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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/8509?offset=650</link>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36239/scilifelab-tutorial-for-bioinformatics-analysis</guid>
	<pubDate>Tue, 17 Apr 2018 04:33:00 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36239/scilifelab-tutorial-for-bioinformatics-analysis</link>
	<title><![CDATA[SciLifeLab tutorial for bioinformatics analysis !]]></title>
	<description><![CDATA[<p>SciLifeLab is a national center for molecular biosciences with focus on health and environmental research.</p>
<h2 id="courses">Courses</h2>
<p><a href="http://uppnex.se/twiki/bin/view/Courses/">Old courses (2012-2014)</a></p>
<h3 id="metagenomics-workshop">Metagenomics Workshop</h3>
<p><a href="https://scilifelab.github.io/courses/Metagenomics/1511/">2015 November - Uppsala</a><br><a href="https://scilifelab.github.io/courses/Metagenomics/1611/">2016 November - Uppsala</a><br><a href="https://scilifelab.github.io/courses/Metagenomics/1711/">2017 November - Uppsala</a></p>
<h3 id="introduction-to-bioinformatics-using-ngs-data">Introduction to Bioinformatics Using NGS Data</h3>
<p><a href="https://scilifelab.github.io/courses/ngsintro/1502/">2015 February - Uppsala</a>&nbsp;<br><a href="https://scilifelab.github.io/courses/ngsintro/1505/">2015 May - Gothenburg</a><br><a href="https://scilifelab.github.io/courses/ngsintro/1509/">2015 September - Uppsala</a><br><a href="https://scilifelab.github.io/courses/ngsintro/1511/">2015 November - Lund</a><br><a href="https://scilifelab.github.io/courses/ngsintro/1601/">2016 January - Uppsala</a><br><a href="https://scilifelab.github.io/courses/ngsintro/1604/">2016 April - Link&ouml;ping</a><br><a href="https://scilifelab.github.io/courses/ngsintro/1609/">2016 September - Uppsala</a><br><a href="https://scilifelab.github.io/courses/ngsintro/1611/">2016 November - Ume&aring;</a><br><a href="https://scilifelab.github.io/courses/ngsintro/1701/">2017 January - Uppsala</a><br><a href="https://scilifelab.github.io/courses/ngsintro/1705/">2017 May - Gothenburg</a><br><a href="https://scilifelab.github.io/courses/ngsintro/1709/">2017 September - Lund</a><br><a href="https://scilifelab.github.io/courses/ngsintro/1711/">2017 November - Uppsala</a><br><a href="https://scilifelab.github.io/courses/ngsintro/1802/">2018 February - Uppsala</a></p>
<h3 id="introduction-to-genome-annotation">Introduction to Genome Annotation</h3>
<p><a href="https://scilifelab.github.io/courses/annotation/2015/">2015 April - Uppsala</a><br><a href="https://scilifelab.github.io/courses/annotation/2016/">2016 April - Uppsala</a><br><a href="https://scilifelab.github.io/courses/annotation/2017/">2017 April - Uppsala</a><br><a href="https://scilifelab.github.io/courses/annotation/2018/">2018 May - Uppsala</a></p>
<h3 id="de-novo-genome-assembly">De Novo Genome Assembly</h3>
<p><a href="https://scilifelab.github.io/courses/assembly/1611/">2016 November - Uppsala</a><br><a href="https://scilifelab.github.io/courses/assembly/2017-11-15/">2017 November - Uppsala</a></p>
<h3 id="rna-seq-course">RNA-seq course</h3>
<p><a href="https://scilifelab.github.io/courses/rnaseq/1510/">2015 October - Uppsala</a><br><a href="https://scilifelab.github.io/courses/rnaseq/1604/">2016 April - Uppsala</a><br><a href="https://scilifelab.github.io/courses/rnaseq/1610/">2016 October - Uppsala</a><br><a href="https://scilifelab.github.io/courses/rnaseq/1703/">2017 March - Uppsala</a><br><a href="https://scilifelab.github.io/courses/rnaseq/1711/">2017 November - Uppsala</a><br><a href="https://scilifelab.github.io/courses/rnaseq/labs">RNAseq tutorials</a></p>
<h3 id="r-programming-foundations-for-life-scientists">R Programming Foundations for Life Scientists</h3>
<p><a href="https://scilifelab.github.io/courses/r_programming/1611/">2016 November - Uppsala</a><br><a href="https://scilifelab.github.io/courses/r_programming/1703/">2017 Mars - Uppsala</a></p>
<h3 id="single-cell-rna-sequencing-analysis">Single cell RNA sequencing analysis</h3>
<p><a href="https://scilifelab.github.io/courses/scrnaseq/1710/">2017 October - Uppsala</a></p><p>Address of the bookmark: <a href="https://scilifelab.github.io/courses/" rel="nofollow">https://scilifelab.github.io/courses/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/videolist/watch/2349/bioinformatics-understanding-of-living-systems-through-information-science</guid>
	<pubDate>Wed, 14 Aug 2013 11:50:17 -0500</pubDate>
	<link>https://bioinformaticsonline.com/videolist/watch/2349/bioinformatics-understanding-of-living-systems-through-information-science</link>
	<title><![CDATA[Bioinformatics -- Understanding of living systems through  information science]]></title>
	<description><![CDATA[<iframe width="" height="" src="https://www.youtube-nocookie.com/embed/6Ovd_GOM9-g" frameborder="0" allowfullscreen></iframe>Recently, the progress of the Human Genome Project, aiming to decode all human DNA sequences, has highlighted a research field called bioinformatics. In this new field, computers and techniques from information science are not just used as tools to advance life science research; they're expected to have a major impact on how we think about the life sciences.

