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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/6052?offset=170</link>
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<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/4004/33rd-annual-convention-of-indian-association-for-cancer-research-from-13th-to-15th-february-2014</guid>
  <pubDate>Tue, 27 Aug 2013 10:37:08 -0500</pubDate>
  <link></link>
  <title><![CDATA[33rd Annual Convention of Indian Association for Cancer Research from 13th to 15th February 2014]]></title>
  <description><![CDATA[
<p>RGCB is organizing the 33rd Annual Convention of Indian Association for Cancer Research from 13th to 15th February 2014 with the theme "Discovery, Innovation and Translation in Cancer Research"</p>

<p>Kindly log on to conference website http://rgcb.res.in/IACR2014 for further details and timely updates and registration. We shall truly appreciate if the same be circulated among your friends, scholars and students encouraging them to participate in the meet.</p>

<p>http://210.212.237.38/iacrconference/</p>
]]></description>
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<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/2645/dna-bending-propensity-in-the-presence-of-base-mismatches-implications-for-dna-repair</guid>
	<pubDate>Mon, 19 Aug 2013 16:01:44 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/2645/dna-bending-propensity-in-the-presence-of-base-mismatches-implications-for-dna-repair</link>
	<title><![CDATA[DNA Bending Propensity in the Presence of Base Mismatches: Implications for DNA Repair]]></title>
	<description><![CDATA[<p>Understanding how the human body recognizes damaged DNA and initiates repair fascinates Michael Feig, professor of biochemistry and molecular biology at Michigan State University. Feig studies the proteins MutS and MSH2-MSH6, which recognize defective DNA and initiate DNA repair. Natural DNA repair occurs when proteins like MutS (the primary protein responsible for recognizing a variety of DNA mismatches) scan the DNA, identify a defect, and recruit other enzymes to carry out the actual repair.</p><p><em>Results from computer simulations show that it is energetically less expensive to bend mismatch-containing, defective DNA (G:T, C:C, C:T, G:A, G:G, T:T, A:A, A+:C) vs. non-defective DNA (containing A:T or G:C base pairs). DNA repair mechanisms likely take advantage of this feature to detect defective DNA based on an increased bending propensity.</em></p><p>http://www.tacc.utexas.edu/news/feature-stories/2013/how-dna-repair-helps-prevent-cancer</p><p>http://pubs.acs.org/doi/abs/10.1021/jp403127a</p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/videolist/watch/4633/cancer-growth-animation</guid>
	<pubDate>Fri, 20 Sep 2013 06:16:51 -0500</pubDate>
	<link>https://bioinformaticsonline.com/videolist/watch/4633/cancer-growth-animation</link>
	<title><![CDATA[Cancer Growth Animation]]></title>
	<description><![CDATA[<iframe width="" height="" src="https://www.youtube-nocookie.com/embed/WXTsxPPcTEs" frameborder="0" allowfullscreen></iframe>This video demonstrates how cancer growth happens in human body.]]></description>
	
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/5946/bioinformatics-tata-memorial-centre-navi-mumbai</guid>
  <pubDate>Mon, 28 Oct 2013 10:40:25 -0500</pubDate>
  <link></link>
  <title><![CDATA[Bioinformatics @ TATA MEMORIAL CENTRE, NAVI MUMBAI]]></title>
  <description><![CDATA[
<p>TATA MEMORIAL CENTRE<br />ADVANCED CENTRE FOR TREATMENT, RESEARCH AND EDUCATION IN CANCER<br />KHARGHAR, NAVI MUMBAI – 410210</p>

<p>No. ACTREC/Advt./ 72 /2013</p>

<p>WALK IN INTERVIEW</p>

<p>1. JRF*<br />Genome-wide RNAi screen with human pooled tyrosine kinase shRNA libraries in head and neck squamous call carcinoma (HNSCC) cell lines<br />DBT A/C No. 3071, Dr. Amit Dutt</p>

<p>2. JRF<br />IRB Project ACTREC Funds<br />Dr. Amit Dutt</p>

<p>3. RA<br />Defining the cancer genome of Head and Neck Squamous Cell Carcinoma (HNSCC) with SNP arrays and next generation sequencing technology<br />A/C No. 2895, Dr. Amit Dutt</p>

<p>Duration of the Project: One year from the date of appointment, or as and when project terminates.</p>

<p>Consolidated Salary: RA : Rs. 40,000/- p.m.<br />JRF* (DBT): Rs. 20,800/- p.m.<br />JRF: Rs. 16,000/- p.m.<br />Date &amp; Time: 6th November, 2013, at 10.00 a.m.</p>

<p>Venue: Conference Room</p>

<p>Minimum Qualifications and Experience:</p>

<p>RA: The ideal applicant should have a PhD in a relevant field. He/she should have a strong computational biology background, with demonstrated experience in coding using Perl, Python, Java or C++. He/she should be familiar with working in unix enviromnent, devising computational algorithms for data analysis, statistical data analysis in R and matlab and database programming using MySQL. Hands on experience in analyzing high throughput data would be an added advantage.</p>

<p>JRF* (DBT project): M.Sc. in Life Sciences or M.Tech in Biotechnology with good academic record (Minimum of 60% aggregate). Valid UGC-CSIR/DBT/ICMR JRF qualification and laboratory experience in molecular biology. Previous experience in molecular biology and animal tissue culture with high throughput platforms and ability to work with a large team would be desirable.</p>

<p>JRF (ACTREC project): M.Sc. in Life Sciences or M.Tech in Biotechnology with good academic record (Minimum of 60% aggregate). Minimum 2 yrs experience in molecular biology and animal tissue culture with high throughput platforms and ability to work with a large team is essential.</p>

