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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/30012?offset=440</link>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/6835/roslin-bioinformatics-group</guid>
  <pubDate>Mon, 25 Nov 2013 23:55:25 -0600</pubDate>
  <link></link>
  <title><![CDATA[Roslin Bioinformatics Group]]></title>
  <description><![CDATA[
<p>Roslin Bioinformatics Group</p>

<p>The Law group provides internal Institute-specific development, training and support roles for data manipulation, sequence analysis and any other aspect of the analysis of biological data using computer systems. Additionally we provide databases and applications supporting the international animal science community, particularly tools and resources for genome mapping.</p>

<p>Head: Andy Law. Members: John Bowman (animal facility database applications), Zen Lu (bioinformatics support), Trevor Paterson (software development)</p>

<p>More @ http://www.bioinformatics.ed.ac.uk/groups/roslin-bioinformatics-group</p>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/videolist/watch/3918/the-human-genome-project-video-3d-animation-introduction-low</guid>
	<pubDate>Sat, 24 Aug 2013 19:01:19 -0500</pubDate>
	<link>https://bioinformaticsonline.com/videolist/watch/3918/the-human-genome-project-video-3d-animation-introduction-low</link>
	<title><![CDATA[The Human Genome Project Video   3D Animation Introduction Low)]]></title>
	<description><![CDATA[<iframe width="" height="" src="https://www.youtube-nocookie.com/embed/YxoQFSBwyms" frameborder="0" allowfullscreen></iframe>]]></description>
	
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/7569/phd-at-university-of-calgary</guid>
  <pubDate>Fri, 27 Dec 2013 20:24:39 -0600</pubDate>
  <link></link>
  <title><![CDATA[PhD at University of Calgary]]></title>
  <description><![CDATA[
<p>Institution/Company: <br />University of Calgary<br />Location: <br />Calgary, AB<br />Job Description: </p>

<p>Novel diagnostic platform for detection of Osteoarthritis</p>

<p>I invite applications from highly motivated individuals to join my laboratory as a PhD student in Systems Biology at the University of Calgary McCaig Institute for Bone and Joint Health. This project is aimed at characterizing the networks of physical (protein-protein) interactions underlying inflammatory processes in patients with Osteoarthritis and how this differs from patients with Rheumatoid Arthritis and normal individuals. This work will eventually lead to the development of a novel diagnostic platform for the non-invasive and accurate detection of early Osteoarthritis. The selected candidate will use state-of-the-art computational methodologies to systematically analyze proteomic data, and develop /implement new algorithms to identify protein and functional interaction networks from high throughput experimental data. The individual will also benefit by working closely with experts at the UofC and UofA through an AIHS Alberta Osteoarthritis Team Grant which includes experts from all pillars of health research. The candidate will also be supported to attend bioinformatics workshops and conferences to advance and disseminate their research.<br />Qualifications: The ideal candidate will have a Master’s degree in Computational Biology, Bioinformatics, or equivalent with strong background knowledge of the Biological Sciences, Biochemistry, and Microbiology. The individual should additionally have experience in handling high-throughput data sets as well as programming skills. The candidate will be registered as a PhD student in Dr. Krawetz’s laboratory, located in the new state-of-the-art Health Research Innovation Centre at the UofC. The individual will have strong verbal and written skills and the ability to work efficiently in a team environment.</p>

<p>In addition to the outstanding research opportunities available in this setting, students also enjoy the many cultural and sporting amenities provided in the city of Calgary, and can take advantage of the unparalleled skiing and hiking in the Rocky Mountains that are less than an hour away.</p>

<p>Candidates must be academically competitive and will be expected to apply for external funding. The stipend is $25,000/yr. For outstanding PhD students, internal top-up award opportunities are available on a competitive basis. If interested in joining the lab, please contact Dr. Krawetz directly at rkrawetz@ucalgary.ca and provide the following information:</p>

