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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/30550?offset=1250</link>
	<atom:link href="https://bioinformaticsonline.com/related/30550?offset=1250" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
	
<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/22297/appointment-of-two-traineeships-and-two-studentships-in-bioinformatics</guid>
  <pubDate>Fri, 08 May 2015 00:24:20 -0500</pubDate>
  <link></link>
  <title><![CDATA[Appointment of two traineeships and two studentships in Bioinformatics]]></title>
  <description><![CDATA[
<p>Applications are invited for the appointment of two traineeships and two studentships in Bioinformatics for a period of six months sponsored by Department of Biotechnology, Government of India in the Bioinformatics Sub-DIC, Saraswathy Thangavelu Centre, JNTBGRI, Puthenthope, Thiruvananthapuram 695 586. The required qualifications and other details are given below.</p>

<p>Position 1: Traineeship<br />Monthly fellowship (in rupee): 5,000/-<br />No. of vacancies: Two<br />Required Qualification: First Class M.Sc Bioinformatics/ Biotechnology/ Botany</p>

<p>Position 2: Studentship<br />Monthly fellowship (in rupee): 5,000/-<br />No. of vacancies: Two<br />Required Qualification: M.Phil/M.Tech Bioinformatics/ Biotechnology/ any branch of Life Science students for doing their thesis work in the area of Bioinformatics.</p>

<p>Age limit as on 1.1.2015, 28 years. Age relaxation will be provided for SC, ST, OBC candidates as per Govt. norms.</p>

<p>Interested candidates may appear for walk-in-interview on 15th May 2015 at 10.30 am at JNTBGRI, Palode, Thiruvananthapuram. The candidate should report to the Office at Palode before 10.00 am.</p>

<p>More at http://jntbgri.res.in/news/appointment-of-two-traineeships-and-two-studentships-in-bioinformatics/</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44628/uncovar-workflow-for-transparent-and-robust-virus-variant-calling-genome-reconstruction-and-lineage-assignment</guid>
	<pubDate>Mon, 05 Aug 2024 23:01:29 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44628/uncovar-workflow-for-transparent-and-robust-virus-variant-calling-genome-reconstruction-and-lineage-assignment</link>
	<title><![CDATA[UnCoVar: Workflow for Transparent and Robust Virus Variant Calling, Genome Reconstruction and Lineage Assignment]]></title>
	<description><![CDATA[<p>UnCoVar: Workflow for Transparent and Robust Virus Variant Calling, Genome Reconstruction and Lineage Assignment</p>
<ul>
<li>
<p>Using state of the art tools, easily extended for other viruses</p>
</li>
<li>
<p>Tool and database updates for critical components via Conda</p>
</li>
<li>
<p>Built using modern design patterns with Conda and Snakemake</p>
</li>
<li>
<p>Extensible and easy to customize</p>
</li>
<li>
<p>Submission Ready Genomes</p>
</li>
<li>
<p>Customizable reporting with comprehensive visualization</p>
</li>
</ul>
<p>https://ikim-essen.github.io/uncovar/</p>
<p>Github&nbsp;https://github.com/IKIM-Essen/uncovar</p>
<p>&nbsp;</p>
<p>&nbsp;</p><p>Address of the bookmark: <a href="https://ikim-essen.github.io/uncovar/" rel="nofollow">https://ikim-essen.github.io/uncovar/</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/22393/narcis-fernandez-fuentes-lab</guid>
  <pubDate>Mon, 25 May 2015 07:30:00 -0500</pubDate>
  <link></link>
  <title><![CDATA[Narcis Fernandez-Fuentes Lab]]></title>
  <description><![CDATA[
<p>Welcome to our web-site compiling all the research-related activities of the group. Our research interests relate to a number of areas within Bioinformatics. We have a long-standing interest in protein structure prediction and structure-to-function relationships. We work in the study of biomolecular interactions, modeling of protein complexes, the study and characterization of protein-protein interactions, peptide design, modeling of genetic variation, structure-based protein design and different aspects of Plant Bioinformatics. Take a look at the our databases and servers and the list of publications for more information.</p>

<p>More at http://www.bioinsilico.org/</p>
]]></description>
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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>
</item>

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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/22431/genomic-scientist-at-udsc</guid>
  <pubDate>Thu, 28 May 2015 19:14:23 -0500</pubDate>
  <link></link>
  <title><![CDATA[Genomic Scientist at UDSC]]></title>
  <description><![CDATA[
<p>Centre for Genetic Manipulation of Crop Plants</p>

