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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/2457?offset=280</link>
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<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/6458/bigre-lab</guid>
  <pubDate>Sun, 17 Nov 2013 10:35:49 -0600</pubDate>
  <link></link>
  <title><![CDATA[BIGRE Lab]]></title>
  <description><![CDATA[
<p>The Laboratoire de Bioinformatique des Génomes et des Réseaux (Genome and Network Bioinformatics) is specialized in the conception, implementation, evaluation and application of bioinformatics approaches for the analysis of genome, transcriptome, proteome and metabolism.<br />Our main activities include</p>

<p>Analysis of regulatory sequences (RSAT project)<br />Classification and analysis of mobile genetic elements (ACLAME project).<br />Analysis of molecular interaction networks (NeAT project)<br />Inference of metabolic pathways from genomic and post-genomic data <br />(metabolic pathfinding, see also metabolic pathfinding in NeAT)<br />Critical assesment of protein interactions (CAPRI)</p>

<p>Lab Page http://www.bigre.ulb.ac.be/</p>
]]></description>
</item>
<item>
	<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>
<item>
	<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/bookmarks/view/37636/department-of-genetics-genomics-and-bioinformatics-national-biotechnology-development-agency-nigeria</guid>
	<pubDate>Wed, 05 Sep 2018 10:48:25 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37636/department-of-genetics-genomics-and-bioinformatics-national-biotechnology-development-agency-nigeria</link>
	<title><![CDATA[DEPARTMENT OF GENETICS, GENOMICS AND BIOINFORMATICS, National Biotechnology Development Agency, Nigeria]]></title>
	<description><![CDATA[<p>The Genetics, Genomics &amp; Bioinformatics Department (GBBD) at NABDA is unique, encompassing all facets of modern genetics and bioinformatics research. Trans-disciplinary research being conducted in our laboratories would lead to cures for human diseases; improvements to crop and livestock quality and yield; creation of new technologies with applications to medicine; agriculture; environment; and industry.</p>
<p>Our capacity building activities covers both general and specialized topics in translational genetics, and is designed to better acquaint scientists and clinicians with the tools and technologies of genetics and genomics.</p>
<p><span>OUR RESEARCH ACTIVITIES INCLUDE:</span></p>
<div>
<ul>
<li>Biomedical Genetics: investigating genetic and environmental factors contributing to phenotypes with relevance to human health and disease.</li>
<li>Computation and Bioinformatics: develop new approaches for the management, analysis, and modelling of large, complex data sets.</li>
<li>Population and Quantitative Genetics: study of how genetic processes evolve to generate genetic variation in populations of organisms, and the effects on the patterning of variation within and between populations and specie, and</li>
<li>Genetic Engineering and Biotechnology: focuses on the research and innovation for industrial enzymes, biologics and biosimilars production.</li>
</ul>
<p>https://www.h3abionet.org/nabda</p>
</div><p>Address of the bookmark: <a href="http://www.nabda.gov.ng/departments/genetics-genomics-and-bioinformatics" rel="nofollow">http://www.nabda.gov.ng/departments/genetics-genomics-and-bioinformatics</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/2573/most-commonly-used-awk-by-bioinformatician</guid>
	<pubDate>Mon, 19 Aug 2013 01:12:38 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/2573/most-commonly-used-awk-by-bioinformatician</link>
	<title><![CDATA[Most Commonly used Awk by Bioinformatician]]></title>
