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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/37514?offset=240</link>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/34711/1mb-long-dna-with-nanopore-technology</guid>
	<pubDate>Tue, 19 Dec 2017 18:49:28 -0600</pubDate>
	<link>https://bioinformaticsonline.com/news/view/34711/1mb-long-dna-with-nanopore-technology</link>
	<title><![CDATA[1mb long DNA with Nanopore technology]]></title>
	<description><![CDATA[<p>The first continuous DNA read of more than a million bases (&gt;1Mb) has been achieved, using Oxford Nanopore sequencing technology. Congratulations to Martin Smith and collaborators! Read more: http://bit.ly/2j5TNCO</p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37835/variantbam-filtering-and-profiling-of-next-generational-sequencing-data-using-region-specific-rules</guid>
	<pubDate>Thu, 04 Oct 2018 16:30:44 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37835/variantbam-filtering-and-profiling-of-next-generational-sequencing-data-using-region-specific-rules</link>
	<title><![CDATA[VariantBam: Filtering and profiling of next-generational sequencing data using region-specific rules]]></title>
	<description><![CDATA[<p>VariantBam is a tool to extract/count specific sets of sequencing reads from next-generational sequencing files. To save money, disk space and I/O, one may not want to store an entire BAM on disk. In many cases, it would be more efficient to store only those read-pairs or reads who intersect some region around the variant locations. Alternatively, if your scientific question is focused on only one aspect of the data (e.g. breakpoints), many reads can be removed without losing the information relevant to the problem.</p>
<h5>&nbsp;</h5><p>Address of the bookmark: <a href="https://github.com/broadinstitute/VariantBam" rel="nofollow">https://github.com/broadinstitute/VariantBam</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38535/nanopack-visualizing-and-processing-long-read-sequencing-data</guid>
	<pubDate>Tue, 25 Dec 2018 21:20:50 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38535/nanopack-visualizing-and-processing-long-read-sequencing-data</link>
	<title><![CDATA[NanoPack: visualizing and processing long-read sequencing data]]></title>
	<description><![CDATA[The NanoPack tools are written in Python3 and released under the GNU GPL3.0 License. The source code can be found at https://github.com/wdecoster/nanopack, together with links to separate scripts and their documentation. The scripts are compatible with Linux, Mac OS and the MS Windows 10 subsystem for Linux and are available as a graphical user interface, a web service at http://nanoplot.bioinf.be and command line tools.<p>Address of the bookmark: <a href="https://github.com/wdecoster/nanopack" rel="nofollow">https://github.com/wdecoster/nanopack</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40754/understanding-your-reads-and-mapping</guid>
	<pubDate>Wed, 29 Jan 2020 06:29:55 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40754/understanding-your-reads-and-mapping</link>
	<title><![CDATA[Understanding your reads and mapping !]]></title>
	<description><![CDATA[<p>One of the best tutorial for beginners ...</p>
<p>https://bioinformatics-core-shared-training.github.io/cruk-summer-school-2017/Day1/Session4-seqIntro.html</p><p>Address of the bookmark: <a href="https://bioinformatics-core-shared-training.github.io/cruk-summer-school-2017/Day1/Session4-seqIntro.html" rel="nofollow">https://bioinformatics-core-shared-training.github.io/cruk-summer-school-2017/Day1/Session4-seqIntro.html</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/5254/mike-ritchie-lab</guid>
  <pubDate>Wed, 02 Oct 2013 15:25:45 -0500</pubDate>
  <link></link>
  <title><![CDATA[Mike Ritchie Lab]]></title>
  <description><![CDATA[
<p>Mike Ritchie Lab primary research focus is the detection of susceptibility genes for common diseases such as cancer, diabetes, hypertension, and cardiovascular disease, among others. The approaches will involve the development and application of new statistical methods with a focus on the detection of gene-gene interactions associated with human disease.</p>

<p>Gene expression and protein expression patterns between normal and non-normal tissues is a growing area of research that may lead to the identification of candidate genes for understanding the etiology of common, complex diseases. </p>