<p>Department of Genetics</p>

<p>University of Delhi South Campus</p>

<p>NEW DELHI – 110 021</p>

<p>WALK-IN-INTERVIEW FOR THE TEMPORARY POSITIONS OF RESEACH SCIENTIT &amp; LAB / FIELD ATTENDANT</p>

<p>1 Research Scientist (RS) – 3</p>

<p>    DBT, Ph. D.</p>

<p>    Experience on DNA Markers, plant genome mapping and bioinformatics</p>

<p>    Salary: 60,000 (Consolidated) + 5% annual increment</p>

<p>    Date and time: 25.06.2015 at 10:30 AM</p>

<p>These temporary positions have been sanctioned in a DBT funded project for the Phase II on ‘Centre of Excellence on genome mapping and molecular breeding of Brassicas.’</p>

<p>The applicants are requested to register their names on the day of interview in the First Floor, Biotech Centre, Centre for Genetic Manipulation of Crop Plants, Department of Genetics before the stipulated time for the interview. Only the registered eligible candidates will be interviewed on the day in the Committee Room.</p>

<p>Applicants are requested to bring all related documents, in original and a set of photocopy, for verification.</p>

<p>No TA/DA will be paid for attending the interview.</p>

<p>Advertisement:</p>

<p>www.du.ac.in/du/index.php?mact=News,cntnt01,detail,0&amp;cntnt01articleid=5492&amp;cntnt01returnid=83</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/45251/aurora-a-new-detective-for-bacterial-genomes</guid>
	<pubDate>Fri, 21 Aug 2026 11:31:00 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/45251/aurora-a-new-detective-for-bacterial-genomes</link>
	<title><![CDATA[Aurora: A New Detective for Bacterial Genomes]]></title>
	<description><![CDATA[<p>Imagine trying to solve a mystery with thousands of clues&mdash;but some of the clues are labelled incorrectly.</p><p>That is the challenge researchers face when studying how bacteria adapt to different environments. A bacterial gene may appear to be linked to a particular habitat, when the real reason is simply that closely related bacteria happen to live there.</p><p>In their 2025 Genome Biology paper, Bujdo&scaron;, Walter, and O&rsquo;Toole introduce aurora, a machine-learning tool designed to tackle this problem.</p><p>Aurora identifies potentially mislabeled or unusual bacterial strains before performing genome-wide association studies (GWAS). By cleaning up the dataset and accounting for bacterial evolutionary relationships, it can help researchers find genetic features that are more genuinely connected to habitat adaptation.</p><p>The researchers tested aurora using simulated and real bacterial datasets and found that it could recover important genetic associations even when datasets contained misleading labels.</p><p>The bigger lesson is simple: better biological discoveries often begin with better data.</p><p>Aurora gives researchers a new way to separate real genetic clues from misleading ones&mdash;and could help us better understand how bacteria adapt, survive, and evolve in the environments they call home.</p><p>Based on Bujdo&scaron; et al., &ldquo;aurora: a machine learning GWAS tool for analyzing microbial habitat adaptation,&rdquo; Genome Biology (2025).[Read the original paper](https://link.springer.com/article/10.1186/s13059-025-03524-7?)</p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/22432/walk-ins-for-jrf-ans-srf-post-in-assam-agricultural-university</guid>
  <pubDate>Thu, 28 May 2015 19:16:47 -0500</pubDate>
  <link></link>
  <title><![CDATA[Walk-ins for JRF ans SRF post in Assam Agricultural University]]></title>
  <description><![CDATA[
<p>Distributed Information Centre<br />Department of Agricultural Biotechnology<br />Assam Agricultural University<br />Jorhat – 785 013<br />Walk-in interview</p>

<p>(ABT/DIC/01/2014 (No. AAU/ABT/DIT/Advt. 01/2015/111 Dtd. 19-05-2015)</p>

<p>Walk in interview for the following position will be held on 6th June, 2015 at 10.00AM in the Office Chamber of the undersigned. Candidates may appear for the interview with bio-data, reprints / publication / thesis etc and passport size photographs, original and attested copies of all testimonials etc, which must be presented at the time of interview. The applicants may submit their resume in advance tomkmodi@aau.ac.in.</p>

<p>Research Associate</p>

<p>    Ph.D. in Biotechnology/ Bioinformatics. Or</p>

<p>    Masters degree in Biotechnology/Bioinformatics with minimum 3(three) years research experience</p>

<p>    Desirable : Experience in Bioinformatics as evidenced from published research</p>