	<description><![CDATA[<p style="text-align: center;">&nbsp;</p><p>Awk is a programming language that is specifically designed for quickly manipulating space delimited data. Although you can achieve all its functionality with Perl, awk is simpler in many practical cases.</p><p>Why awk? You can replace a pipeline of 'stuff | grep | sed | cut...' with a single call to awk. For a simple script, most of the timelag is in loading these apps into memory, and it's much faster to do it all with one. This is ideal for something like an openbox pipe menu where you want to generate something on the fly. You can use awk to make a neat one-liner for some quick job in the terminal, or build an awk section into a shell script. You can find a lot of online tutorials, but here I will only show a few examples which cover most of bioinformatician daily uses of awk.</p><p>choose rows where column 3 is larger than column 5:</p><p>awk '$3&gt;$5' input.txt &gt; output.txt</p><p>extract column 2,4,5:</p><p>awk '{print $2,$4,$5}' input.txt &gt; output.txt</p><p>awk 'BEGIN{OFS="\t"}{print $2,$4,$5}' input.txt</p><p>show rows between 20th and 80th:</p><p>awk 'NR&gt;=20&amp;&amp;NR&lt;=80' input.txt &gt; output.txt</p><p>calculate the average of column 2:</p><p>awk '{x+=$2}END{print x/NR}' input.txt</p><p>regex (egrep):</p><p>awk '/^test[0-9]+/' input.txt</p><p>calculate the sum of column 2 and 3 and put it at the end of a row or replace the first column:</p><p>awk '{print $0,$2+$3}' input.txt</p><p>awk '{$1=$2+$3;print}' input.txt</p><p>join two files on column 1:</p><p>awk 'BEGIN{while((getline&lt;"file1.txt")&gt;0)l[$1]=$0}$1 in l{print $0"\t"l[$1]}' file2.txt &gt; output.txt</p><p>count number of occurrence of column 2 (uniq -c):</p><p>awk '{l[$2]++}END{for (x in l) print x,l[x]}' input.txt</p><p>apply "uniq" on column 2, only printing the first occurrence (uniq):</p><p>awk '!($2 in l){print;l[$2]=1}' input.txt</p><p>count different words (wc):</p><p>awk '{for(i=1;i!=NF;++i)c[$i]++}END{for (x in c) print x,c[x]}' input.txt</p><p>deal with simple CSV:</p><p>awk -F, '{print $1,$2}'</p><p>substitution (sed is simpler in this case):</p><p>awk '{sub(/test/, "no", $0);print}' input.txt</p><p>&nbsp;</p><p>OK now here's where to read this stuff properly explained. roll</p><p>Two thorough tutorials:</p><p>http://www.gnu.org/software/gawk/manual/gawk.html</p><p>http://www.grymoire.com/Unix/Awk.html</p><p>A famous list of useful one-liners - though they're short, many are quite tricky:</p><p>http://www.pement.org/awk/awk1line.txt</p><p>And some nice explanations of those one-liners. After reading this you'll have a pretty good grasp!</p><p>http://www.catonmat.net/blog/awk-one-li &hellip; -part-one/</p><p>http://www.catonmat.net/blog/ten-awk-ti &hellip; -pitfalls/</p>]]></description>
	<dc:creator>Neel</dc:creator>
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<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/opportunity/view/4106/phd-at-national-institute-for-research-in-reproductive-health</guid>
  <pubDate>Fri, 30 Aug 2013 04:50:35 -0500</pubDate>
  <link></link>
  <title><![CDATA[PhD at National Institute for Research in Reproductive Health]]></title>
  <description><![CDATA[
<p>National Institute for Research in Reproductive Health</p>

<p>(Indian Council of Medical Research )<br />Jehangir Merwanji Street, Parel, Mumbai 400 012</p>

<p>Advertisement No. 1/NIRRH/Ph.D. 2013<br />Admission to Ph.D. Programme – 2013</p>

<p>National Institute for Research in Reproductive Health, Mumbai, a premier institute of the Indian Council of Medical Research, conducts basic, clinical and operational research in different areas of reproductive health. The thrust areas of research include: Fertility Regulation, Infertility and Reproductive Disorders, Reproductive Tract Infections, Maternal and Child Health, Osteoporosis, Genetic Disorders, Stem Cell Biology, Structural Biology, Bioinformatics and Reproductive Toxicology. Institute is affiliated to the University of Mumbai for the award of Ph.D. degree in Applied Biology, Biochemistry, Life Sciences and Biotechnology. The institute invites applications from young and bright students for enrollment in Ph.D. programme.</p>

<p>More at http://www.nirrh.res.in/announcements/phd_program_2013.htm</p>
]]></description>
</item>
<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>
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