<p>- Short cover letter explaining your interest in the lab<br />- Resume<br />- Scanned copy of transcript or listing of course grades<br />- Names and contact information for two individuals who will be willing to provide letters of reference</p>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/21150/webinar-on-an-integrated-rna-and-dna-approach-to-unravel-genetic-regulation-in-cancer</guid>
	<pubDate>Wed, 11 Feb 2015 04:59:57 -0600</pubDate>
	<link>https://bioinformaticsonline.com/news/view/21150/webinar-on-an-integrated-rna-and-dna-approach-to-unravel-genetic-regulation-in-cancer</link>
	<title><![CDATA[Webinar on 'An integrated RNA and DNA approach to unravel genetic regulation in cancer']]></title>
	<description><![CDATA[<div><p><strong>Webinar on 'An integrated RNA and DNA approach to unravel genetic regulation in cancer'</strong></p><p><strong>Abstract</strong></p><p>Whole exome DNA sequencing (WES) or whole genome DNA sequencing (WGS) allows detection of mutations and polymorphisms in all exonic and genomic regions, respectively, while messenger RNA sequencing (RNA-Seq) enables quantitative analysis of gene expression. Mutations in the genome result in diverse transcriptional aberrations that can be missed in a stand-alone WES/WGS analysis. An integration of DNA variant analysis and RNA-Seq analysis enables one to investigate the consequences of genomic changes in the RNA transcripts including germline and somatic changes, imprinting, RNA editing and allele specific expression (ASE). In this webinar, we will demonstrate this integrated approach using Strand NGS to identify high confidence mutations, RNA editing events and ASE in cancer.</p><p><strong>Webinar Details</strong></p><table width="100%" border="1" cellspacing="0" cellpadding="0">
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<p style="text-align: center;"><br /> <strong>Sessions</strong></p>
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<p style="text-align: center;"><a href="http://www.strand-ngs.com/webinar_registration"><strong>San Francisco Time<br /> (PST)</strong></a></p>
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<p style="text-align: center;"><a href="http://www.strand-ngs.com/webinar_registration"><strong>Tokyo Time<br /> (GMT+09:00)</strong></a></p>
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<td valign="top">
<p style="text-align: center;"><a href="http://www.strand-ngs.com/webinar_registration"><strong>Berlin Time<br /> (GMT+01:00)</strong></a></p>
</td>
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<p style="text-align: center;"><a href="http://www.strand-ngs.com/webinar_registration"><strong>Mumbai Time<br /> (GMT+05:30)</strong></a></p>
</td>
</tr>
<tr>
<td>
<p style="text-align: center;"><a href="http://www.strand-ngs.com/webinar_registration"><strong>Session 1</strong></a></p>
</td>
<td valign="top">
<p style="text-align: center;">25 Feb&nbsp;<br /> 12:30 AM</p>
</td>
<td>
<p style="text-align: center;">25 Feb&nbsp;<br /> 5:30 PM</p>
</td>
<td>
<p style="text-align: center;">25 Feb&nbsp;<br /> 9:30 AM</p>
</td>
<td>
<p style="text-align: center;">25 Feb&nbsp;<br /> 2:00 PM</p>
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<p style="text-align: center;"><a href="http://www.strand-ngs.com/webinar_registration"><strong>Session 2</strong></a></p>
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<td valign="top">
<p style="text-align: center;">25 Feb&nbsp;<br /> 9:00 AM</p>
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<td>
<p style="text-align: center;">26 Feb<br /> 2:00 AM</p>
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<p style="text-align: center;">25 Feb&nbsp;<br /> 6:00 PM</p>
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<p style="text-align: center;">25 Feb&nbsp;<br /> 10:30 PM</p>
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</table><p><strong style="font-size: 12.8000001907349px;">Register here: </strong><a href="http://www.strand-ngs.com/webinar_registration">http://www.strand-ngs.com/webinar_registration</a></p><p><strong>About Speaker:</strong></p><p>Dr. Veena Hedatale, has a PhD in Plant Genetics from The Radboud University, Netherlands focused on meiosis and recombination. Her prior academic experience at Cornell University was on genetic mapping and gene transformation in Rice. She has worked with Monsanto, and contributed to data mining, database development as well as gene/promoter/pathway discovery for traits related to yield and stress in crop species. At Strand, Veena has worked on Pharmacogenomic analysis of targets and Gene family analysis projects. Currently, she is part of the Strand NGS Application Science team and is involved in the analysis of next generation sequencing data.</p><p>Please feel free to contact us 24/5, for availing free online training or if you have any questions.</p></div><div><p><strong style="font-size: 12.8000001907349px;">Email:</strong> sales@strandngs.com</p><p><strong>Phone (USA):</strong> 1-800-752-9122</p><p><strong>Phone (ROW):</strong> +1-650-353-5060</p><p>&nbsp;</p></div>]]></description>
	<dc:creator>Yeshodari</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/7215/postdoc-positions-in-computational-biology-center-for-genomic-science-milan-italy</guid>
  <pubDate>Thu, 12 Dec 2013 18:34:47 -0600</pubDate>
  <link></link>
  <title><![CDATA[Postdoc positions in computational biology - Center for Genomic Science - Milan, Italy]]></title>
  <description><![CDATA[
<p>Job Description: three postdoc positions in computational biology are available at the Center for Genomic Science in Milan (Italy):</p>