Q. The main feature of bioinformatics is, it utilizes computers to analyze life. One is example is the genome. In all organisms, DNA contains genetic information, and this is called the genome. But the amount of information involved is huge, so recently, it's been read using next-generation sequencers, and analyzed by computers. In bioinformatics research, what we do is utilize those genome information to investigate the principles of life.

As an organism evolves, its genome sequence changes through sudden mutations. Additionally, at the genome level, mutations called rearrangements, such as inversions, transpositions, and duplications, occur. 

The genome comparison system developed by the Sakakibara Lab calculates homologous sequences called anchors, which are conserved between species. If the genome is considered as a long text, then anchors can be thought of as words.

Q. We're coming to understand the genomes of various organisms - not just humans, but monkeys, chimpanzees, bacteria, and so on. The first method used to analyze a genome is comparing it with the genomes of other organisms, to see where it's the same and where it's different. In that way, the content of the genome is decoded bit by bit, using computers. By contrast, in our method, we've developed software called Murasaki, which we also use to analyze large genomes, by comparing them with those of other organisms.

The Sakakibara Lab uses a next-generation sequencer at Keio University, along with a cluster machine with hundreds of CPUs. In this way, the Lab is analyzing genome mutations that cause cancer, and the genome of the natto production strain Bacillus subtilis.

Until now, genome analysis could only be done in national-scale projects. But now, next-generation sequencer development has made genome analysis possible in an ordinary lab. In a world-first achievement, the Sakakibara Lab has decoded the natto bacillus genome, through analysis using Keio's next-generation sequencer.

Q. In the future, biology and the life sciences may become almost entirely information science and computer science. And in healthcare, that may enable us, for example, to predict whether individuals are susceptible to cancer, or to certain lifestyle-related diseases, by understanding their personal genome data. So, I think it's amply possible that we can make use of such information effectively, to help people live longer and be free from disease, by thinking about their lifestyle habits.
 