<p>*M.Sc. degree obtained after a one year course will not be considered.</p>

<p>Candidates fulfilling above requirements should send their application by e-mail to<br />‘careers.duttlab@gmail.com. in the format given below so as to reach on or before<br />4th November, 2013.</p>

<p>Advertisement:</p>

<p>http://www.actrec.gov.in/data%20files/2013/AD-RA-JR-TECHN-6-NOV.pdf</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/26303/maker</guid>
	<pubDate>Sun, 07 Feb 2016 15:59:24 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/26303/maker</link>
	<title><![CDATA[MAKER]]></title>
	<description><![CDATA[<p>MAKER is a portable and easily configurable genome annotation pipeline.Its purpose is to allow smaller eukaryotic and prokaryotic genome projects to independently annotate their genomes and to create genome databases. MAKER identifies repeats, aligns ESTs and proteins to a genome, produces ab-initio gene predictions and automatically synthesizes these data into gene annotations having evidence-based quality values.</p>
<p>More at http://www.yandell-lab.org/software/maker.html</p><p>Address of the bookmark: <a href="http://www.yandell-lab.org/software/maker.html" rel="nofollow">http://www.yandell-lab.org/software/maker.html</a></p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/29282/cosmic</guid>
	<pubDate>Sat, 01 Oct 2016 15:04:10 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/29282/cosmic</link>
	<title><![CDATA[COSMIC]]></title>
	<description><![CDATA[<p>The accurate description and annotation of structural variants can be complex. &nbsp;This is due to the different resolution that variants are reported from traditional&nbsp;cytogenetic coordinates down to the actual base pair positions. Furthermore, multiple&nbsp;rearrangements in a single area of the genome can make cataloguing and interpreting&nbsp;their effects challenging.&nbsp;</p>
<p>The Rearrangement Overview page describes the one or more breakpoints which make up a structural&nbsp;variant. A breakpoint is defined as a region or point where the sample sequence has altered&nbsp;from the reference sequence. Minimum interpretation is made of this data. One variant event&nbsp;can consist of one or multiple breakpoints. The Syntax (shown above the table) gives a detailed description of the variant and its location &nbsp;(e.g. chr11:g.36585230_76606619del, a deletion of&nbsp;roughly 40Mb on chromosome 11). Syntax is based on HGVS mutation nomenclature recommendations&nbsp;[http://www.hgvs.org/rec.html].&nbsp;</p>
<p>http://cancer.sanger.ac.uk/cosmic/help/rearrangement/overview</p><p>Address of the bookmark: <a href="http://cancer.sanger.ac.uk/cosmic/help/rearrangement/overview" rel="nofollow">http://cancer.sanger.ac.uk/cosmic/help/rearrangement/overview</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/41040/phd-position-in-molecular-cell-biology</guid>
  <pubDate>Sat, 15 Feb 2020 06:09:55 -0600</pubDate>
  <link></link>
  <title><![CDATA[PhD position in Molecular Cell Biology]]></title>
  <description><![CDATA[
<p>https://www.jobvector.de/jobs-stellenangebote/biologie-life-sciences/wissenschaftliche-r-mitarbeiter-in/phd-position-molecular-cell-biology-129604.html?suid=0ec057818886c1eceac674ca3f83943367a6cbe2</p>

<p>Essential experience / qualifications:<br />We are looking for highly motivated candidates holding a Master / Diploma in Biology, Biochemistry, Molecular Medicine or similar; solid knowledge of molecular and cell biological techniques; good English knowledge.</p>

<p>Applications:<br />Please send your application (including CV, letter of motivation, contact information of two references, and list of publication) by 13.03.2020 at the latest to:</p>

<p>Universitätsklinikum Erlangen<br />Chirurgische Klinik<br />Translational Research Center<br />Prof. Dr. rer. nat. Michael Stürzl<br />Schwabachanlage 12<br />91054 Erlangen<br />E-Mail: michael.stuerzl@uk-erlangen.de</p>
]]></description>
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<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/40881/liu-lab</guid>
  <pubDate>Tue, 04 Feb 2020 06:27:02 -0600</pubDate>
  <link></link>
  <title><![CDATA[Liu Lab]]></title>
  <description><![CDATA[
<p>Shirley is a computational biologist with expertise in cancer epigenetics. Her research focuses on algorithm development and integrative mining from big data generated on microarrays, massively parallel sequencing, and other high throughput techniques to model the specificity and function of transcription factors, chromatin regulators and lncRNAs in tumor development, progression, drug response and resistance.</p>

<p>https://liulab-dfci.github.io/software/</p>
]]></description>
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<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>
	
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<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/videolist/watch/18381/how-far-can-bioinformatics-go-creating-organisms-used-for-testing</guid>
	<pubDate>Fri, 17 Oct 2014 02:08:16 -0500</pubDate>
	<link>https://bioinformaticsonline.com/videolist/watch/18381/how-far-can-bioinformatics-go-creating-organisms-used-for-testing</link>
	<title><![CDATA[How far can bioinformatics go creating organisms used for testing?]]></title>
	<description><![CDATA[<iframe width="" height="" src="https://www.youtube-nocookie.com/embed/FojhDef2NW4" frameborder="0" allowfullscreen></iframe>"I think you can get very far on a technical level. The problem is that a human body is more complex than just one cell." ... "At some point we still need clinical tests on animals and humans before we use it for real treatment. But we will likely be able to remove 99 % of animal tests in the future."

Erik Lindahl, Professor of Theoretical and Computational Biophysics at KTH Royal Institute of Technology is telling us about his work.

From the episode "Science for life – mapping the building blocks of the human body". Watch the rest of the talk, and other talks at www.crosstalks.tv

Crosstalks is an academic talkshow produced by KTH Royal Institute of Technology and Stockholm University.]]></description>
	
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