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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/2464?offset=320</link>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/videolist/watch/11249/how-to-sequence-the-human-genome-mark-j-kiel</guid>
	<pubDate>Fri, 30 May 2014 13:24:11 -0500</pubDate>
	<link>https://bioinformaticsonline.com/videolist/watch/11249/how-to-sequence-the-human-genome-mark-j-kiel</link>
	<title><![CDATA[How to sequence the human genome - Mark J. Kiel]]></title>
	<description><![CDATA[<iframe width="" height="" src="https://www.youtube-nocookie.com/embed/MvuYATh7Y74" frameborder="0" allowfullscreen></iframe>View full lesson: http://ed.ted.com/lessons/how-to-sequence-the-human-genome-mark-j-kiel

Your genome, every human's genome, consists of a unique DNA sequence of A's, T's, C's and G's that tell your cells how to operate. Thanks to technological advances, scientists are now able to know the sequence of letters that makes up an individual genome relatively quickly and inexpensively. Mark J. Kiel takes an in-depth look at the science behind the sequence.

Lesson by Mark J. Kiel, animation by Marc Christoforidis.]]></description>
	
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34088/sequence-evolution-function-computational-approaches-in-comparative-genomics</guid>
	<pubDate>Sun, 06 Aug 2017 06:58:12 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34088/sequence-evolution-function-computational-approaches-in-comparative-genomics</link>
	<title><![CDATA[Sequence - Evolution - Function; Computational Approaches in Comparative Genomics]]></title>
	<description><![CDATA[<p><em>Sequence - Evolution - Function</em><span>&nbsp;is an introduction to the computational approaches that play a critical role in the emerging new branch of biology known as functional genomics. The book provides the reader with an understanding of the principles and approaches of functional genomics and of the potential and limitations of computational and experimental approaches to genome analysis.</span></p><p>Address of the bookmark: <a href="https://www.ncbi.nlm.nih.gov/books/NBK20260/" rel="nofollow">https://www.ncbi.nlm.nih.gov/books/NBK20260/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/34929/shendurelab</guid>
  <pubDate>Thu, 28 Dec 2017 09:57:50 -0600</pubDate>
  <link></link>
  <title><![CDATA[ShendureLab]]></title>
  <description><![CDATA[
<p>The mission of our lab is to develop and apply new technologies and methods for genetics, genomics and molecular biology. Most of our work exploits next-generation DNA sequencing which is effectively emerging as a broadly enabling microscope for the measurement of biological phenomena. Our ongoing work generally falls into six areas. These are listed below as links to representative publications in each area.</p>

<p>Developing New Molecular Methods</p>

<p>Genomic Approaches to Developmental Biology</p>

<p>Massively Parallel Functional Genomics</p>

<p>Translating Genomics to the Clinic</p>

<p>Genetic Basis of Human Disease</p>

<p>Genome Sequencing Technologies</p>

<p>http://krishna.gs.washington.edu/index.html<br />http://www.gs.washington.edu/faculty/shendure.htm</p>
]]></description>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/11434/adhoc-bioinformatics-faculty-position-nit</guid>
  <pubDate>Tue, 03 Jun 2014 16:19:52 -0500</pubDate>
  <link></link>
  <title><![CDATA[Adhoc Bioinformatics Faculty Position @ NIT]]></title>
  <description><![CDATA[
<p>NATIONAL INSTITUTE OF TECHNOLOGY, DEPARTMENT OF BIOTECHNOLOGY, WARANGAL – 506 021, Andhra Pradesh</p>

<p>No.NITW/BT/2014/adhoc</p>

<p>APPLICATIONS ARE INVITED FOR THE APPOINTMENT OF ADHOC FACULTY ON CONTRACT BASIS IN THE DEAPARTMENT OF BIOTECHNOLOGY</p>

<p>Period of Contract: Initially the appointment is for one semester i.e., from July 2014 up to December 2014 only.</p>

<p>Essential Qualifications:</p>

<p>i) B. Tech or equivalent in Biotechnology/ Industrial Biotechnology/ Biochemical Engineering / Chemical Engg. Or M. Sc in Microbiology/ Botany/ Zoology/ Biochemistry/Biotechnology and ii) M. Tech or equivalent in Biotechnology/Industrial Biotechnology/Bioinformatics</p>

