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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/43614?offset=60</link>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/videolist/watch/19555/a-3d-map-of-the-human-genome</guid>
	<pubDate>Fri, 12 Dec 2014 22:27:55 -0600</pubDate>
	<link>https://bioinformaticsonline.com/videolist/watch/19555/a-3d-map-of-the-human-genome</link>
	<title><![CDATA[A 3D Map of the Human Genome]]></title>
	<description><![CDATA[<iframe width="" height="" src="https://www.youtube-nocookie.com/embed/dES-ozV65u4" frameborder="0" allowfullscreen></iframe>Suhas Rao and Miriam Huntley (of the Aiden Lab) describe a 3D map of the human genome at kilobase resolution, revealing the principles of chromatin looping. Guest Origami Folding: Sarah Nyquist.

Suhas S.P. Rao*, Miriam H. Huntley*, Neva C. Durand, Elena K. Stamenova, Ivan D. Bochkov, James T. Robinson, Adrian L. Sanborn, Ido Machol, Arina D. Omer, Eric S. Lander, Erez Lieberman Aiden. (2014). A 3D Map of the Human Genome at Kilobase Resolution Reveals Principles of Chromatin Looping. Cell.]]></description>
	
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36880/jvarkit-java-utilities-for-bioinformatics</guid>
	<pubDate>Fri, 08 Jun 2018 09:31:55 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36880/jvarkit-java-utilities-for-bioinformatics</link>
	<title><![CDATA[Jvarkit : Java utilities for Bioinformatics]]></title>
	<description><![CDATA[Collection of Java tool kits for bioinformatics works:

Jvarkit : Java utilities for Bioinformatics<p>Address of the bookmark: <a href="http://lindenb.github.io/jvarkit/" rel="nofollow">http://lindenb.github.io/jvarkit/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/11528/post-doctoral-research-assistant-in-genetics</guid>
  <pubDate>Thu, 05 Jun 2014 16:01:39 -0500</pubDate>
  <link></link>
  <title><![CDATA[Post-doctoral Research Assistant in Genetics]]></title>
  <description><![CDATA[
<p>Post-doctoral Research Assistant in Genetics<br />Camden, North London<br />£31.1K per annum inclusive of London Weighting</p>

<p>This is a fixed term post for 36 months.</p>

<p>We wish to recruit a highly motivated, postdoctoral scientist to carry out a BBSRC funded project in the laboratory of Dr. Denis Larkin. The project is focused on developing and applying new algorithms to study genome and chromosome evolution in birds, mammals and other vertebrate species using whole-genome sequences and existing algorithms. The post holder will use cutting edge computational and laboratory approaches to generate chromosomal assemblies for sequenced genomes, study chromosomal structures and genome differences between bird and other vertebrate species in attempt to identify species- and clade-specific genome signatures.</p>

<p>Applicants must have a Ph.D. and a track record of success, as indicated by first-author publications in international journals. They must possess excellent organisation skills and be capable of individual initiative and of interacting as part of a team. Applicants with extensive practical experience in bioinformatics or computer science, programming, visualization, handling of large data sets, high-performance computing are encouraged to apply. The post will involve collaboration with a wide range of academic partners both within the UK, EU and worldwide. In addition to leading their own project the post holder will have opportunities to contribute to multiple international genome initiatives.</p>

<p>Experience in programming, bioinformatics and comparative genome analysis is essential. Applicants should have a minimum of a degree and preferably a higher degree in a relevant subject.</p>

<p>The Royal Veterinary College has the largest range of veterinary, para-veterinary and animal science undergraduate and postgraduate courses of any veterinary school in the world and is one of the largest veterinary schools in Europe.</p>

<p>Prospective applicants are encouraged to contact Dr. Denis Larkin, Comparative Biomedical Sciences Department on +442071211906 or email: dlarkin@rvc.ac.uk</p>

<p>We offer a generous reward package.</p>

<p>For further information and to apply on-line please visit our website: www.rvc.ac.uk<br />Job reference CBS-0025-14A</p>

<p>Closing date: 4 July 2014<br />Interviews are likely to be held in July 2014</p>

