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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/27090?offset=1590</link>
	<atom:link href="https://bioinformaticsonline.com/related/27090?offset=1590" rel="self" type="application/rss+xml" />
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/16313/project-assistant-position-at-jmi</guid>
  <pubDate>Fri, 12 Sep 2014 00:37:44 -0500</pubDate>
  <link></link>
  <title><![CDATA[Project Assistant Position at JMI]]></title>
  <description><![CDATA[
<p>Project Assistant Position (@ Rs.10,000/pm Fixed) is available for one year ina research project funded by the Department of Science and Technology entitled, "Folding and stability of naturally truncated photosynthetic pigment,C- phycoerythrin from cyanobacterium Phormidium tenue", at Centre forInterdisciplinary Research in Basic Sciences, lamia Millia Islamia, New Delhi-110025 under' the supervision of Dr. Md. Imtaiyaz Hassan (PrincipalInvestigator).</p>

<p>Eligibility:<br />M.Sc. in any stream of Life Sciences with minimum 55% marks.</p>

<p>Desirable:<br />Candidates having experience in Molecular Spectroscopy, Protein Folding and Bioinformatics will be preferred.</p>

<p>Interested candidate may appear in the walk in Interview conducted on September 16, 2014 (Tuesday) 11:00 AM in the Director's Office, Centre for Interdisciplinary Research in Basic Sciences, lamia Millia Islamia, New Delhi-110025.<br />Candidates are required to bring a set of Xerox copy of their recent CV and qualifying degree (certificate/mark sheet) along with original documents. NoTA/DA will be paid.</p>

