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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/27216?offset=340</link>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/videolist/watch/11355/genomics-and-personalized-medicine-breakthroughs</guid>
	<pubDate>Sun, 01 Jun 2014 23:40:14 -0500</pubDate>
	<link>https://bioinformaticsonline.com/videolist/watch/11355/genomics-and-personalized-medicine-breakthroughs</link>
	<title><![CDATA[Genomics and Personalized Medicine Breakthroughs]]></title>
	<description><![CDATA[<iframe width="" height="" src="https://www.youtube-nocookie.com/embed/VAR-1vNc0TE" frameborder="0" allowfullscreen></iframe>http://bit.ly/e8QGzY Human genome mapping is now enabling a breakthrough in medical innovation -- personalized medicine. What does this mean for patients? We can now identify predispositions to disease, predict how we metabolize drugs, and figure out what kinds of treatments we may respond to, and even determine when a drug may give us an adverse reaction. All medical specialties benefit from human genome intelligence -- oncology saw the first impacts -- but advances are now being seen in cardiology, obstetrics and gynecology, pediatric diseases, gastroenterology, rheumatology, immunology and other areas. This video covers the areas that genetic medicine is impacting and where the future of genomic medicine is heading.]]></description>
	
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37306/genome-u-plot-a-whole-genome-visualization</guid>
	<pubDate>Fri, 13 Jul 2018 19:50:41 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37306/genome-u-plot-a-whole-genome-visualization</link>
	<title><![CDATA[Genome U-Plot: a whole genome visualization]]></title>
	<description><![CDATA[<p><span>Genome U-Plot for producing clear and intuitive graphs that allows researchers to generate novel insights and hypotheses by visualizing SVs such as deletions, amplifications, and chromoanagenesis events. The main features of the Genome U-Plot are its layered layout, its high spatial resolution and its improved aesthetic qualities.&nbsp;</span></p>
<p><span>https://github.com/gaitat/GenomeUPlot</span></p><p>Address of the bookmark: <a href="https://github.com/gaitat/GenomeUPlot" rel="nofollow">https://github.com/gaitat/GenomeUPlot</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37796/grsr-a-tool-for-deriving-genome-rearrangement-scenarios-from-multiple-unichromosomal-genome-sequences</guid>
	<pubDate>Fri, 28 Sep 2018 09:35:10 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37796/grsr-a-tool-for-deriving-genome-rearrangement-scenarios-from-multiple-unichromosomal-genome-sequences</link>
	<title><![CDATA[GRSR: a tool for deriving genome rearrangement scenarios from multiple unichromosomal genome sequences]]></title>
	<description><![CDATA[<p>GRSR is a Tool for Deriving Genome Rearrangement Scenarios for Multiple Uni-chromosomal Genomes. This tool will do the following steps:</p>
<ul>
<li>Step 1. Run mugsy to get multiple sequence alignment results.</li>
<li>Step 2 &amp; 3. Extraction of the Coordinates of Core Blocks, Construction of Synteny Blocks and Generating Signed Permutations.</li>
<li>Step 4. Generate pairwise genome rearrangement scenarios and find repeats at the breakpoints of each rearrangement events.</li>
<li></li>
<li></li>
</ul>
<p>https://github.com/DanwangJessica/GRSR</p><p>Address of the bookmark: <a href="https://github.com/DanwangJessica/GRSR" rel="nofollow">https://github.com/DanwangJessica/GRSR</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/videolist/watch/12288/genomic-medicine-bruce-korf-2014</guid>
	<pubDate>Tue, 24 Jun 2014 07:58:44 -0500</pubDate>
	<link>https://bioinformaticsonline.com/videolist/watch/12288/genomic-medicine-bruce-korf-2014</link>
	<title><![CDATA[Genomic Medicine - Bruce Korf (2014)]]></title>
	<description><![CDATA[<iframe width="" height="" src="https://www.youtube-nocookie.com/embed/FYldIrsXHKw" frameborder="0" allowfullscreen></iframe>May 21, 2014 - Current Topics in Genome Analysis 2014
A lecture series covering contemporary areas in genomics and bioinformatics. More: http://www.genome.gov/COURSE2014]]></description>
	