<p>Or</p>

<p>Integrated M. Tech in Biotechnology/Industrial Biotechnology/ Bioinformatics</p>

<p>Candidates must possess First class (60% aggregate marks or 6.5 CGPA) at B. Tech/ M. Sc and M. Tech.</p>

<p>Desirable: Ph. D Pay Package: All selected candidates shall be eligible for a consolidated pay of Rs.30, 000/- per month. Candidates with Ph. D shall be eligible for an additional amount of Rs.5, 000/- per month.</p>

<p>How to apply : Applications on plain paper with attested photocopies of certificate and bio data along with justification for eligibility should reach to the Head, Department of Biotechnology, National Institute of Technology, Warangal AP 506004 in the form of soft or hard copy on or before 21st June 2014 email : biotech_hod@nitw.ac.in</p>

<p>Intimation: No separate call letters will be sent to the candidates. All the eligible candidates will be notified in the institute web site on 23rd June 2014. All the eligible candidates are requested to report for the interview to the Head, Department of Biotechnology at 9:00 AM on 27th June 2014</p>

<p>Joining: Selected candidates will be informed and they are expected to join immediately.</p>

<p>Advertisement:</p>

<p>http://www.nitw.ac.in/nitw/announcements/2014/Bio-Adhoc%20Advt.%20May-2014.pdf</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37257/asar-advanced-metagenomic-sequence-analysis-in-r</guid>
	<pubDate>Mon, 09 Jul 2018 05:20:50 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37257/asar-advanced-metagenomic-sequence-analysis-in-r</link>
	<title><![CDATA[ASAR: Advanced metagenomic Sequence Analysis in R]]></title>
	<description><![CDATA[<p><span>An interactive data analysis tool for selection, aggregation and visualization of metagenomic data is presented. Functional analysis with a SEED hierarchy and pathway diagram based on KEGG orthology based upon MG-RAST annotation results is available.</span></p>
<p><span><span>To read the manual, please click the link&nbsp;</span><a href="https://askarbek-orakov.github.io/ASAR/">https://askarbek-orakov.github.io/ASAR/</a></span></p><p>Address of the bookmark: <a href="https://github.com/Askarbek-orakov/ASAR" rel="nofollow">https://github.com/Askarbek-orakov/ASAR</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/11735/search-shell-command-history</guid>
	<pubDate>Thu, 12 Jun 2014 17:43:34 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/11735/search-shell-command-history</link>
	<title><![CDATA[Search Shell Command History]]></title>
	<description><![CDATA[<p>We use couple of hundreads of command in daily basis. Most of them are actually repeated several time. The question remain open how do I search old command history under bash shell and modify or reuse it? <br /><br />Now a days almost all modern shell allows you to search command history if enabled by user. Use history command to display the history list with line numbers. Lines listed with with a * have been modified by user.</p><p><br /><strong>Shell history search command</strong><br /><br />Type history at a shell prompt:<br />$ history</p><p>It will display the list of all used commandline history with an serial number.<br /><br />To search particular command, enter:<br />$ history | grep command-name<br />$ history | egrep -i 'scp|ssh|ftp'<br />Emacs Line-Edit Mode Command History Searching<br /><br />To get previous command containing string, hit [CTRL]+[r] followed by search string:<br /><br />(reverse-i-search): <br /><br />To get previous command, hit [CTRL]+[p]. You can also use up arrow key.<br /><br />CTRL-p<br /><br />To get next command, hit [CTRL]+[n]. You can also use down arrow key.<br /><br />CTRL-n<br /><br /></p><p><strong>fc command</strong></p><p>Apart from hostory command there are fc command to extract the command from history. The fc stands for either "find command" or "fix command.</p><p>For example list last 10 command, enter:<br />$ fc -l 10<br />To list commands 130 through 150, enter:<br />$ fc -l 130 150<br />To list all commands since the last command beginning with ssh, enter:<br />$ fc -l ssh<br />You can edit commands 1 through 5 using vi text editor, enter:<br />$ fc -e vi 1 5</p><p><strong>Delete command history</strong><br /><br />The -c option causes the history list to be cleared by deleting all of the entries:<br />$ history -c</p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40955/the-global-alliance-for-genomics-and-health-ga4gh</guid>