<p>For any further information you may e-mail to: mihassan@jmLac.in</p>

<p>Read more at http://jmi.ac.in/upload/advertisement/jobs_cirbs_2014september8.pdf</p>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/44770/nvidia-and-arc-institute-unveil-evo-2-a-breakthrough-ai-for-dna-design</guid>
	<pubDate>Fri, 21 Feb 2025 10:39:47 -0600</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/44770/nvidia-and-arc-institute-unveil-evo-2-a-breakthrough-ai-for-dna-design</link>
	<title><![CDATA[NVIDIA and Arc Institute Unveil Evo 2: A Breakthrough AI for DNA Design]]></title>
	<description><![CDATA[<p>NVIDIA and the Arc Institute have introduced <strong style="font-size: 12.8px;">Evo 2</strong>, a groundbreaking AI model designed to <strong style="font-size: 12.8px;">understand, predict, and generate DNA sequences</strong>. This marks a major advancement in computational biology, offering scientists an unprecedented tool to decode the genetic blueprint of life and even design entirely new biological systems.</p><h3><strong>The Power of Evo 2: AI Meets DNA</strong></h3><p>Evo 2 is <strong>the largest AI model for biology ever created</strong>, trained on an astonishing <strong>9.3 trillion DNA "letters"</strong> (nucleotides) carefully selected from genomes spanning the entire tree of life. This massive dataset ensures that Evo 2 can recognize patterns and relationships in genetic sequences at an unparalleled scale.</p><p>For the first time, scientists can <strong>design DNA with AI</strong>, moving beyond simple sequence analysis to active DNA generation. Evo 2 enables researchers to <strong>predict, modify, and even create entire genetic sequences</strong>, opening new possibilities in medicine, agriculture, and synthetic biology.</p><h3><strong>Decoding the Dark Genome</strong></h3><p>One of the biggest challenges in genetics is understanding the <strong>non-coding regions</strong> of DNA&mdash;vast stretches of the genome that do not code for proteins but play crucial roles in regulating gene expression. These regions control when and how genes are activated, influencing everything from development to disease.</p><p>Evo 2 is designed to <strong>decode these non-coding elements</strong>, helping researchers uncover their functions and use this knowledge to develop gene-based therapies, synthetic life forms, and precision agriculture solutions.</p><h3><strong>From Reading DNA to Writing It</strong></h3><p>To put Evo 2&rsquo;s impact into perspective:</p><ul>
<li><strong>Previous AI models could "read" DNA</strong> like a book, analyzing genetic sequences and identifying patterns.</li>
<li><strong>Evo 2 can "write" entirely new DNA</strong>, designing functional genes, chromosomes, and even full genomes from scratch.</li>
</ul><p>This means scientists can now <strong>engineer biological systems with AI</strong>, designing new proteins, metabolic pathways, and genetic circuits to address real-world challenges.</p><h3><strong>A Step Toward Generative Biology</strong></h3><p>The Arc Institute describes Evo 2 as a major step toward <strong>"generative biology"</strong>&mdash;a revolutionary approach where AI is used to create <strong>novel biological structures</strong> rather than just analyzing existing ones. This could lead to breakthroughs such as:</p><ul>
<li><strong>New medicines</strong>: AI-generated enzymes and proteins tailored for targeted therapies.</li>
<li><strong>Disease-resistant crops</strong>: Genetically optimized plants for higher yield and climate resilience.</li>
<li><strong>Synthetic organisms</strong>: Custom-designed microbes for bioremediation, biofuel production, and industrial applications.</li>
</ul><h3><strong>An Open-Source Revolution</strong></h3><p>Unlike many proprietary AI models, <strong>Evo 2 is open source</strong>, making its capabilities accessible to researchers worldwide. This democratization of AI-driven biology means that scientists from different disciplines can <strong>collaborate, experiment, and innovate</strong>, accelerating discoveries in genetic engineering and synthetic biology.</p><p>With Evo 2, the boundaries of what&rsquo;s possible in <strong>DNA design, genetic engineering, and biological innovation</strong> are being redrawn. The future of life sciences is no longer just about understanding life&rsquo;s code&mdash;it&rsquo;s about writing it.</p>]]></description>
	<dc:creator>BioStar</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/17188/jamia-hamdard-bioinformatics-faculty-jobs-2014</guid>
  <pubDate>Sat, 20 Sep 2014 21:00:05 -0500</pubDate>
  <link></link>
  <title><![CDATA[JAMIA HAMDARD Bioinformatics Faculty Jobs 2014]]></title>
  <description><![CDATA[
<p>JAMIA HAMDARD</p>

<p>(Deemed University)</p>

<p>Hamdard Nagar, New Delhi – 110 062</p>

<p>R E C R U I T M E N T</p>

<p>(Advertisement No. 5/2014)</p>

<p>Applications on prescribed form are invited for filling up the following teaching positions in the Department of Biotechnology, Faculty of Science in the university. Eligible candidates may apply on or before 30.09.2014.</p>

<p>1. Professor/Associate Professor - One in Pay Band of Rs. 37400-67000+ AGP Rs.10000/9000</p>

<p>2. Assistant Professor                   -  Two in Pay Band of Rs. 15600-39100+ AGP Rs. 6000/-</p>

<p>ASSISTANT PROFESSOR – 02 (including 01 SFS)</p>

<p>Specialization : Bioinformatics</p>

<p>Qualification and Experience :</p>

<p>Ph.D. in Biotechnology or an allied discipline with M.Sc. in Biotechnology/ Biochemistry in the First division or equivalent grade from a recognized University/ Institute.</p>

<p>NET in Life Science or allied discipline in addition to the above qualification.</p>

<p>Experience : At  least two years of Post-doctoral teaching and/or research experience in Bioinformatics or relevant field in a UGC recognized Institution of repute or international research institute/ University.  Proof of research to be evidenced by publications in SCI-indexed journals of high impact factor as the first or corresponding author.</p>

<p>Note : University may consider exempting candidates from NET, who has been awarded Ph.D. degree from ‘A’ Grade accredited University following the procedure as notified by the UGC in its Regulations of 2009 and adopted by Jamia Hamdard.</p>