<p>- Development of computational methods to investigate the interplay between epigenetic and genetic layers and their role in tumor progression, by integrating genomic, epigenomic and transcriptional data. PI: Mattia Pelizzola (http://tiny.cc/comEpi)<br />- Epigenome and transcriptome analysis in mouse models of Hepatocellular Carcinoma. PI: Bruno Amati - Small and long non-coding RNAs in cancer stem cells. PI: Francesco Nicassio</p>

<p>All projects will benefit from the availability of both in-house and publicly available next-generation sequencing datasets. Familiarity with Linux environment, programming skills (especially in R) and a background in either computational biology, or physics/engineering/math will be advantageous.</p>

<p>Deadline for the application January 6th, to apply: http://genomics.iit.it/resources.html</p>

<p>Start date: March 1st, 2014</p>

<p>Duration: 1+2 years</p>

<p>Contact Person (Referent): Mattia Pelizzola</p>

<p>Ref. E-Mail: mattia.pelizzola@iit.it</p>

<p>Tel: 0039-02-94375058<br />Group Web Page: http://genomics.iit.it</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/35418/karyoploter-plot-whole-genomes-with-arbitrary-data</guid>
	<pubDate>Fri, 02 Feb 2018 03:24:28 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/35418/karyoploter-plot-whole-genomes-with-arbitrary-data</link>
	<title><![CDATA[karyoploteR: plot whole genomes with arbitrary data]]></title>
	<description><![CDATA[<p><span><a href="http://bioconductor.org/packages/karyoploteR">karyoploteR</a></span><span>&nbsp;is an R package to create karyoplots, that is, representations of whole genomes with arbitrary data plotted on them. It is inspired by the R base graphics system and does not depend on other graphics packages. The aim of karyoploteR is to offer the user an easy way to plot data along the genome to get broad genome-wide view to facilitate the identification of genome wide relations and distributions.</span></p><p>Address of the bookmark: <a href="https://bernatgel.github.io/karyoploter_tutorial/" rel="nofollow">https://bernatgel.github.io/karyoploter_tutorial/</a></p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/7383/embo-practical-course-on-bioinformatics-and-genomes-analyses-at-hellenic-pasteur-institute-athens-greece</guid>
  <pubDate>Sat, 21 Dec 2013 10:00:24 -0600</pubDate>
  <link></link>
  <title><![CDATA[EMBO practical Course on  "Bioinformatics and Genomes Analyses" at Hellenic Pasteur Institute, Athens, Greece]]></title>
  <description><![CDATA[
<p>The main objectives of this Practical Course are to strengthen skills <br />of PhD students and young researchers in the domain of Bioinformatics <br />and Genome Data Analyses on the use of advanced fundamental algorithms <br />and their applications in genome studies.</p>

<p>The course topics will include theoretical and practical aspects in:<br />- Genomes comparisons,<br />- Evolutionary analyses (orthologs, paralogs and ancestral genomes <br />inference),<br />- RNAseq and Next Generation Sequencing (including algorithms, methods <br />and sequence mapping tools, data analyses and applications).</p>

<p>The course programme will be centred on theoretical presentations <br />followed by practical sessions. Practical sessions in a Linux <br />environment will involve Unix shell and Perl scripting. Participants <br />are assumed to be familiar with this environment.</p>

<p>A series of lectures delivered by prominent scientists on recent hot <br />topics in genome (Viruses, Prokaryotes, Eukaryotes) studies will be <br />included in the programme and future research perspectives will be <br />highlighted.</p>

