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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/41604?offset=360</link>
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	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40834/nucleus-python-and-c-code-for-reading-and-writing-genomics-data</guid>
	<pubDate>Sun, 02 Feb 2020 08:14:19 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40834/nucleus-python-and-c-code-for-reading-and-writing-genomics-data</link>
	<title><![CDATA[Nucleus: Python and C++ code for reading and writing genomics data.]]></title>
	<description><![CDATA[<p>Nucleus is a library of Python and C++ code designed to make it easy to read, write and analyze data in common genomics file formats like SAM and VCF. In addition, Nucleus enables painless integration with the TensorFlow machine learning framework, as anywhere a genomics file is consumed or produced, a TensorFlow tfrecords file may be used instead.</p><p>Address of the bookmark: <a href="https://github.com/google/nucleus" rel="nofollow">https://github.com/google/nucleus</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/42793/fully-funded-position-as-phd-research-fellow-in-genomicsbioinformatics</guid>
  <pubDate>Wed, 03 Feb 2021 04:18:57 -0600</pubDate>
  <link></link>
  <title><![CDATA[Fully funded position as PhD Research Fellow in genomics/bioinformatics]]></title>
  <description><![CDATA[
<p>A fully funded position as PhD Research Fellow in genomics/bioinformatics is available at the Section for Genetics and Evolutionary Biology (EVOGENE) at the Department of Biosciences, University of Oslo.</p>

<p>The fellowship will be for a period of 3 years, or for a period of 4 years, with 25 % compulsory work (e.g. teaching responsibilities at the department) contingent on the qualifications of the candidate and the teaching needs of the department.</p>