<p>For more information: http://www.jamiahamdard.ac.in/PDF/Online%20application%20form%20_Teaching_1.pdf<br />http://www.jamiahamdard.ac.in/PDF/PBAS.pdf</p>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/videolist/watch/3918/the-human-genome-project-video-3d-animation-introduction-low</guid>
	<pubDate>Sat, 24 Aug 2013 19:01:19 -0500</pubDate>
	<link>https://bioinformaticsonline.com/videolist/watch/3918/the-human-genome-project-video-3d-animation-introduction-low</link>
	<title><![CDATA[The Human Genome Project Video   3D Animation Introduction Low)]]></title>
	<description><![CDATA[<iframe width="" height="" src="https://www.youtube-nocookie.com/embed/YxoQFSBwyms" frameborder="0" allowfullscreen></iframe>]]></description>
	
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/17500/joao-pedro-de-magalhaes-lab</guid>
  <pubDate>Fri, 26 Sep 2014 19:08:34 -0500</pubDate>
  <link></link>
  <title><![CDATA[Joao Pedro de Magalhaes Lab]]></title>
  <description><![CDATA[
<p>Ageing has a profound impact on human society and modern medicine, yet it remains a major puzzle of biology. The goal of my work is to help understand the genetic, cellular, and molecular mechanisms of ageing. In the long term, I would like my work to help ameliorate age-related diseases and preserve health. No other biomedical field has so much potential to improve human health as research on the basic mechanisms of ageing. Please see our lab website for further details about our work and publications. </p>