Bioinformatics is only two decades old. In this field, many areas are still unknown. Professor Sakakibara, having been involved since the beginning, will continue tackling new, challenging research projects.]]></description>
	
</item>
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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/researchlabs/view/4547/bioinformatics-infrastructure-facility</guid>
  <pubDate>Sun, 15 Sep 2013 09:22:25 -0500</pubDate>
  <link></link>
  <title><![CDATA[Bioinformatics Infrastructure Facility]]></title>
  <description><![CDATA[
<p>The Bioinformatics Infrastructure Facility has started working in the year 2007 at Presidency College, Kolkata. It is one of the premier institutes of India and boasts of a rich heritage and great alumni. The Infrastructure Facility has a dedicated team headed by Sayak Ganguli and ably supported by Priayanka Dhar. The coordinator of the facility is Abhijit Datta of the Post Graduate Department of Botany. The lab mainly focusses on the analysis of the RNA Induced Silencing Complex. Recent highlights include the presentation of a paper at the RNAi World Congress.</p>

<p>More @ http://bioinfo-presiuniv.edu.in/index.php</p>
]]></description>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/38590/senior-bioinformatics-scientist-strand-life-sciences-bangalore-india</guid>
  <pubDate>Wed, 02 Jan 2019 09:23:49 -0600</pubDate>
  <link></link>
  <title><![CDATA[Senior Bioinformatics Scientist @ Strand Life Sciences -- Bangalore, India]]></title>
  <description><![CDATA[
<p>RESPONSIBILITIES<br />The candidate is expected to work on a variety of projects related to analysis of data from NGS, Mass Spectrometry, Flow Cytometry and other related modalities. The position expects hands-on work and a strong eye for detail. The candidate will be able to contribute to impactful work spanning patient care, clinical research, and new assay and method development.<br />REQUIREMENTS<br />A PhD in a quantitative field (statistics, math, bioinformatics, computer science, physics or similar) and work experience or post-doc experience handling high throughout genomics data.<br />PREFERENCES<br />Experience in working in inter-disciplinary groups and ability to author research publications are additional desired qualities.<br />LOCALE<br />The position is in Bangalore and reports to the Chief Scientific Officer.<br />HOW TO APPLY<br />Write to ramesh[at]strandls.com.</p>
]]></description>
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<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/40226/bioinformatics-training-courses-at-rasa-lsi</guid>
	<pubDate>Wed, 06 Nov 2019 00:30:51 -0600</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/40226/bioinformatics-training-courses-at-rasa-lsi</link>
	<title><![CDATA[Bioinformatics Training Courses At RASA LSI]]></title>
	<description><![CDATA[<p>RASA conducts comprehensive Life Science skill development training courses in Pune, India for working professionals, researchers, students and job-seeker. The trainings are crafted meticulously, covering different modules of courses such as Bioinformatics course, In silico Drug Discovery course, Next Generation Sequence data analysis course, Molecular Biology &amp; Life&nbsp;science software development course wherein you learn from industry leaders&nbsp;how to apply these skills in life science &amp; have a command over software developing process &nbsp;by using various methodologies. We conduct in-class training and instructor-led live online classes worldwide, along with corporate and skill development training worldwide.</p><p>Workshops are conducted in regular intervals on Drug Designing, Protein Modeling and Simulation, Chemoinformatics, Bioinformatics etc.The workshops are highly beneficial for working professionals, students, researcher for enhancements of the skills in short duration.</p>]]></description>
	<dc:creator>RASA Life Sciences</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40489/machine-learning-training-and-courses-in-bioinformatics</guid>
	<pubDate>Tue, 31 Dec 2019 19:33:07 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40489/machine-learning-training-and-courses-in-bioinformatics</link>
	<title><![CDATA[Machine learning training and courses in bioinformatics !]]></title>
