</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/19636/google-genomics</guid>
	<pubDate>Thu, 18 Dec 2014 11:05:42 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/19636/google-genomics</link>
	<title><![CDATA[Google Genomics]]></title>
	<description><![CDATA[<ul>
<li>
<p><strong>Explore genetic variation interactively.</strong> Compare entire cohorts in seconds with SQL-like queries. Compute transition/transversion ratios, genome-wide association, allelic frequency and more.</p>
</li>
<li>
<p><strong>Process big genomic data easily.</strong> Run batch analyses like principal component analysis and Hardy-Weinberg equilibrium on as many samples as you like, in minutes or hours, with just a little code.</p>
</li>
<li>
<p><strong>Use Google's infrastructure and big data expertise.</strong> Store one genome or a million using Google Genomics and take advantage of the same infrastructure that powers Search, Maps, YouTube, Gmail and Drive.</p>
</li>
<li>
<p><strong>Support emerging global standards.</strong> Google Genomics is implementing the API defined by the Global Alliance for Genomics and Health for visualization, analysis and more. Compliant software can access Google Genomics, local servers, or any other implementation.</p>
</li>
</ul><p>Address of the bookmark: <a href="https://cloud.google.com/genomics/" rel="nofollow">https://cloud.google.com/genomics/</a></p>]]></description>
	<dc:creator>Tenzin Paul</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41604/synteny-and-rearrangement-identifier-syri</guid>
	<pubDate>Tue, 05 May 2020 10:37:10 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41604/synteny-and-rearrangement-identifier-syri</link>
	<title><![CDATA[Synteny and Rearrangement Identifier (SyRI)]]></title>
	<description><![CDATA[<p>SyRI is a comprehensive tool for predicting genomic differences between related genomes using whole-genome assemblies (WGA). The assemblies are aligned using whole-genome alignment tools, and these alignments are then used as input to SyRI. SyRI identifies syntenic path (longest set of co-linear regions), structural rearrangements (inversions, translocations, and duplications), local variations (SNPs, indels, CNVs etc) within syntenic and structural rearrangements, and un-aligned regions.</p><p>Address of the bookmark: <a href="https://schneebergerlab.github.io/syri/" rel="nofollow">https://schneebergerlab.github.io/syri/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/43559/job-offer-for-a-postdoctoral-researcher-in-genomics-bioinformatics-2-years</guid>
  <pubDate>Fri, 22 Oct 2021 04:44:33 -0500</pubDate>
  <link></link>
  <title><![CDATA[Job offer for a postdoctoral researcher in genomics / bioinformatics (2 years)]]></title>
  <description><![CDATA[
<p>Ongoing research in the group of Karine Van Doninck involves topics at the core of<br />evolutionary biology, including the evolution of sex, genome maintenance,<br />recombination and extreme stress resistance on different eukaryotic systems,<br />including rotifers, amoeba and Corbicula clams. We are employing different tools<br />(including experimental ecology, population genetics, phylogeny, comparative<br />genomics, transcriptomics, bioinformatics, molecular and cellular biology) to study<br />evolutionary processes at the level of populations, both experimental and natural, and<br />genomes.</p>

<p>Offer<br />We offer a full-time contract for two years. The contract starts between October 2021<br />and December 2021. The position involves no or extremely light teaching load, if the<br />candidate is interested. Salaries are competitive at the European level. The recruited<br />person will benefit from the Belgian social insurance scheme (health care, etc.) without<br />additional expenses.</p>

<p>Profile<br />Applicants are expected to show outstanding commitment to research and must have<br />obtained a PhD by the start of the position. A strong expertise in genomics is required.<br />More specifically, solid competences in bioinformatics (e.g. scripting pipelines) and in<br />genome evolution are needed. Knowledge or interest regarding recombination,<br />metazoan evolution, phylogenomics and population genomics is an added-value.</p>

<p>Application<br />Applications should be submitted via email to karine.van.doninck@ulb.be. The<br />application package should contain the following documents:<br />- A curriculum vitae with the complete list of publications<br />- A cover letter mentioning why the candidate is interested in the position<br />- Minimum 2 recommendation letters<br />Interviews: Interviews will be conducted with the selected candidates. Selected<br />candidates could also be invited to give a seminar to MBE ULB.<br />For any additional information, please contact karine.van.doninck@ulb.be</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/26993/lastz</guid>
	<pubDate>Mon, 18 Apr 2016 04:41:55 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/26993/lastz</link>
	<title><![CDATA[LASTZ]]></title>
	<description><![CDATA[<p>LASTZ is a program for aligning DNA sequences, a pairwise aligner. Originally designed to handle sequences the size of human chromosomes and from different species, it is also useful for sequences produced by NGS sequencing technologies such as Roche 454.</p>
<p>More at http://www.bx.psu.edu/~rsharris/lastz/</p>
<p>Thesis: http://www.bx.psu.edu/~rsharris/rsharris_phd_thesis_2007.pdf</p><p>Address of the bookmark: <a href="http://www.bx.psu.edu/~rsharris/lastz/" rel="nofollow">http://www.bx.psu.edu/~rsharris/lastz/</a></p>]]></description>
	<dc:creator>Abhi</dc:creator>
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