<p>Functional and Comparative Genomics</p>

<p>http://jp.senescence.info/<br />http://www.senescence.info/<br />http://www.liv.ac.uk/integrative-biology/staff/joao-de-magalhaes/</p>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/21150/webinar-on-an-integrated-rna-and-dna-approach-to-unravel-genetic-regulation-in-cancer</guid>
	<pubDate>Wed, 11 Feb 2015 04:59:57 -0600</pubDate>
	<link>https://bioinformaticsonline.com/news/view/21150/webinar-on-an-integrated-rna-and-dna-approach-to-unravel-genetic-regulation-in-cancer</link>
	<title><![CDATA[Webinar on 'An integrated RNA and DNA approach to unravel genetic regulation in cancer']]></title>
	<description><![CDATA[<div><p><strong>Webinar on 'An integrated RNA and DNA approach to unravel genetic regulation in cancer'</strong></p><p><strong>Abstract</strong></p><p>Whole exome DNA sequencing (WES) or whole genome DNA sequencing (WGS) allows detection of mutations and polymorphisms in all exonic and genomic regions, respectively, while messenger RNA sequencing (RNA-Seq) enables quantitative analysis of gene expression. Mutations in the genome result in diverse transcriptional aberrations that can be missed in a stand-alone WES/WGS analysis. An integration of DNA variant analysis and RNA-Seq analysis enables one to investigate the consequences of genomic changes in the RNA transcripts including germline and somatic changes, imprinting, RNA editing and allele specific expression (ASE). In this webinar, we will demonstrate this integrated approach using Strand NGS to identify high confidence mutations, RNA editing events and ASE in cancer.</p><p><strong>Webinar Details</strong></p><table width="100%" border="1" cellspacing="0" cellpadding="0">
<tbody>
<tr>
<td valign="top">
<p style="text-align: center;"><br /> <strong>Sessions</strong></p>
</td>
<td valign="top">
<p style="text-align: center;"><a href="http://www.strand-ngs.com/webinar_registration"><strong>San Francisco Time<br /> (PST)</strong></a></p>
</td>
<td valign="top">
<p style="text-align: center;"><a href="http://www.strand-ngs.com/webinar_registration"><strong>Tokyo Time<br /> (GMT+09:00)</strong></a></p>
</td>
<td valign="top">
<p style="text-align: center;"><a href="http://www.strand-ngs.com/webinar_registration"><strong>Berlin Time<br /> (GMT+01:00)</strong></a></p>
</td>
<td valign="top">
<p style="text-align: center;"><a href="http://www.strand-ngs.com/webinar_registration"><strong>Mumbai Time<br /> (GMT+05:30)</strong></a></p>
</td>
</tr>
<tr>
<td>
<p style="text-align: center;"><a href="http://www.strand-ngs.com/webinar_registration"><strong>Session 1</strong></a></p>
</td>
<td valign="top">
<p style="text-align: center;">25 Feb&nbsp;<br /> 12:30 AM</p>
</td>
<td>
<p style="text-align: center;">25 Feb&nbsp;<br /> 5:30 PM</p>
</td>
<td>
<p style="text-align: center;">25 Feb&nbsp;<br /> 9:30 AM</p>
</td>
<td>
<p style="text-align: center;">25 Feb&nbsp;<br /> 2:00 PM</p>
</td>
</tr>
<tr>
<td valign="top">
<p style="text-align: center;"><a href="http://www.strand-ngs.com/webinar_registration"><strong>Session 2</strong></a></p>
</td>
<td valign="top">
<p style="text-align: center;">25 Feb&nbsp;<br /> 9:00 AM</p>
</td>
<td>
<p style="text-align: center;">26 Feb<br /> 2:00 AM</p>
</td>
<td>
<p style="text-align: center;">25 Feb&nbsp;<br /> 6:00 PM</p>
</td>
<td>
<p style="text-align: center;">25 Feb&nbsp;<br /> 10:30 PM</p>
</td>
</tr>
</tbody>
</table><p><strong style="font-size: 12.8000001907349px;">Register here: </strong><a href="http://www.strand-ngs.com/webinar_registration">http://www.strand-ngs.com/webinar_registration</a></p><p><strong>About Speaker:</strong></p><p>Dr. Veena Hedatale, has a PhD in Plant Genetics from The Radboud University, Netherlands focused on meiosis and recombination. Her prior academic experience at Cornell University was on genetic mapping and gene transformation in Rice. She has worked with Monsanto, and contributed to data mining, database development as well as gene/promoter/pathway discovery for traits related to yield and stress in crop species. At Strand, Veena has worked on Pharmacogenomic analysis of targets and Gene family analysis projects. Currently, she is part of the Strand NGS Application Science team and is involved in the analysis of next generation sequencing data.</p><p>Please feel free to contact us 24/5, for availing free online training or if you have any questions.</p></div><div><p><strong style="font-size: 12.8000001907349px;">Email:</strong> sales@strandngs.com</p><p><strong>Phone (USA):</strong> 1-800-752-9122</p><p><strong>Phone (ROW):</strong> +1-650-353-5060</p><p>&nbsp;</p></div>]]></description>
	<dc:creator>Yeshodari</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/23628/postgraduate-research-associate-bioinformatics-computational-biology-reference-code-59</guid>
  <pubDate>Tue, 04 Aug 2015 20:32:39 -0500</pubDate>
  <link></link>
  <title><![CDATA[Postgraduate Research Associate Bioinformatics / Computational Biology (Reference code: 59)]]></title>
  <description><![CDATA[
<p>The Department of Biotechnology, group “Genome Bioinformatics” is currently seeking a Postgraduate Research Associate Bioinformatics / Computational Biology (Reference code: 59)</p>

<p>Extent of employment: 30 Hours per Week<br />Duration of employment: 1st of October 2015 to 30th of September 2019<br />Gross monthly salary and pay grade in terms of collective agreement for university staff (payable 14 times per year): B1, € 1.997,20</p>

