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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/42985?offset=230</link>
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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/bookmarks/view/3885/precision-medicine</guid>
	<pubDate>Sat, 24 Aug 2013 15:47:03 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/3885/precision-medicine</link>
	<title><![CDATA[Precision Medicine]]></title>
	<description><![CDATA[<p>Coupling established clinical&ndash;pathological indexes with state-of-the-art molecular profiling to create diagnostic, prognostic, and therapeutic strategies precisely tailored to each patient's requirements &mdash; hence the term &ldquo;Precision medicine&rdquo;&nbsp;</p>
<p>Source:<a href="http://www.nejm.org/doi/full/10.1056/NEJMp1114866">http://www.nejm.org/doi/full/10.1056/NEJMp1114866</a></p>
<p><strong>Another video on precision medicine</strong>:</p>
<p><a href="http://www.youtube.com/watch?v=Pi8W0yOXnzE">http://www.youtube.com/watch?v=Pi8W0yOXnzE</a></p>
<p>Precision Medicine basically intergrates bioinformatics, genomics , genetics, molecular biology and nanotechnology to deliver precise cure/diagnotics to a specific patient.</p>
<p>Examples:</p>
<ul>
<li><span>The drug imatinib (Gleevec) designed to inhibit an altered enzyme produced by a fused version of two genes found in chronic myelogenous leukemia.</span></li>
<li><span>The breast cancer drug trastuzumab (Herceptin) works only for women whose tumors have a particular genetic profile called HER-2 positive.</span></li>
</ul>
<p><span>E.g. source :</span></p>
<p><span><a href="http://www.bionews-tx.com/news/2013/08/15/how-the-impact-of-cancer-genomics-on-precision-medicine-is-revolutionizing-cancer-treatment/">http://www.bionews-tx.com/news/2013/08/15/how-the-impact-of-cancer-genomics-on-precision-medicine-is-revolutionizing-cancer-treatment/</a></span></p><p>Address of the bookmark: <a href="http://www.cbsnews.com/video/watch/?id=50149783n" rel="nofollow">http://www.cbsnews.com/video/watch/?id=50149783n</a></p>]]></description>
	<dc:creator>Rahul Agarwal</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/3031/following-the-scientific-literature-a-personal-practical-guide-for-young-computational-biologists</guid>
	<pubDate>Fri, 23 Aug 2013 07:18:51 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/3031/following-the-scientific-literature-a-personal-practical-guide-for-young-computational-biologists</link>
	<title><![CDATA[Following the scientific literature: A personal practical guide for young computational biologists]]></title>
	<description><![CDATA[<p><span>The goal of this guide is to describe&nbsp;</span><strong>why</strong><span>,&nbsp;</span><strong>when</strong><span>,&nbsp;</span><strong>where</strong><span>&nbsp;and&nbsp;</span><strong>how</strong><span>&nbsp;can you follow the most up-to-date science of interest and&nbsp;</span><strong>what</strong><span>&nbsp;papers/journals you should follow. The guide is biased towards the fields of genomics/systems biology.(from article)</span></p>
<p><span>Source:&nbsp;<strong><span>&nbsp;<a href="http://www.cs.tau.ac.il/~ulitskyi/">Igor Ulitsky</a>&nbsp;&amp;&nbsp;<a href="http://www.cs.tau.ac.il/~rshamir/">Ron Shamir</a></span></strong></span></p><p>Address of the bookmark: <a href="http://acgt.cs.tau.ac.il/guides/LiteratureGuide.htm" rel="nofollow">http://acgt.cs.tau.ac.il/guides/LiteratureGuide.htm</a></p>]]></description>
	<dc:creator>Rahul Agarwal</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/5402/key-bioinformatics-scientists</guid>
	<pubDate>Wed, 09 Oct 2013 13:37:07 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/5402/key-bioinformatics-scientists</link>
	<title><![CDATA[Key Bioinformatics Scientists]]></title>
	<description><![CDATA[<p>Address of the bookmark: <a href="http://www.iscb.org/iscb-leadership-a-staff-/officers-and-board-directors" rel="nofollow">http://www.iscb.org/iscb-leadership-a-staff-/officers-and-board-directors</a></p>]]></description>
	<dc:creator>Rahul Agarwal</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/9586/list-of-bioinformatics-companies-and-genomics-service-providers</guid>
	<pubDate>Wed, 02 Apr 2014 06:52:28 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/9586/list-of-bioinformatics-companies-and-genomics-service-providers</link>
	<title><![CDATA[List of bioinformatics companies and genomics service providers]]></title>
	<description><![CDATA[<p>Plz check out link for bioinformatics and genomics companies.&nbsp;</p><p>Address of the bookmark: <a href="http://grouthbio.com/Genome_Software_Service.php" rel="nofollow">http://grouthbio.com/Genome_Software_Service.php</a></p>]]></description>
	<dc:creator>Rahul Agarwal</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/17966/internship-program-for-bioinformatics-biotechnology-professionals-no-of-vacancy-2</guid>
  <pubDate>Wed, 08 Oct 2014 01:10:08 -0500</pubDate>
  <link></link>
  <title><![CDATA[Internship Program for Bioinformatics / Biotechnology Professionals (No. Of Vacancy: 2)]]></title>
  <description><![CDATA[
<p>ArrayGen is offering an Internship Program for Post graduate Bioinformatics / Biotechnology students and professionals. ArrayGen Technologies provide an excellent opportunity to gain research experience and explore if a scientific career is right for you. Currently we offer positions to outstanding students interested in Next Generation Sequencing (NGS) data analysis. Applications are accepted throughout the year. Accepted students will be listed on web with their schedules. Accepted students can attend our future workshops and trainings freely at the specified venue.</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34485/phyloxml-xml-for-evolutionary-biology-and-comparative-genomics</guid>