<p>    Rs 36,000+HRA for the 1st two years and 38,000+HRA for the 3rd year.</p>

<p>Senior Research Fellow</p>

<p>    Master Degree in Biotechnology/ Bioinformatics. With 2 (two) years  Experience in Bioinformatics as evidenced from Course work/ Diploma/Published research</p>

<p>    Rs 28,000+HRA for NET qualified candidate/Professional degree holder</p>

<p>    Rs 18,000+HRA for non-NET qualified general degree holder</p>

<p>Junior Research Fellow</p>

<p>    Master Degree in Biotechnology/ Bioinformatics/Computer Science/Computer Application</p>

<p>    Desirable: Experience in Bioinformatics as evident from Course work/ Diploma/Published research</p>

<p>    Rs 25,000+HRA for NET qualified candidate/Professional degree holder</p>

<p>    Rs 16,000+HRA for non-NET qualified general degree holder</p>

<p>Note: Term and conditions will be as per the DBT, Govt of India guidelines.</p>

<p>Advertisement: http://14.139.222.145/classified/biotech46.html</p>
]]></description>
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<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/45296/luo-lab-symbiosis-genomics-evolution</guid>
  <pubDate>Wed, 09 Sep 2026 03:30:30 -0500</pubDate>
  <link></link>
  <title><![CDATA[Luo Lab | Symbiosis Genomics &amp; Evolution]]></title>
  <description><![CDATA[
<p>We study the evolutionary genomics of marine invertebrates to understand their origins and diversity. Our lab combines high-throughput sequencing and single-cell transcriptomics to explore a wide range of non-model systems. We are particularly interested in how evolutionary novelty arises, with a focus on animal development and photosymbiosis.</p>

<p>Research Directions</p>

<p>Stony corals: evolution of novelty and photosymbiosis</p>

<p>Symbiotic acoels: cell type evolution and photosymbiosis</p>

<p>Animal genomes: structural evolution and gene regulation</p>

<p>https://sgel.biodiv.tw/home</p>
]]></description>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/22512/srf-post-in-nehu-shillong</guid>
  <pubDate>Wed, 03 Jun 2015 13:15:38 -0500</pubDate>
  <link></link>
  <title><![CDATA[SRF post in NEHU, Shillong]]></title>
  <description><![CDATA[
<p>Dept of Biochemistry <br />North-Eastern Hill University<br />(A University with Potential for Excellence) <br />Umshing, Shillong- 793 022</p>

<p>Applications are invited for the post of Senior Research Fellow- SRF (1) and Junior Research Fellow- JRF (1) to be appointed in a SERB-funded major research project entitled “Biochemical and functional properties of Synechocystis Glutathione S-transferase(s)” sanctioned to Dr. Timir Tripathi, Molecular and Structural Biophysics Laboratory, Department of Biochemistry, NEHU, Shillong. </p>

<p>Essential Qualifications: For both positions M.Sc. or equivalent with a good academic record is a prerequisite. </p>

<p>For Project-SRF, experience in bioinformatics/computational biology is required, which should be evident by atleast one good publication. </p>

<p>For JRF position, freshers can also apply. </p>

<p>Stipend: As per SERB norms. </p>

<p>Interested students can email their detailed bio-data including mobile number and recent photograph to msb.biochem@gmail.com, latest by 20.06.15. The hard copy is not required. The date of interview will be informed after primary scrutiny of the applications. No TA/DA will be paid if called for interview. For details of the research work of the PI’s group kindly visit www.ttripathi.webs.com</p>

<p>Advertisement: http://www.nehu.ac.in/Advertisements/BiochemSERB_Advt_020615.pdf</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36109/sankeynetwork-with-networkd3</guid>
	<pubDate>Fri, 06 Apr 2018 12:07:55 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36109/sankeynetwork-with-networkd3</link>
	<title><![CDATA[sankeyNetwork with networkD3]]></title>
	<description><![CDATA[<p><span>You can also create&nbsp;</span><a href="http://en.wikipedia.org/wiki/Sankey_diagram">Sankey diagrams</a><span>&nbsp;with&nbsp;</span><code>sankeyNetwork</code><span>. Here is an example using downloaded JSON data:</span></p>
<p><span>https://en.wikipedia.org/wiki/Sankey_diagram</span></p><p>Address of the bookmark: <a href="https://christophergandrud.github.io/networkD3/#sankey" rel="nofollow">https://christophergandrud.github.io/networkD3/#sankey</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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