<p>Responsibilities<br />The successful candidate (f/m) will pursue a Ph.D. project related to the interpretation of plant genome and transcriptome sequencing data from next-generation sequencing (NGS) platforms. In particular, the candidate will characterize the unexplored genome of quinoa, a crop plant of long-standing tradition in Latin America. We collaborate with research partners in Austria and abroad, and the candidate’s project will be of central importance in the context of this research network.</p>

<p>Required skills and qualifications<br />We are looking for a graduate student (f/m) with a Master’s degree in bioinformatics or in a related field, solid programming skills (e.g. developing sequence analysis tools), experience with the analysis of NGS data sets, understanding of lab methods and knowledge of genomics/transcriptomics. The group has successfully performed several projects using NGS technology. We have recently published the reference genome sequence of sugar beet (Dohm et al., Nature, 2014), a crop plant closely related to quinoa (same family, but different genus). Not yet published is a quinoa genome assembly that we have generated, and which will serve as the starting point of the candidate’s project. We are a multidisciplinary team and offer work in a lively and friendly atmosphere, and state-of-the-art computing infrastructure. We are looking forward to expanding our team by a dedicated and strongly motivated person with a distinct interest in the challenges of plant genomics.</p>

<p>Applications can be submitted until: 16th of August 2015</p>

<p>University of Natural Resources and Life Sciences Vienna seeks to increase the number of its female faculty and staff members. Therefore qualified women are strongly encouraged to apply. In case of equal qualification, female candidates will be given preference unless reasons specific to an individual male candidate tilt the balance in his favour.</p>

<p>Please send your job application (incl. letter of motivation, CV, summary of Master’s thesis and contact details for two referees) to Personnel department, University of Natural Resources and Life Sciences, 1190 Vienna, Peter-Jordan-Straße 70; E-Mail: kerstin.buchmueller@boku.ac.at. (Reference code: 59)</p>

<p>We regret that we cannot reimburse applicants travel and lodging expenses incurred as part of the selection and hiring process.</p>