<p>Starting date no later than October 1, 2021.</p>

<p>More at https://www.jobbnorge.no/en/available-jobs/job/199984/phd-research-fellow-in-genomics-and-bioinformatics</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/29282/cosmic</guid>
	<pubDate>Sat, 01 Oct 2016 15:04:10 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/29282/cosmic</link>
	<title><![CDATA[COSMIC]]></title>
	<description><![CDATA[<p>The accurate description and annotation of structural variants can be complex. &nbsp;This is due to the different resolution that variants are reported from traditional&nbsp;cytogenetic coordinates down to the actual base pair positions. Furthermore, multiple&nbsp;rearrangements in a single area of the genome can make cataloguing and interpreting&nbsp;their effects challenging.&nbsp;</p>
<p>The Rearrangement Overview page describes the one or more breakpoints which make up a structural&nbsp;variant. A breakpoint is defined as a region or point where the sample sequence has altered&nbsp;from the reference sequence. Minimum interpretation is made of this data. One variant event&nbsp;can consist of one or multiple breakpoints. The Syntax (shown above the table) gives a detailed description of the variant and its location &nbsp;(e.g. chr11:g.36585230_76606619del, a deletion of&nbsp;roughly 40Mb on chromosome 11). Syntax is based on HGVS mutation nomenclature recommendations&nbsp;[http://www.hgvs.org/rec.html].&nbsp;</p>
<p>http://cancer.sanger.ac.uk/cosmic/help/rearrangement/overview</p><p>Address of the bookmark: <a href="http://cancer.sanger.ac.uk/cosmic/help/rearrangement/overview" rel="nofollow">http://cancer.sanger.ac.uk/cosmic/help/rearrangement/overview</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34678/svfinder-tool-for-detecting-genomic-rearrangement-form-dna-seq-data</guid>
	<pubDate>Thu, 14 Dec 2017 15:51:40 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34678/svfinder-tool-for-detecting-genomic-rearrangement-form-dna-seq-data</link>
	<title><![CDATA[SVfinder: Tool for detecting genomic rearrangement form DNA-seq data]]></title>
	<description><![CDATA[<p><span>SVfinder provides genome-wide detection of structural variants from next generation paired-end sequencing reads.</span></p><p>Address of the bookmark: <a href="https://github.com/cauyrd/SVfinder" rel="nofollow">https://github.com/cauyrd/SVfinder</a></p>]]></description>
	<dc:creator>Robert M Willioms</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/29992/spines</guid>
	<pubDate>Mon, 28 Nov 2016 05:33:26 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/29992/spines</link>
	<title><![CDATA[Spines]]></title>
	<description><![CDATA[<p><a href="https://www.broadinstitute.org/ftp/distribution/software/spines/"><em>Spines</em></a>&nbsp;is a collection of software tools, developed and used by the Vertebrate Genome Biology Group at the Broad Institute. It provides basic data structures for efficient data manipulation (mostly genomic sequences, alignments, variation etc.), as well as specialized tool sets for various analyses. It also features three sequence alignment packages:&nbsp;<em>Satsuma,</em>&nbsp;a highly parallelized program for high-sensitivity, genome-wide synteny;&nbsp;<em>Papaya,</em>&nbsp;an all-purpose alignment tool for less diverged sequences; and&nbsp;<em>SLAP,</em>&nbsp;a context-sensitive local aligner for diverged sequences with large gaps.</p>
<p>Access&nbsp;<em>Spines</em>&nbsp;<a href="https://www.broadinstitute.org/ftp/distribution/software/spines/">here</a>.</p><p>Address of the bookmark: <a href="https://www.broadinstitute.org/genome-sequencing-and-analysis/spines" rel="nofollow">https://www.broadinstitute.org/genome-sequencing-and-analysis/spines</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34172/orthodotter-synteny-plots-oxford-grid</guid>
	<pubDate>Wed, 09 Aug 2017 07:16:16 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34172/orthodotter-synteny-plots-oxford-grid</link>
	<title><![CDATA[orthodotter: Synteny plots (oxford grid)]]></title>
	<description><![CDATA[<pre><code>orthodotter -h
--------------------------------------------------------------------------------
orthodotter - Plot orthologous genes on an oxford grid.
       -f &lt;file&gt;     : input file, containing orthologous genes, default is stdin
                       species chr-name start end species chr-name start end
       -toPlot &lt;arg&gt; : give the x and y sets and the color separated by double-dots,
                       for example set1:set2:red will plot set1 on x, set2 on y with
                       red points. Could give several -toPlot arguments.
                       To launch the clustering of dots, use extra-option 1=dist,min_nb_genes
                       where dist is the minimal distance (euclidian) between two points and min_nb_genes the minimal
                       number of genes in a cluster to be valid.
       -o &lt;file&gt;     : output file, default is stdout
       -x &lt;int&gt;      : resolution of x axis, default is 600
       -y &lt;int&gt;      : resolution on y axis, default is 600
       -r &lt;int&gt;      : radius of circle representing orthologous genes
       -format       : could be png, gif, jpg, pdf or ps. Default is png.
       -fg           : foreground color, default is black
       -bg           : background color, default is transparent
       -fSize &lt;int&gt;  : fontSize, default is 1
       -filter       : check chromosome names