<p>We promote equality of opportunity and diversity within the workplace and welcome applications from all sections of the community.</p>
]]></description>
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<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/33221/genome-annotation-transfer-utility-gatu</guid>
	<pubDate>Mon, 29 May 2017 05:54:53 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/33221/genome-annotation-transfer-utility-gatu</link>
	<title><![CDATA[Genome Annotation Transfer Utility (GATU)]]></title>
	<description><![CDATA[<p>Genome Annotation Transfer Utility (GATU) was designed to facilitate quick, efficient annotation of similar genomes using genomes that have already been annotated. For example, whenever a new strain of SARS coronavirus is sequenced, it is possible, using GATU, to automatically annotate the new strain using a previously-annotated strain of SARS CoV. This saves researchers from tedious manual annotation of these sequences.</p>
<p>The program utilizes tBLASTn and BLASTn algorithms to map genes from the reference genome (the annotated strain) to the new sequence (the unannotated strain). The goal is to annotate the majority of the new genome&rsquo;s genes in a single step. ORFs present in the target genome and absent from the reference genome are also identified; these ORFs can be further analyzed using BLAST, VGO and BBB. Afterwards, they can either be accepted for/rejected from annotation. GATU can handle multiple-exon genes as well as mature peptides. Although it was designed for use with viral genomes, GATU can also be used to help annotate larger genomes (ie. bacterial genomes).</p>
<p>The output is saved in GenBank, XML, or EMBL file format.</p><p>Address of the bookmark: <a href="https://virology.uvic.ca/help/tool-help/help-books/genome-annotation-transfer-utility-gatu-documentation/" rel="nofollow">https://virology.uvic.ca/help/tool-help/help-books/genome-annotation-transfer-utility-gatu-documentation/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/39917/chromomap-an-r-package-for-interactive-visualization-and-annotation-of-chromosomes</guid>
	<pubDate>Sat, 07 Sep 2019 10:45:31 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/39917/chromomap-an-r-package-for-interactive-visualization-and-annotation-of-chromosomes</link>
	<title><![CDATA[chromoMap-An R package for Interactive Visualization and Annotation of Chromosomes]]></title>
	<description><![CDATA[<p><code>chromoMap</code>&nbsp;provides interactive, configurable and elegant graphics visualization of chromosomes or chromosomal regions allowing users to map chromosome elements (like genes,SNPs etc.) on the chromosome plot.Each chromosome is composed of loci(representing a specific range determined based on chromosome length) that, on hover, shows details about the annotations in that locus range. The plots can be saved as HTML documents that can be shared easily. In addition, you can include them in R Markdown or in R Shiny applications.</p>
<p>Some of the prominent features of the package are:</p>
<ul>
<li>visualizing polyploidy simultaneously on the same plot.</li>
<li>annotating groups of elements as distinct colors.</li>
<li>creating chromosome heatmaps.</li>
<li>adjusting chromosome range or visualizing chromosome regions such as genes</li>
<li>adding labels to the plot</li>
<li>adding hyperlinks to each element</li>
</ul><p>Address of the bookmark: <a href="https://cran.r-project.org/web/packages/chromoMap/vignettes/chromoMap.html" rel="nofollow">https://cran.r-project.org/web/packages/chromoMap/vignettes/chromoMap.html</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/39450/apollo-first-instantaneous-collaborative-genomic-annotation-editor-available-on-the-web</guid>
	<pubDate>Fri, 31 May 2019 19:55:39 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/39450/apollo-first-instantaneous-collaborative-genomic-annotation-editor-available-on-the-web</link>
	<title><![CDATA[Apollo: First instantaneous, collaborative genomic annotation editor available on the Web]]></title>
	<description><![CDATA[<ul>
<li>Apollo is a plug-in for the&nbsp;<a href="http://jbrowse.org/">JBrowse</a>&nbsp;Genome Viewer.</li>
<li>In addition to genes and pseudogenes, users can annotate ncRNAs (snRNA, snoRNA, tRNA, rRNA), miRNAs, repeat regions, and transposable elements; each annotation type has its own configuration of the &lsquo;Information Editor&rsquo;.</li>
<li>History tracking with undo/redo functions is available.</li>
<li>Users are able to directly set an annotation to a specific state, choosing from the &lsquo;History&rsquo; display.</li>