	<description><![CDATA[<p>Machine learning techniques have been successful in analyzing biological data because of their capabilities in handling randomness and uncertainty of data noise and in generalization. In this class, we will learn basics about probabilistic models and machine learning techniques. We will focus on probabilistic models (Markov models, Hidden Markov models, and Bayesian networks) for biological sequence analysis and systems biology. Other machine learning techniques, such as Naive bayes, neural networks and SVMs will only be covered briefly.</p>
<p>More at&nbsp;http://homes.sice.indiana.edu/yye/lab/teaching/spring2017-I529/</p>
<p>More tutorial at&nbsp;</p>
<p><a href="http://calla.rnet.missouri.edu/cheng_courses/mlbioinfo/mlbioinfo.htm">http://calla.rnet.missouri.edu/cheng_courses/mlbioinfo/mlbioinfo.htm</a></p>
<p><a href="http://www.raetschlab.org/lectures/MLBioinformatics">http://www.raetschlab.org/lectures/MLBioinformatics</a></p>
<p><a href="http://www.raetschlab.org/lectures/bertinoro08">http://www.raetschlab.org/lectures/bertinoro08</a></p>
<p>Book at&nbsp;</p>
<p><a href="https://personal.utdallas.edu/~pradiptaray/teaching/7_deep_learning_bioinfo.pdf">https://personal.utdallas.edu/~pradiptaray/teaching/7_deep_learning_bioinfo.pdf</a></p><p>Address of the bookmark: <a href="http://homes.sice.indiana.edu/yye/lab/teaching/spring2017-I529/" rel="nofollow">http://homes.sice.indiana.edu/yye/lab/teaching/spring2017-I529/</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/3046/r-and-bioconductor-tutorial</guid>
	<pubDate>Fri, 23 Aug 2013 08:23:59 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/3046/r-and-bioconductor-tutorial</link>
	<title><![CDATA[R and Bioconductor Tutorial]]></title>
	<description><![CDATA[<p>This tutorial is intended to introduce users quickly to the basics of R, focusing on a few common tasks that &nbsp;biologists need to perform &nbsp;some basic analysis: &nbsp;load a table, plot some graphs, and perform some basic statistics. More extensive tutorials can be found on the project website and via bioconductor (not covered here).</p>
<p>You can add more tutorial links in comments if found new pages.</p><p>Address of the bookmark: <a href="http://manuals.bioinformatics.ucr.edu/home/R_BioCondManual" rel="nofollow">http://manuals.bioinformatics.ucr.edu/home/R_BioCondManual</a></p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41991/sequence-ontology-bioinformatics-analysis-soba-tool-to-provide-a-simple-statistical-and-graphical-summary-of-an-annotated-genome</guid>
	<pubDate>Wed, 22 Jul 2020 10:11:13 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41991/sequence-ontology-bioinformatics-analysis-soba-tool-to-provide-a-simple-statistical-and-graphical-summary-of-an-annotated-genome</link>
	<title><![CDATA[Sequence Ontology Bioinformatics Analysis (SOBA) tool to provide a simple statistical and graphical summary of an annotated genome]]></title>
	<description><![CDATA[<p><span>We have developed the Sequence Ontology Bioinformatics Analysis (SOBA) tool to provide a simple statistical and graphical summary of an annotated genome. We envisage its use during annotation jamborees, genome comparison and for use by developers for rapid feedback during annotation software development and testing. SOBA also provides annotation consistency feedback to ensure correct use of terminology within annotations, and guides users to add new terms to the Sequence Ontology when required. SOBA is available at http://www.sequenceontology.org/cgi-bin/soba.cgi.</span></p>
<p><span>More at <a href="https://pubmed.ncbi.nlm.nih.gov/20494974/">https://pubmed.ncbi.nlm.nih.gov/20494974/</a></span></p><p>Address of the bookmark: <a href="http://www.sequenceontology.org/cgi-bin/soba.cgi" rel="nofollow">http://www.sequenceontology.org/cgi-bin/soba.cgi</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/videolist/watch/4043/what-is-bioinformatics</guid>
	<pubDate>Wed, 28 Aug 2013 06:53:05 -0500</pubDate>
	<link>https://bioinformaticsonline.com/videolist/watch/4043/what-is-bioinformatics</link>
	<title><![CDATA[What is Bioinformatics?]]></title>
	<description><![CDATA[<iframe src="http://player.vimeo.com/video/71581534?byline=0" width="" height="" frameborder="0" webkitAllowFullScreen allowFullScreen></iframe>Illustration and Animation: Rachel Robinson Script: Tiffany Trent Voice-over: Kris Monger Sound: Glisten Carefully by Guennadi Malyshevski]]></description>
	
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