<p>The topics that will be included in the course programme are similar <br />to those included in previously organized courses:http://www.pasteur.fr/~tekaia/BGA_courses.html</p>

<p>The course is aimed at motivated Ph.D students and Post-Doctoral <br />Researchers in Academic Institutions, with background in Mathematics, <br />Statistics, Biology or Computer Science and who are involved in <br />Bioinformatics and Genomes studies.</p>

<p>Selection of participants will be based on their background, running <br />research projects and on expressed motivations.<br />Selected students will have free accommodation and meals and are <br />expected to contribute with 200 euros and to pay for their travel <br />expenses.<br />All participants (students and invited speakers) will stay in the same <br />hotel.</p>

<p>Detailed indications are available on the course web site: http://events.embo.org/14-comparative-genomics/index.html</p>

<p>Candidates are advised to complete carefully the application form, <br />together with an abstract of at least one of their running projects, a <br />"one-page CV" and a personal Identity Picture (Photo).</p>

<p>The application deadline is March 14, 2014.</p>

<p>The organizers:<br />Menelaos Manoussakis, Hellenic Pasteur Institute, Athens, Greece.<br />Evdokia Karagouni, Hellenic Pasteur Institute, Athens - Greece.<br />Evie Melanitou,  Institut Pasteur Paris - France.<br />Fredj Tekaia ( Institut Pasteur Paris France)<br />URL: http://www.pasteur.fr/~tekaia/BGA_courses.html</p>