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/12787/integrative-genomics-viewer-igv-tutorial</guid>
	<pubDate>Sat, 12 Jul 2014 15:16:23 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/12787/integrative-genomics-viewer-igv-tutorial</link>
	<title><![CDATA[Integrative Genomics Viewer (IGV) tutorial]]></title>
	<description><![CDATA[<p>The <a href="http://www.broadinstitute.org/igv/">Integrative Genomics Viewer (IGV)</a> from the Broad Center allows you to view several types of data files involved in any NGS analysis that employs a reference genome, including how reads from a dataset are mapped, gene annotations, and predicted genetic variants.</p>
<p>http://www.broadinstitute.org/igv/</p><p>Address of the bookmark: <a href="https://wikis.utexas.edu/display/bioiteam/Integrative+Genomics+Viewer+%28IGV%29+tutorial" rel="nofollow">https://wikis.utexas.edu/display/bioiteam/Integrative+Genomics+Viewer+%28IGV%29+tutorial</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/12936/assistant-professor-medical-bioinformatics</guid>
  <pubDate>Wed, 23 Jul 2014 05:00:38 -0500</pubDate>
  <link></link>
  <title><![CDATA[Assistant Professor - Medical Bioinformatics]]></title>
  <description><![CDATA[
<p>Advt. No : ME-I/A-IV/03/14</p>

<p>No.of Posts:01 (SC)</p>

<p>Pay Scale:</p>

<p>Pay Band of Rs.15600-39100 + Rs.6000/- GP +NPA @ 25% of Basic Pay +Learning Resource Allowance @ Rs.20,000/-P.A.+ Conveyance Allowance @ Rs. 1650/-P.M.+ Academic Allowance @ Rs.2500/- P.M. and other admissible allowances.</p>

<p>Qualifications:</p>

<p>Area of Specialization:-</p>

<p>Bioinformatics/Computational/Biology/Genomics/ Proteomics/ Structural Biology</p>

<p>1. Postgraduate qualification, e.g. Master’s Degree in Biotechnology/Bioinformatics/ Biophysics.</p>

<p>2. A Doctorate Degree of recognized University/Institute in a basic or allied Medical Science subject e.g. Medical Biotechnology/Biophysics. Bioinformatics/X-ray Crystallography/</p>

<p>Immunology/Structural Biology etc</p>

<p>Experience:</p>

<p>1.Minimum three years teaching and/or research experience in a recognized medical/research Institution in an allied medical subject after obtaining doctorate degree and preferably in Medical</p>

<p>Molecular Biology/ Biophysics/Structural Biology/Genomics and Clinical Proteomics/Computational Biology.</p>

<p>2. Minimum two publication with atleast one in international journal and atleast one as first author</p>

<p>Desirable:-</p>

<p>Consistently excellent scholastic/academic record, demonstrated ability to write grant proposal/(s) successfully, Post Doctoral training in a frontier area of medical Bioinformatics Research and of direct relevance to clinical diagnosis or patient care (preferably from a recognized top-ranking medical institution abroad)</p>

<p>Send your applications to O/O, Deputy Registrar, Recruitment &amp; Establishment Cell, University of Health Sciences, Rohtak by 08.7.2014</p>