       -h            : help
--------------------------------------------------------------------------------
orthodotter -f Vigne_Banane.ortho -toPlot Vigne:Banane:black:1=10,5 -x 1200 -y 1200 -bg white -o Vigne_vs_Banane.png &gt; Vigne_vs_Banane.clusters
--------------------------------------------------------------------------------</code></pre><p>Address of the bookmark: <a href="https://github.com/institut-de-genomique/orthodotter" rel="nofollow">https://github.com/institut-de-genomique/orthodotter</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34038/quota-synteny-alignment</guid>
	<pubDate>Mon, 31 Jul 2017 04:11:57 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34038/quota-synteny-alignment</link>
	<title><![CDATA[Quota synteny alignment]]></title>
	<description><![CDATA[<p><span>Typically in comparative genomics, we can identify anchors, chain them into syntenic blocks and interpret these blocks as derived from a common descent. However, when comparing two genomes undergone ancient genome duplications (plant genomes in particular), we have large number of blocks that are not orthologous, but are paralogous. This has forced us sometimes to use&nbsp;</span><em>ad-hoc</em><span>&nbsp;rules to screen these blocks. So the question is:&nbsp;</span><span>given the expected depth (quota) along both x- and y-axis, select a subset of the anchors with maximized total score</span><span>.</span></p><p>Address of the bookmark: <a href="https://github.com/tanghaibao/quota-alignment" rel="nofollow">https://github.com/tanghaibao/quota-alignment</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41582/flexidot-highly-customizable-ambiguity-aware-dotplots-for-visual-sequence-analyses</guid>
	<pubDate>Fri, 24 Apr 2020 08:39:28 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41582/flexidot-highly-customizable-ambiguity-aware-dotplots-for-visual-sequence-analyses</link>
	<title><![CDATA[flexidot: Highly customizable, ambiguity-aware dotplots for visual sequence analyses]]></title>
	<description><![CDATA[<p><span>FlexiDot is a cross-platform dotplot suite generating high quality self, pairwise and all-against-all visualizations. To improve dotplot suitability for comparison of consensus and error-prone sequences, FlexiDot harbors routines for strict and relaxed handling of mismatches and ambiguous residues. The custom shading modules facilitate dotplot interpretation and motif identification by adding information on sequence annotations and sequence similarities to the images. Combined with collage-like outputs, FlexiDot supports simultaneous visual screening of a large sequence sets, allowing dotplot use for routine screening.</span></p>
<p><img src="https://github.com/molbio-dresden/flexidot/blob/master/images/Beetle_matrix_shading.png?raw=true" alt="image" style="border: 0px; border: 0px;"></p><p>Address of the bookmark: <a href="https://github.com/molbio-dresden/flexidot" rel="nofollow">https://github.com/molbio-dresden/flexidot</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44525/synorth-exploring-the-evolution-of-synteny-and-long-range-regulatory-interactions-in-vertebrate-genomes</guid>
	<pubDate>Mon, 06 May 2024 06:21:10 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44525/synorth-exploring-the-evolution-of-synteny-and-long-range-regulatory-interactions-in-vertebrate-genomes</link>
	<title><![CDATA[Synorth: exploring the evolution of synteny and long-range regulatory interactions in vertebrate genomes]]></title>
	<description><![CDATA[<p><span>Genomic regulatory blocks are chromosomal regions spanned by long clusters of highly conserved noncoding elements devoted to long-range regulation of developmental genes, often immobilizing other, unrelated genes into long-lasting syntenic arrangements. Synorth&nbsp;</span><a href="http://synorth.genereg.net/" target="_blank">http://synorth.genereg.net/</a><span>&nbsp;is a web resource for exploring and categorizing the syntenic relationships in genomic regulatory blocks across multiple genomes, tracing their evolutionary fate after teleost whole genome duplication at the level of genomic regulatory block loci, individual genes, and their phylogenetic context.</span></p>
<p><span>More at&nbsp;https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2745767/</span></p><p>Address of the bookmark: <a href="http://synorth.genereg.net/" rel="nofollow">http://synorth.genereg.net/</a></p>]]></description>
	<dc:creator>LEGE</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/38682/bourque-lab</guid>
  <pubDate>Mon, 14 Jan 2019 15:39:25 -0600</pubDate>
  <link></link>
  <title><![CDATA[Bourque Lab]]></title>
  <description><![CDATA[
<p>The goal of the lab is to understand mammalian genomes using comparative genomic and epigenomic analyses. Areas of interest include: the evolution of regulatory sequences, the role of transposable elements in gene regulation and the impact of genome rearrangements in evolution and cancer.</p>

<p>As a computational genomicists our work involves examining billions of DNA base pairs and interpreting how variation impacts basic biology and disease. We develop computational methods and resources for the functional annotation of genomes with a special emphasis on sequencing-based assays (e.g. ChIP-seq, RNA-Seq, exome- and whole-genome sequencing, single-cell analysis).</p>

<p>http://www.computationalgenomics.ca</p>
]]></description>
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