	<pubDate>Sat, 08 Feb 2020 07:37:31 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40955/the-global-alliance-for-genomics-and-health-ga4gh</link>
	<title><![CDATA[The Global Alliance for Genomics and Health (GA4GH)]]></title>
	<description><![CDATA[<p>The Global Alliance for Genomics and Health (GA4GH) is a policy-framing and technical standards-setting organization, seeking to enable responsible genomic data sharing within a <a href="https://www.ga4gh.org/genomic-data-toolkit/regulatory-ethics-toolkit/framework-for-responsible-sharing-of-genomic-and-health-related-data/">human rights framework</a>.</p>
<p>GA4GH core funders and sponsors enable our work and allow us to convene the international genomic data sharing community.</p>
<p>https://www.ga4gh.org/</p><p>Address of the bookmark: <a href="https://www.ga4gh.org/" rel="nofollow">https://www.ga4gh.org/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/11609/bioinformatician%E2%80%99s-pocket-reference</guid>
	<pubDate>Sun, 08 Jun 2014 09:56:58 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/11609/bioinformatician%E2%80%99s-pocket-reference</link>
	<title><![CDATA[Bioinformatician’s Pocket Reference !!]]></title>
	<description><![CDATA[<p><span>It is amusing how brain of bioinformaticians work! Learning a new programming language for days feels so much of fun that making 5 minute discussion with neighbours (unless under special circumstances!) in our own mother-tongue. Today every bioinformatician keeps more than few languages and core IT toolkits on their plate. It has become mandatory to be able to mould different code snippets to build our own custom workflows, and thus keeping syntax at our fingertips has become essential.Although Google is best way to get syntax problem solved, it is not a bad idea to keep reference sheets is our smartphones or stick out some printed sheets on the back of your door, in the old fashion way!!</span></p><p>Address of the bookmark: <a href="http://infoplatter.wordpress.com/2014/04/06/bioinformaticians-pocket-reference/" rel="nofollow">http://infoplatter.wordpress.com/2014/04/06/bioinformaticians-pocket-reference/</a></p>]]></description>
	<dc:creator>RAJESH DETROJA</dc:creator>
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<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/42470/the-new-corona-variant-has-23-mutations-in-all-which-is-unusually-huge</guid>
	<pubDate>Wed, 23 Dec 2020 03:50:50 -0600</pubDate>
	<link>https://bioinformaticsonline.com/news/view/42470/the-new-corona-variant-has-23-mutations-in-all-which-is-unusually-huge</link>
	<title><![CDATA[The new corona variant has 23 mutations in all, which is unusually huge !]]></title>
	<description><![CDATA[<p>The new SARS-CoV-2 version, B.1.1.7, which was first seen in the third week of September in Kent and Greater London, has since spread to other locations in the UK. According to the COVID-19 Genomics UK Consortium (COG-UK Consortium) that analysed the genome data of the virus and identified the variant, the new variant has been spreading "rapidly" over the last four weeks and has now been detected in other locations in the UK, suggesting further spread of the variant in the region.</p><p><span>According to a<span>&nbsp;</span></span><a href="https://virological.org/t/preliminary-genomic-characterisation-of-an-emergent-sars-cov-2-lineage-in-the-uk-defined-by-a-novel-set-of-spike-mutations/563"><strong><span>preliminary report</span></strong></a><span><span>&nbsp;</span>posted on December 19 by the COG-UK Consortium scientists, as of December 15, 1,623 variant genomes have been sequenced. In a<span>&nbsp;</span></span><a href="https://twitter.com/TheCGPS/status/1340749351803629569"><strong><span>December 21 tweet</span></strong></a><span>, COG-UK Consortium said that it added 2,963 more genome sequences of SARS-CoV-2, of which 942 (32%) belong to the new variant. The Consortium<span>&nbsp;</span></span><a href="https://twitter.com/CovidGenomicsUK/status/1341073233420955654"><strong><span>intends to sequence</span></strong></a><span><span>&nbsp;</span>20,000 more SARS-CoV-2 genomes in the next two weeks to further ascertain the spread of the variant.