<p>www.boku.ac.at</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/29407/live-webinar-on-rna-seq-data-analysis-on-9-nov-2016</guid>
	<pubDate>Wed, 19 Oct 2016 05:25:27 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/29407/live-webinar-on-rna-seq-data-analysis-on-9-nov-2016</link>
	<title><![CDATA[Live Webinar on RNA-Seq Data Analysis on 9 Nov 2016]]></title>
	<description><![CDATA[<p><strong><a href="http://www.strand-ngs.com/webinar_registration">Live Webinar on RNA-Seq Data Analysis</a></strong></p><p><a href="http://www.strand-ngs.com/webinar_registration">Abstract: </a>Strand NGS supports an extensive workflow for the analysis and visualization of RNA-Seq data. The workflow includes Transcriptome / Genome alignment, Differential expression analysis with Statistical approach and Splicing events detection. Strand NGS also supports novel discovery like identification of novel genes, exons and Novel splice junctions, alongside it can also detect gene fusion events. Further downstream analysis such as GO and pathway analysis can be performed on the set of interesting genes. The product has an option to create pipelines for time consuming jobs which automates analysis and leaves more time for end data interpretation. This webinar will give an overview of the features in the RNA-Seq data analysis workflow in Strand NGS and also highlights on parameters within each feature that can be optimized depending on datasets and analysis needs.</p><p><a href="http://www.strand-ngs.com/webinar_registration">Speaker:</a> Mr. Sugandan Sivamani, Senior Application Scientist, Strand Life Sciences</p><p>Date: 9th Nov, <a href="http://www.strand-ngs.com/webinar_registration">Session 1</a> for SAPK/ APFO: 2:30 PM IST Date: 9th Nov, <a href="http://www.strand-ngs.com/webinar_registration">Session 2</a> for AFO/ EMEA: 9:00 AM PST</p><p>Register here <a href="http://www.strand-ngs.com/webinar_registration">http://www.strand-ngs.com/webinar_registration</a></p>]]></description>
	<dc:creator>Strand</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/17898/ensembl-77-has-been-released</guid>
	<pubDate>Sun, 05 Oct 2014 16:38:58 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/17898/ensembl-77-has-been-released</link>
	<title><![CDATA[Ensembl 77 has been released!]]></title>
	<description><![CDATA[<h3>New updates in e!77 !!</h3><ul>
<li>Updated&nbsp;<a href="http://e77.ensembl.org/Homo_sapiens/Info/Index" title="Human species page">human</a>&nbsp;gene set (GENCODE 21)</li>
<li>Updated <a href="http://e77.ensembl.org/Rattus_norvegicus/Info/Index">rat</a> gene set&nbsp;including manual annotation from HAVANA</li>
<li>New species:&nbsp;<a href="http://e77.ensembl.org/Chlorocebus_sabaeus/Info/Index">Vervet-African green monkey</a></li>
<li>Imported Transcript Support Levels (TSLs) from UCSC&nbsp;for&nbsp;<a href="http://e77.ensembl.org/Homo_sapiens/Info/Index">human</a>&nbsp;and&nbsp;<a href="http://e77.ensembl.org/Mus_musculus/Info/Index">mouse</a></li>
<li>Imported <a href="http://appris.bioinfo.cnio.es/" target="_blank" title="APPRIS">APPRIS</a> flag for&nbsp;<a href="http://e77.ensembl.org/Homo_sapiens/Info/Index">human</a> and <a href="http://e77.ensembl.org/Mus_musculus/Info/Index">mouse</a></li>
<li>Updated <a href="http://e77.ensembl.org/Poecilia_formosa/Info/Index" title="Amazon molly">Amazon molly</a> gene set</li>
</ul><p>Find more at http://www.ensembl.info/blog/2014/10/02/ensembl-77-has-been-released/</p>]]></description>
	<dc:creator>Seema Singh</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/33486/quick-next-generation-sequencing-ngs-terms-definition</guid>
	<pubDate>Fri, 09 Jun 2017 04:52:26 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/33486/quick-next-generation-sequencing-ngs-terms-definition</link>
	<title><![CDATA[Quick next generation sequencing (NGS) terms definition]]></title>
	<description><![CDATA[<p><strong>fragment size:</strong><span>&nbsp;the Illumina WGS protocol generates paired-end reads from both ends of longer fragments. The lengths of these fragments are assumed to be sampled from a normal distribution. Therefore, in the absence of structural variants, mapping locations of the paired ends span within an interval [&delta;min,&delta;max]. Most (&gt;90%) of paired-end reads are sampled from no-SV regions, therefore the fragment size distribution can be learned empirically for each WGS data set separately.</span><br /><br /><strong>concordant reads:</strong><span>&nbsp;a read pair is called concordant if they can be mapped to the reference genome as &ldquo;expected&rdquo;: (a) mapped to opposing strands where the upstream read is mapped to the forward strand and the downstream read is mapped to the reverse strand2, (b) the distance between ends is between the minimum and maximum expected fragment size.</span><br /><br /><strong>discordant reads:</strong><span>&nbsp;briefly, any non-concordant read pair is considered discordant. Note that, by definition, the discordant read pairs signal potential SVs. The sequence signature produced by these type of reads is known as read-pair signature.</span><br /><br /><strong>split reads:</strong><span>&nbsp;a read that can only be mapped to the reference genome by breaking into two sub-reads is called a split-read. These types of reads also indicate a potential SV or a short insertion or deletion (indel).</span><br /><br /><strong>read depth:</strong><span>&nbsp;number of reads that map within a region of the genome. Overall genome-wide read depth is also referred to as depth of coverage. It is expected that the number of reads that &ldquo;cover&rdquo; each base-pair to follow a Poisson distribution. Therefore, if the read depth over a certain region deviates significantly from this distribution, it signals for a potential copy number variation (CNV).</span></p>]]></description>
	<dc:creator>Neel</dc:creator>
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