	<pubDate>Wed, 29 Nov 2017 10:04:48 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34485/phyloxml-xml-for-evolutionary-biology-and-comparative-genomics</link>
	<title><![CDATA[phyloXML:  XML for evolutionary biology and comparative genomics]]></title>
	<description><![CDATA[<p><a href="http://www.biomedcentral.com/1471-2105/10/356/">phyloXML</a><span>&nbsp;(</span><a href="http://www.phyloxml.org/examples_syntax/phyloxml_syntax_example_1.html">example</a><span>) is an&nbsp;</span><a href="http://en.wikipedia.org/wiki/XML">XML</a><span>&nbsp;language designed to describe phylogenetic trees (or networks) and associated data. PhyloXML provides elements for commonly used features, such as taxonomic information, gene names and identifiers, branch lengths, support values, and gene duplication and speciation events. Using these standardized elements allows interoperability between various applications and databases. Furthermore, both due to extensible nature of XML itself and the provision of &lt;property&gt; elements by phyloXML, extensibility as well as domain specific applications are ensured. The structure of phyloXML is described by&nbsp;</span><a href="http://en.wikipedia.org/wiki/XML_Schema_%28W3C%29">XML Schema Definition (XSD)</a><span>&nbsp;language.</span></p><p>Address of the bookmark: <a href="http://www.phyloxml.org/" rel="nofollow">http://www.phyloxml.org/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36267/pspairwise-sequentially-markovian-coalescent-psmc-model</guid>
	<pubDate>Thu, 19 Apr 2018 05:29:23 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36267/pspairwise-sequentially-markovian-coalescent-psmc-model</link>
	<title><![CDATA[PSPairwise Sequentially Markovian Coalescent (PSMC) model]]></title>
	<description><![CDATA[<p><span>Implementation of the Pairwise Sequentially Markovian Coalescent (PSMC) model</span></p><p>Address of the bookmark: <a href="https://github.com/lh3/psmc" rel="nofollow">https://github.com/lh3/psmc</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/38649/ngs-platforms-launched-by-bgi%E2%80%99s-mgi-tech</guid>
	<pubDate>Thu, 10 Jan 2019 04:42:06 -0600</pubDate>
	<link>https://bioinformaticsonline.com/news/view/38649/ngs-platforms-launched-by-bgi%E2%80%99s-mgi-tech</link>
	<title><![CDATA[NGS Platforms launched by BGI’s MGI Tech]]></title>
	<description><![CDATA[<p>MGI Tech Co., Ltd. (MGI), a subsidiary of BGI Group, is committed to enabling effective and affordable healthcare solutions for all. Based on its proprietary technology, MGI produces sequencing devices, equipment, consumables and reagents to support life science research, medicine and healthcare. MGI's multi-omics platforms include genetic sequencing, mass spectrometry and medical imaging. Providing real-time, comprehensive, life-long solutions, its mission&nbsp;is to&nbsp;develop and promote advanced life science tools for future healthcare.</p><p>MGI, a subsidiary of global genomics leader BGI Group, announced pricing and its first early access customer for the new ultra high-throughput sequencer, MGISEQ-T7, saying it has driven down sequencing cost to&nbsp;$5&nbsp;per gigabyte, with exceptionally high accuracy. Such innovations are helping more people to realize the benefits of genomic information.</p><p>In October, MGI launched the MGISEQ-T7, a highly flexible production-scale platform that is the most powerful sequencer to date. It can produce as many as 60 whole human genomes in one day. The instrument sells for&nbsp;$1 million.</p><p>The T7 enables simultaneous but independent operation of up to four flow cells, which means different applications such as single-cell RNA sequencing, whole exome sequencing and whole genome sequencing can be run in different flow cells at the same time. This helps to reduce costs, allowing MGI to offer the most competitive sequencing price in the market.</p><p><span>Powered by DNBseq&trade;, MGISEQ delivers quality data with accuracy for SNP and Indel calling rate of 99.9% and 99%, respectively, along with decreased duplication rate down to less than 2 percent, and almost zero Index mis-assignment rate.</span></p><p><span><span>SOURCE MGI</span></span></p><p>https://www.bgi.com/global/company/news/bgis-mgi-tech-launches-two-new-ngs-platforms/</p><p>http://en.mgitech.cn/</p>]]></description>
	<dc:creator>Jit</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40834/nucleus-python-and-c-code-for-reading-and-writing-genomics-data</guid>
	<pubDate>Sun, 02 Feb 2020 08:14:19 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40834/nucleus-python-and-c-code-for-reading-and-writing-genomics-data</link>
	<title><![CDATA[Nucleus: Python and C++ code for reading and writing genomics data.]]></title>
	<description><![CDATA[<p>Nucleus is a library of Python and C++ code designed to make it easy to read, write and analyze data in common genomics file formats like SAM and VCF. In addition, Nucleus enables painless integration with the TensorFlow machine learning framework, as anywhere a genomics file is consumed or produced, a TensorFlow tfrecords file may be used instead.</p><p>Address of the bookmark: <a href="https://github.com/google/nucleus" rel="nofollow">https://github.com/google/nucleus</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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