<p>Lab homepage @ http://ritchielab.psu.edu/ritchielab/</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/11611/ten-recommendations-for-creating-usable-bioinformatics-command-line-software</guid>
	<pubDate>Sun, 08 Jun 2014 10:06:26 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/11611/ten-recommendations-for-creating-usable-bioinformatics-command-line-software</link>
	<title><![CDATA[Ten recommendations for creating usable bioinformatics command line software]]></title>
	<description><![CDATA[<p><span>Bioinformatics software varies greatly in quality. In terms of usability, the command line interface is the first experience a user will have of a tool. Unfortunately, this is often also the last time a tool will be used. Here I present ten recommendations for command line software author&rsquo;s tools to follow, which I believe would greatly improve the uptake and usability of their products, waste less user&rsquo;s time, and improve the quality of scientific analyses.</span></p><p>Address of the bookmark: <a href="http://www.gigasciencejournal.com/content/2/1/15?utm_content=buffer25ee0&amp;utm_medium=social&amp;utm_source=twitter.com&amp;utm_campaign=buffer" rel="nofollow">http://www.gigasciencejournal.com/content/2/1/15?utm_content=buffer25ee0&amp;utm_medium=social&amp;utm_source=twitter.com&amp;utm_campaign=buffer</a></p>]]></description>
	<dc:creator>RAJESH DETROJA</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27432/gkno</guid>
	<pubDate>Fri, 20 May 2016 18:56:37 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27432/gkno</link>
	<title><![CDATA[GKNO]]></title>
	<description><![CDATA[<p><span>gkno opens the world of complex bioinformatic analysis to people of all level of computational expertise. This site contains documentation, tutorials and information on all the tools that comprise gkno.</span></p>
<p><span>http://gkno.me/how-to/install.html</span></p>
<p><span>http://gkno.me/software.html</span></p><p>Address of the bookmark: <a href="http://gkno.me/" rel="nofollow">http://gkno.me/</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/30833/dnasp-v5-a-software-for-comprehensive-analysis-of-dna-polymorphism-data</guid>
	<pubDate>Mon, 06 Feb 2017 04:45:37 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/30833/dnasp-v5-a-software-for-comprehensive-analysis-of-dna-polymorphism-data</link>
	<title><![CDATA[DnaSP v5: a software for comprehensive analysis of DNA polymorphism data]]></title>
	<description><![CDATA[<p><span>DnaSP is a software package for a comprehensive analysis of DNA polymorphism data. Version 5 implements a number of new features and analytical methods allowing extensive DNA polymorphism analyses on large datasets. Among other features, the newly implemented methods allow for: (i) analyses on multiple data files; (ii) haplotype phasing; (iii) analyses on insertion/deletion polymorphism data; (iv) visualizing sliding window results integrated with available genome annotations in the UCSC browser.</span></p><p>Address of the bookmark: <a href="http://www.ub.edu/dnasp/" rel="nofollow">http://www.ub.edu/dnasp/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34470/simngs-and-simlibrary-%E2%80%93-software-for-simulating-next-gen-sequencing-data</guid>
	<pubDate>Tue, 28 Nov 2017 06:49:11 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34470/simngs-and-simlibrary-%E2%80%93-software-for-simulating-next-gen-sequencing-data</link>
	<title><![CDATA[simNGS and simLibrary – Software for Simulating Next-Gen Sequencing Data]]></title>
	<description><![CDATA[<p>simNGS is software for simulating observations from Illumina sequencing machines using the statistical models behind the AYB base-calling software. By default, observations only incorporate noise due to sequencing and do not incorporate effects from more esoteric sources of noise that may be present in real data ("dust", bubbles, merged clusters, sequence-heterogeneous clusters, etc). Many of these additional sources may optionally applied.</p>
<p>simNGS takes fasta format sequences and a file describing the covariance of noise between bases and cycles observed in an actual run of the machine, randomly generates noisy intensities representing the signals for the sequence at each cycle and calculates likelihoods for all possible base calls.</p><p>Address of the bookmark: <a href="https://www.ebi.ac.uk/goldman-srv/simNGS/" rel="nofollow">https://www.ebi.ac.uk/goldman-srv/simNGS/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/42165/bioinformatics-scientistresearch-software-engineer-at-university-of-dundee-dundee-united-kingdom</guid>
  <pubDate>Wed, 26 Aug 2020 10:31:25 -0500</pubDate>
  <link></link>
  <title><![CDATA[Bioinformatics Scientist/Research Software Engineer at University of Dundee Dundee, United Kingdom]]></title>
  <description><![CDATA[
<p>We are recruiting for an exceptional individual to join us as a computational scientist, bioinformatician, or (research) software engineer with an interest in interactive data analysis platforms for biology and medicine within our Jalview (www.jalview.org) research software engineering team.</p>

<p>More at https://www.jobs.dundee.ac.uk/fe/tpl_uod01.asp?s=4A515F4E5A565B1A&amp;jobid=104342,2382988671&amp;key=147934117&amp;c=99413415238921&amp;pagestamp=sesxbbuyifokdsfygf</p>

<p>Last date: 30th August 2020</p>

<p>Informal enquiries about this position may be made to Prof. Geoff Barton (gjbarton@dundee.ac.uk) or Dr Jim Procter (jprocter@dundee.ac.uk). To find out more about Jalview research software engineering team please visit www.jalview.org and www.compbio.dundee.ac.uk</p>
]]></description>
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