</span></p><p><span>There is no clear proof, at least not yet, that it does cause severe pandemic. But there is a justification for seriously taking the possibility. Another coronavirus lineage in South Africa has acquired one specific mutation that is also present in B.1.1.7. This variant is increasingly spreading across South Africa's coastal regions. And doctors have observed in preliminary research that individuals infected with this variant bear a higher viral load-a higher concentration of the virus in their upper respiratory tract. In many viral diseases, this is associated with more severe symptoms.</span></p><p>&nbsp;</p>]]></description>
	<dc:creator>Shruti Paniwala</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43362/machine-learning-for-genomics</guid>
	<pubDate>Thu, 09 Sep 2021 11:26:32 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43362/machine-learning-for-genomics</link>
	<title><![CDATA[Machine Learning for Genomics]]></title>
	<description><![CDATA[<h3>Module 1: Statistics for genomics (2-8 August 2021)</h3>
<ul>
<li>A simple intro to statistical distributions</li>
<li>hypothesis testing</li>
<li>linear models.</li>
</ul>
<p>reading:&nbsp;<a href="http://compgenomr.github.io/book/stats.html">http://compgenomr.github.io/book/stats.html</a></p>
<p>slides:&nbsp;<a href="https://github.com/BIMSBbioinfo/compgen2021/tree/main/week1/compgen2021_stats.pdf">https://github.com/BIMSBbioinfo/compgen2021/tree/main/week1/compgen2021_stats.pdf</a></p>
<p>exercises+code:&nbsp;<a href="https://github.com/BIMSBbioinfo/compgen2021/tree/main/week1/">https://github.com/BIMSBbioinfo/compgen2021/tree/main/week1/</a></p>
<h3><a href="https://github.com/BIMSBbioinfo/compgen2021#module-2-unsupervised-learning-for-genomics-9-15-august-2021"></a>Module 2: Unsupervised learning for genomics (9-15 August 2021)</h3>
<ul>
<li>Understanding basic intuition behind machine learning approaches.</li>
<li>Using unsupervised learning to cluster and visualise data points</li>
<li>Dimension reduction techniques for visualisation and as input to clustering methods</li>
</ul>
<p>reading:&nbsp;<a href="http://compgenomr.github.io/book/unsupervisedLearning.html">http://compgenomr.github.io/book/unsupervisedLearning.html</a></p>
<p>slides:&nbsp;<a href="https://github.com/BIMSBbioinfo/compgen2021/tree/main/week2/compgen2021_unsupervisedLearning.pdf">https://github.com/BIMSBbioinfo/compgen2021/tree/main/week2/compgen2021_unsupervisedLearning.pdf</a></p>
<p>exercises+code:&nbsp;<a href="https://github.com/BIMSBbioinfo/compgen2021/tree/main/week2/">https://github.com/BIMSBbioinfo/compgen2021/tree/main/week2/</a></p>
<h3><a href="https://github.com/BIMSBbioinfo/compgen2021#module-3-supervised-learning-for-genomics-16-22-august-2021"></a>Module 3: Supervised learning for genomics (16-22 August 2021)</h3>
<ul>
<li>Understanding and using supervised learning methods for predictive purposes</li>
<li>How to measure prediction performance</li>
<li>Understand and use cross-validation and related concepts</li>
</ul>
<p>reading:&nbsp;<a href="http://compgenomr.github.io/book/supervisedLearning.html">http://compgenomr.github.io/book/supervisedLearning.html</a></p>
<p>slides:&nbsp;<a href="https://github.com/BIMSBbioinfo/compgen2021/tree/main/week3/compgen2021_supervisedLearning.pdf">https://github.com/BIMSBbioinfo/compgen2021/tree/main/week3/compgen2021_supervisedLearning.pdf</a></p>
<p>exercises+code:&nbsp;<a href="https://github.com/BIMSBbioinfo/compgen2021/tree/main/week3/">https://github.com/BIMSBbioinfo/compgen2021/tree/main/week3/</a></p>
<p>https://github.com/BIMSBbioinfo/compgen2021</p><p>Address of the bookmark: <a href="https://github.com/BIMSBbioinfo/compgen2021" rel="nofollow">https://github.com/BIMSBbioinfo/compgen2021</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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