<li>Adding and updating PubMed IDs will prompt users with a publication title to confirm their submission.</li>
<li>Gene Ontology (GO) terms are supported and GO ID auto-completion has been incorporated.</li>
<li>Users may access a &lsquo;Recent Changes&rsquo; page.</li>
<li>Help page with Apollo specific content is available.</li>
</ul><p>Address of the bookmark: <a href="http://genomearchitect.github.io/" rel="nofollow">http://genomearchitect.github.io/</a></p>]]></description>
	<dc:creator>Jit</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/bookmarks/view/41673/lr-gapcloser-a-tiling-path-based-gap-closer-that-uses-long-reads-to-complete-genome-assembly</guid>
	<pubDate>Thu, 14 May 2020 15:09:52 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41673/lr-gapcloser-a-tiling-path-based-gap-closer-that-uses-long-reads-to-complete-genome-assembly</link>
	<title><![CDATA[LR_Gapcloser: a tiling path-based gap closer that uses long reads to complete genome assembly]]></title>
	<description><![CDATA[<p>LR_Gapcloser is a gap closing tool using long reads from studied species. The long reads could be downloaed from public read archive database (for instance, NCBI SRA database ) or be your own data. Then they are fragmented and aligned to scaffolds using BWA mem algorithm in BWA package. In the package, we provided a compiled bwa, so the user needn't to install bwa. LR_Gapcloser uses the alignments to find the bridging that cross the gap, and then fills the long read original sequence into the genomic gaps.</p><p>Address of the bookmark: <a href="https://github.com/CAFS-bioinformatics/LR_Gapcloser" rel="nofollow">https://github.com/CAFS-bioinformatics/LR_Gapcloser</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38413/genobuntu-a-software-package-containing-more-than-70-software-and-packages-oriented-towards-ngs-and-genome-assembly</guid>
	<pubDate>Tue, 11 Dec 2018 05:15:57 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38413/genobuntu-a-software-package-containing-more-than-70-software-and-packages-oriented-towards-ngs-and-genome-assembly</link>
	<title><![CDATA[Genobuntu: A software package containing more than 70 software and packages oriented towards NGS and genome assembly]]></title>
	<description><![CDATA[<p><span>Genobuntu is a software package containing more than 70 software and packages oriented towards NGS. In its current version, Genobuntu supports pre assembly tools, genome assemblers as well as post assembly tools.&nbsp;</span><br><br><span>Commonly used biological software and example script files for different assembly pipelines have also been provided, where the example script files can be updated to suit one&rsquo;s experimental needs. Genobuntu attempts to reduce the amount of time and energy needed to build software workstations and it can also act as a good teaching source for a class room setting.&nbsp;</span></p>
<p>https://sourceforge.net/projects/genobuntu/</p><p>Address of the bookmark: <a href="https://sourceforge.net/projects/genobuntu/" rel="nofollow">https://sourceforge.net/projects/genobuntu/</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38735/genome-assembly-tutorial-genome-assembly-for-short-and-long-reads</guid>
	<pubDate>Sat, 19 Jan 2019 17:29:53 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38735/genome-assembly-tutorial-genome-assembly-for-short-and-long-reads</link>
	<title><![CDATA[Genome assembly tutorial &quot;Genome Assembly for short and long reads&quot;]]></title>
	<description><![CDATA[<p>In this lab we will perform de novo genome assembly of a bacterial genome. You will be guided through the genome assembly starting with data quality control, through to building contigs and analysis of the results. At the end of the lab you will know:</p>
<ol>
<li>How to perform basic quality checks on the input data</li>
<li>How to run a short read assembler on Illumina data</li>
<li>How to run a long read assembler on Pacific Biosciences or Oxford Nanopore data</li>
<li>How to improve the accuracy of a long read assembly using short reads</li>
<li>How to assess the quality of an assembly</li>
</ol>
<p>https://bioinformaticsdotca.github.io/high-throughput_biology_2017</p><p>Address of the bookmark: <a href="https://bioinformaticsdotca.github.io/high-throughput_biology_2017_module6_lab" rel="nofollow">https://bioinformaticsdotca.github.io/high-throughput_biology_2017_module6_lab</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

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