<p>For more details,please visit website:http://pgimsrohtak.nic.in/2014%20AP%20Advt.pdf</p>
]]></description>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38526/versatile-genome-assembly-evaluation-with-quast-lg</guid>
	<pubDate>Fri, 21 Dec 2018 22:06:31 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38526/versatile-genome-assembly-evaluation-with-quast-lg</link>
	<title><![CDATA[Versatile genome assembly evaluation with QUAST-LG]]></title>
	<description><![CDATA[<p>QUAST-LG is an extension of&nbsp;<a href="http://cab.spbu.ru/software/quast/">QUAST</a>&nbsp;intended for evaluating large-scale genome assemblies (up to mammalian-size).</p>
<p>QUAST-LG&nbsp;is included in the QUAST&nbsp; package starting from version 5.0.0 (<a href="https://sourceforge.net/projects/quast/files/latest/download?source=files">download the latest release</a>). Run QUAST as usual and do not forget to add&nbsp;<span>‐‐large</span>&nbsp;option to your command!</p>
<p>A short list of the new features (see&nbsp;<a href="http://cab.spbu.ru/files/quast/latest-docs/CHANGES.txt">CHANGES</a>&nbsp;for all):</p>
<ul>
<li>Significant speedup achieved by both&nbsp;use of new fast aligner (<a href="https://github.com/lh3/minimap2">minimap2</a>) and the refactoring of alignment analyzing&nbsp;modules</li>
<li>New k-mer-based completeness and correctness metrics</li>
<li>BUSCO added for enhanced reference-free analysis</li>
<li>The concept of upper bound&nbsp;assembly (theoretical limits on the assembly&nbsp;completeness and&nbsp;contiguity for a given genome and set of reads)</li>
</ul><p>Address of the bookmark: <a href="http://cab.spbu.ru/software/quast-lg/" rel="nofollow">http://cab.spbu.ru/software/quast-lg/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/13025/the-5-reasons-to-mistakes-at-bioinformatics-work</guid>
	<pubDate>Thu, 24 Jul 2014 02:51:41 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/13025/the-5-reasons-to-mistakes-at-bioinformatics-work</link>
	<title><![CDATA[The 5 reasons to mistakes at bioinformatics work !!!]]></title>
	<description><![CDATA[<p>When you're just starting out with biological programming, it's easy to run into complex problems that make you wonder how anyone has ever managed to write a program. There are some problems that trip up nearly every bioinformatician--everything from getting started understanding the biological problems to dealing with program design. Some random mistakes are so prominent that even experienced biological programmers do it. The 8 years in bioinformatics and my few random observations, most of them are snarky. These reasons will always take longer than expected and compel you to postpone your project deadline.</p><p><strong>1.Stupid for biologist:</strong> Biology is so complex that it will make bioinformatician feel stupid. There are no any universal fixed rules; it can surprise you any time. So be nice to biologists who ask questions and resolve your biological puzzles. Sometime you will have no idea what the hell you were doing either.<br /><br /><strong>2.Puzzling why:</strong> Do not hesitate to ask question. Especially. at the beginning of project you will have to ask a lot of questions. Instead of puzzling it out at end check out and clear your doubt even for a single error. It may can leads to wrong conclusion.<br /><br /><strong>3.Running marathon:</strong> The most of the biological software&rsquo;s documentation is always incomplete. In other word they are no more than 95 percent complete. Sometime a single problem can halt your entire project for months. Compilation and running the pipelines in tedious because almost all are interdependent and need proper configuration. I face the same kind of problem with Evolver :( &hellip; <br /><br /><strong>4.Folders missing:</strong> The pipelines generate lots of data, and we keep them in several folders for future use. But sometime we delete them by mistake and move to recovery&hellip;<br /><br /><strong>5.Digging deeper:</strong> Digging deeper is fruitful, but some time it can be catastrophic. You may get frustrated or direction less. So keep a biologist with you for rescue &hellip;. Sometime an expert computer programmer to handle your server. Remember, the server will always go down when you need it the most.<br /><br />The most common frustrating&nbsp; common line: Why do we do this again?</p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38670/ltr-finder-an-efficient-program-for-finding-full-length-ltr-retrotranspsons-in-genome-sequences</guid>
	<pubDate>Sun, 13 Jan 2019 07:05:53 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38670/ltr-finder-an-efficient-program-for-finding-full-length-ltr-retrotranspsons-in-genome-sequences</link>
	<title><![CDATA[LTR_Finder: an efficient program for finding full-length LTR retrotranspsons in genome sequences.]]></title>
	<description><![CDATA[<p>LTR_Finder is an efficient program for finding full-length LTR retrotranspsons in genome sequences.</p>
<p>The Program first constructs all exact match pairs by a suffix-array based algorithm and extends them to long highly similar pairs. Then Smith-Waterman algorithm is used to adjust the ends of LTR pair candidates to get alignment boundaries. These boundaries are subject to re-adjustment using supporting information of TG..CA box and TSRs and reliable LTRs are selected. Next, LTR_FINDER tries to identify PBS, PPT and RT inside LTR pairs by build-in aligning and counting modules. RT identification includes a dynamic programming to process frame shift. For other protein domains, LTR_FINDER calls ps_scan (from PROSITE,&nbsp;<a href="http://www.expasy.org/prosite/">http://www.expasy.org/prosite/</a>) to locate cores of important enzymes if they occur.</p><p>Address of the bookmark: <a href="https://github.com/xzhub/LTR_Finder" rel="nofollow">https://github.com/xzhub/LTR_Finder</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/13337/phd-opportunity-at-universite-de-liege-belgium</guid>
  <pubDate>Sat, 02 Aug 2014 01:12:43 -0500</pubDate>
  <link></link>
  <title><![CDATA[PhD opportunity at Université de Liège - Belgium]]></title>
  <description><![CDATA[
<p>PhD opportunity at Université de Liège - Belgium</p>

<p>The Bioinformatics and Systems Biology Unit of Université de Liège (Belgium) is looking for a highly motivated master student with programming skills for a PhD thesis project (4 years, fully funded) with the goal of designing computational tools that use literature, genomic and structural data in order to infer regulatory and metabolic networks.  </p>

<p>Applicants are invited to send their resume and a recommendation letter to Prof. Patrick Meyer (more details at   www.biosys.ulg.ac.be )</p>

<p>For more information : www.biosys.ulg.ac.be</p>
]]></description>
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