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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/22793?offset=870</link>
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	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43110/quasimodo-quasispecies-metric-determination-on-omics</guid>
	<pubDate>Sat, 26 Jun 2021 15:22:56 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43110/quasimodo-quasispecies-metric-determination-on-omics</link>
	<title><![CDATA[QuasiModo - Quasispecies Metric Determination on Omics]]></title>
	<description><![CDATA[<p><span>This repository contains the scripts and pipeline that reproduces the results of the HCMV benchmarking study. In this study we evaluated genome assemblers and variant callers on 10 in vitro generated, mixed strain HCMV sequence samples, each consisting of two lab strains in different abundance ratios. This tool can also be used to evaluate assemblies and variant calling results on other similar datasets.</span></p>
<p><span>https://academic.oup.com/bib/article/22/3/bbaa123/5868070</span></p><p>Address of the bookmark: <a href="https://github.com/hzi-bifo/Quasimodo" rel="nofollow">https://github.com/hzi-bifo/Quasimodo</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43427/ogdraw-draw-organelle-genome-maps</guid>
	<pubDate>Tue, 05 Oct 2021 03:34:35 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43427/ogdraw-draw-organelle-genome-maps</link>
	<title><![CDATA[OGDRAW - Draw Organelle Genome Maps]]></title>
	<description><![CDATA[<p>OrganellarGenomeDRAW converts annotations in the&nbsp;<a href="https://www.ncbi.nlm.nih.gov/genbank/">GenBank</a>&nbsp;or&nbsp;<a href="https://www.ebi.ac.uk/ena">EMBL/ENA</a>&nbsp;format into graphical maps. The input has to be a&nbsp;<a href="https://www.ncbi.nlm.nih.gov/Sitemap/samplerecord.html">GenBank&nbsp;</a>or&nbsp;<a href="https://www.ebi.ac.uk/ena/submit/flat-file">EMBL/ENA flat file</a>&nbsp;wherase the output can vary among several types of files. The application is optimized to create detailed high-quality maps of organellar genomes (plastid and mitochondria). Nevertheless, you can upload most<span style="color: #0b0118;">&nbsp;database</span>&nbsp;entries.</p>
<p>&nbsp;</p>
<p>Please take a look at our&nbsp;<a href="https://chlorobox.mpimp-golm.mpg.de/OGDraw-FAQ.html">FAQ section</a>&nbsp;and do not hesitate to report bugs or suggestions for improvements by&nbsp;<a href="mailto:chlorobox@mpimp-golm.mpg.de?subject=OGDRAW">email</a>.</p><p>Address of the bookmark: <a href="https://chlorobox.mpimp-golm.mpg.de/OGDraw.html" rel="nofollow">https://chlorobox.mpimp-golm.mpg.de/OGDraw.html</a></p>]]></description>
	<dc:creator>Abhi</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43690/ucsc-sars-cov-2-genome-browser</guid>
	<pubDate>Thu, 06 Jan 2022 06:48:40 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43690/ucsc-sars-cov-2-genome-browser</link>
	<title><![CDATA[UCSC SARS-CoV-2 Genome Browser]]></title>
	<description><![CDATA[<p><span>The UCSC SARS-CoV-2 Genome Browser (</span><a href="https://genome.ucsc.edu/covid19.html">https://genome.ucsc.edu/covid19.html</a><span>) is an adaptation of our popular genome-browser visualization tool for this virus, containing many annotation tracks and new features, including conservation with similar viruses, immune epitopes, RT&ndash;PCR and sequencing primers and CRISPR guides. We invite all investigators to contribute to this resource to accelerate research and development activities globally.</span></p><p>Address of the bookmark: <a href="https://www.nature.com/articles/s41588-020-0700-8" rel="nofollow">https://www.nature.com/articles/s41588-020-0700-8</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43859/mumco-is-a-simple-bash-script-that-uses-whole-genome-alignment-information-provided-by-mummer-v4-to-detect-variants</guid>
	<pubDate>Wed, 27 Apr 2022 04:34:12 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43859/mumco-is-a-simple-bash-script-that-uses-whole-genome-alignment-information-provided-by-mummer-v4-to-detect-variants</link>
	<title><![CDATA[MUM&amp;Co is a simple bash script that uses Whole Genome Alignment information provided by MUMmer (v4) to detect variants.]]></title>