<p>Date: 5 – 17 May, 2014. <br />More at http://events.embo.org/14-comparative-genomics/index.html<br />will take place in the ,</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/32946/grass-a-generic-algorithm-for-scaffolding-next-generation-sequencing-assemblies</guid>
	<pubDate>Tue, 23 May 2017 05:20:32 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/32946/grass-a-generic-algorithm-for-scaffolding-next-generation-sequencing-assemblies</link>
	<title><![CDATA[GRASS: a generic algorithm for scaffolding next-generation sequencing assemblies.]]></title>
	<description><![CDATA[<p><span>GRASS (GeneRic ASsembly Scaffolder)-a novel algorithm for scaffolding second-generation sequencing assemblies capable of using diverse information sources. GRASS offers a mixed-integer programming formulation of the contig scaffolding problem, which combines contig order, distance and orientation in a single optimization objective. The resulting optimization problem is solved using an expectation-maximization procedure and an unconstrained binary quadratic programming approximation of the original problem. We compared GRASS with existing HTS scaffolders using Illumina paired reads of three bacterial genomes. Our algorithm constructs a comparable number of scaffolds, but makes fewer errors. This result is further improved when additional data, in the form of related genome sequences, are used.</span></p><p>Address of the bookmark: <a href="https://github.com/AlexeyG/GRASS" rel="nofollow">https://github.com/AlexeyG/GRASS</a></p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/7568/oldest-hominin-dna-sequenced</guid>
	<pubDate>Fri, 27 Dec 2013 19:58:31 -0600</pubDate>
	<link>https://bioinformaticsonline.com/news/view/7568/oldest-hominin-dna-sequenced</link>
	<title><![CDATA[Oldest Hominin DNA Sequenced]]></title>
	<description><![CDATA[<p>Matthias Meyer and his team from the Max Planck Institute for Evolutionary Anthropology in Leipzig, Germany, have developed new techniques for retrieving and sequencing highly degraded ancient DNA. They then joined forces with Juan-Luis Arsuaga and applied the new techniques to a cave bear from the Sima de los Huesos site. After this success, the researchers sampled two grams of bone powder from a hominin thigh bone from the cave. They extracted its DNA and sequenced the genome of the mitochondria or mtDNA, a small part of the genome that is passed down along the maternal line and occurs in many copies per cell. The researchers then compared this ancient mitochondrial DNA with Neandertals, Denisovans, present-day humans, and apes.<br /><br />From the missing mutations in the old DNA sequences the researchers calculated that the Sima hominin lived about 400,000 years ago. They also found that it shared a common ancestor with the Denisovans, an extinct archaic group from Asia related to the Neandertals, about 700,000 years ago. "The fact that the mtDNA of the Sima de los Huesos hominin shares a common ancestor with Denisovan rather than Neandertal mtDNAs is unexpected since its skeletal remains carry Neandertal-derived features," says Matthias Meyer. Considering their age and Neandertal-like features, the Sima hominins were likely related to the population ancestral to both Neandertals and Denisovans. Another possibility is that gene flow from yet another group of hominins brought the Denisova-like mtDNA into the Sima hominins or their ancestors.<br /><br /></p><p>Reference</p><p>http://www.sciencedaily.com/releases/2013/12/131204132018.htm</p>]]></description>
	<dc:creator>Surajeet</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/35429/list-of-visualization-tools-for-genome-alignments</guid>
	<pubDate>Fri, 02 Feb 2018 13:25:33 -0600</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/35429/list-of-visualization-tools-for-genome-alignments</link>
	<title><![CDATA[List of visualization tools for genome alignments]]></title>
	<description><![CDATA[<p><span>Genome</span><span>&nbsp;browsers are useful not only for showing final results but also for improving analysis protocols, testing data quality, and generating result drafts. Its integration in analysis pipelines allows the optimization of parameters, which leads to better results. But sometime, we need publication ready figure of genomes. Following are the list of genome alignment visualization tools, which could be useful for analysis and&nbsp;interpretation of results:</span></p><p>ABySS Explorer</p><p>Interactive Java application that uses a novel graph-based representation to display a sequence assembly and associated metadata</p><p>http://www.bcgsc.ca/platform/bioinfo/software/abyss-explorer</p><p>BamView</p><p>Genome browser and annotation tool that allows visualization of sequence features, next-generation sequencing (NGS) data and the results of analyses within the context of the sequence, and also its six-frame translation</p><p>http://www.sanger.ac.uk/resources/software/artemis/</p><p>DNannotator&nbsp;</p><p>Annotation web toolkit for regional genomic sequences</p><p>http://bioapp.psych.uic.edu/DNannotator.htm</p><p>JVM&nbsp;</p><p>Java Visual Mapping tool for NGS reads</p><p>http://www.springer.com/cda/content/document/cda_downloaddocument/9789401792448-c2.pdf?SGWID=0-0-45-1487072-p176815501</p><p>LookSeq&nbsp;</p><p>Web-based visualization of sequences derived from multiple sequencing technologies. Low- or high-depth read pileups and easy visualization of putative single nucleotide and structural variation</p><p>http://lookseq.sourceforge.net</p><p>MagicViewer&nbsp;</p><p>Visualization of short read alignment, identification of genetic variation and association with annotation information of a reference genome</p><p>http://bioinformatics.zj.cn/magicviewer/</p><p>MapView&nbsp;</p><p>Alignments of huge-scale single-end and pair-end short reads</p><p>http://omictools.com/mapview-s1367.html</p><p>MultiPipMaker</p><p>Computes alignments of similar regions in two DNA sequences. The resulting alignments are summarized with a &lsquo;percent identity plot&rsquo; (pip)</p><p>http://pipmaker.bx.psu.edu/pipmaker/</p><p>PileLineGUI&nbsp;</p><p>Handling genome position files in NGS studies</p><p>http://sing.ei.uvigo.es/pileline/pilelinegui.html</p><p>SAMtools tview&nbsp;</p><p>Simple and fast text alignment viewer; NGS compatible</p><p>http://www.htslib.org/</p><p>SEWAL</p><p>Uses a locality-sensitive hashing algorithm to enumerate all unique sequences in an entire Illumina sequencing run</p><p>http://www.sourceforge.net/projects/sewal</p><p>STAR&nbsp;</p><p>A web-based integrated solution to management and visualization of sequencing data</p><p>http://wanglab.ucsd.edu/star/browser</p><p>SVA&nbsp;</p><p>Software for annotating and visualizing sequenced human genomes</p><p>http://www.svaproject.org</p><p>Viewer (IGV)&nbsp;</p><p>Visualization of large heterogeneous datasets, providing a smooth and intuitive user experience at all levels of genome resolution</p><p>https://www.broadinstitute.org/igv/</p><p>ZOOM Lite&nbsp;</p><p>NGS data mapping and visualization software</p><p>http://bioinfor.com/zoom/lite/</p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
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