	<description><![CDATA[<p dir="auto">MUM&amp;Co is able to detect:<br>Deletions, insertions, tandem duplications and tandem contractions (&gt;=50bp &amp; &lt;=150kb)<br>Inversions (&gt;=1kb) and translocations (&gt;=10kb)</p><p>Address of the bookmark: <a href="https://github.com/SAMtoBAM/MUMandCo" rel="nofollow">https://github.com/SAMtoBAM/MUMandCo</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44537/the-atcc-genome-portal</guid>
	<pubDate>Wed, 15 May 2024 14:24:16 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44537/the-atcc-genome-portal</link>
	<title><![CDATA[The ATCC Genome Portal]]></title>
	<description><![CDATA[<p><span>The ATCC Genome Portal (AGP,&nbsp;</span><a href="https://genomes.atcc.org/">https://genomes.atcc.org/</a><span>) is a database of authenticated genomes for bacteria, fungi, protists, and viruses held in ATCC&rsquo;s biorepository. It now includes 3,938 assemblies (253% increase) produced under ISO 9000 by ATCC. Here, we present new features and content added to the AGP for the research community.</span></p><p>Address of the bookmark: <a href="https://genomes.atcc.org/" rel="nofollow">https://genomes.atcc.org/</a></p>]]></description>
	<dc:creator>Abhi</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44489/proksee</guid>
	<pubDate>Wed, 27 Mar 2024 11:11:54 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44489/proksee</link>
	<title><![CDATA[Proksee]]></title>
	<description><![CDATA[<p><span>Proksee is an expert system for genome assembly, annotation and visualization. To begin using Proksee, provide a complete genome sequence, sequencing reads or a CGView/Proksee map JSON file.</span></p>
<fieldset><legend>Please Cite the Following</legend>
<div>Grant JR, Enns E, Marinier E, Mandal A, Herman EK, Chen C, Graham M, Van Domselaar G, and Stothard P</div>
<div><a href="https://pubmed.ncbi.nlm.nih.gov/37140037/">Proksee: in-depth characterization and visualization of bacterial genomes</a></div>
<div>Nucleic Acids Research, 2023, gkad326, https://doi.org/10.1093/nar/gkad326</div>
</fieldset><p>Address of the bookmark: <a href="https://proksee.ca/" rel="nofollow">https://proksee.ca/</a></p>]]></description>
	<dc:creator>LEGE</dc:creator>
</item>
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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>
</item>
<item>
	<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>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/videolist/watch/16686/sequence-viewer-download-transcripts-exons-and-proteins</guid>
	<pubDate>Mon, 15 Sep 2014 17:30:36 -0500</pubDate>
	<link>https://bioinformaticsonline.com/videolist/watch/16686/sequence-viewer-download-transcripts-exons-and-proteins</link>
	<title><![CDATA[Sequence Viewer: Download Transcripts, Exons and Proteins]]></title>
	<description><![CDATA[<iframe width="" height="" src="https://www.youtube-nocookie.com/embed/ZWnLyYKozaI" frameborder="0" allowfullscreen></iframe>How to download FASTA sequence for certain gene features while in the NCBI's Sequence Viewer.

Sequence Viewer homepage:
www.ncbi.nlm.nih.gov/projects/sviewer/

Sequence Viewer playlist:
https://www.youtube.com/playlist?list=PL76D7EE6A6A8AC1C3]]></description>
	
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34565/fogsaa-fast-optimal-global-sequence-alignment-algorithm</guid>
	<pubDate>Fri, 08 Dec 2017 14:41:08 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34565/fogsaa-fast-optimal-global-sequence-alignment-algorithm</link>
	<title><![CDATA[FOGSAA: Fast Optimal Global Sequence Alignment Algorithm]]></title>
	<description><![CDATA[<p>Sequence alignment algorithms are widely used to infer similarirty and the point of differences between pair of sequences. FOGSAA is a fast Global alignment algorithm. It is basically a branch and bound approach which starts branch expansion in a greedy way taking the symbols from the given pair of sequences (protein or nucleotide) and results in an optimal alignment faster than conventional dymanic programming techniques. It is also better than the heuristic methods with respect to alignment quality.</p><p>Address of the bookmark: <a href="http://www.isical.ac.in/~bioinfo_miu/FOGSAA.htm" rel="nofollow">http://www.isical.ac.in/~bioinfo_miu/FOGSAA.htm</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

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