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	<title><![CDATA[BOL: Jitendra Narayan's News]]></title>
	<link>https://bioinformaticsonline.com/news/owner/admin?</link>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/45351/ai-uncovers-hidden-secrets-in-bacterial-dna-opening-new-frontiers-in-genomic-research</guid>
	<pubDate>Fri, 25 Sep 2026 22:38:42 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/45351/ai-uncovers-hidden-secrets-in-bacterial-dna-opening-new-frontiers-in-genomic-research</link>
	<title><![CDATA[AI Uncovers Hidden Secrets in Bacterial DNA, Opening New Frontiers in Genomic Research]]></title>
	<description><![CDATA[<div style="margin-top: 0.5em; margin-bottom: 0.5em;">Scientists are now using artificial intelligence in order to examine sections of bacterial DNA that have not been looked at before. This method is showing potential RNA interactions and previously unknown genetic systems which could alter our understanding of microbes. A new study presents Minerva, a genome language model, demonstrating that AI can assist researchers in identifying biological patterns that traditional techniques might fail to detect.</div><div style="margin-top: 0.5em; margin-bottom: 0.5em;">The study, which was made available as a preprint on bioRxiv on 23 September 2026, focuses on the non-coding sections of DNA that are still largely unknown. Although these areas do not produce proteins, they can contain important signals and instructions which have an effect on cell function. The research presents a novel approach to investigating how bacteria handle and control their genetic information.</div><div style="margin-top: 0.5em; margin-bottom: 0.5em;"><span style="font-weight: bold;">AI maps previously unexplored genomic regions</span></div><div style="margin-top: 0.5em; margin-bottom: 0.5em;">The team developed Minerva in order to identify possible interactions between different regions in microbial genomes; rather than depending on similarities with known sequences, Minerva predicts these relationships directly from the DNA by using patterns learned by a genome language model.</div><div style="margin-top: 0.5em; margin-bottom: 0.5em;">On 150 bacterial genomes, Minerva identified a large number of interactions that were not included in the existing annotations. The researchers stated that 84.3 per cent of the predicted intergenic base-pairing interactions were not present in the current annotations, which demonstrates that AI can be of help in generating new ideas in biology.</div><div style="margin-top: 0.5em; margin-bottom: 0.5em;"><span style="font-weight: bold;">Unusual RNA structures and viral genetic systems identified</span></div><div style="margin-top: 0.5em; margin-bottom: 0.5em;">The study also examined a bacterial RNA family known as TwoAYGGAY in Pseudomonas; the model anticipated longer RNA structures and identified associations with repeated DNA sequences, thus providing new insights into how these non-coding elements are organised and how they have evolved.</div><div style="margin-top: 0.5em; margin-bottom: 0.5em;">In a separate section of the study, the researchers examined reverse transcriptase systems associated with bacteriophages, which are viruses that infect bacteria. They identified RNA arrays that maintain their structure but have different sequences and were linked to Unknown Group 27 reverse transcriptases. The findings indicate that these RNAs could function as templates for the production of complementary DNA that is capable of forming hairpin shapes.</div><div style="margin-top: 0.5em; margin-bottom: 0.5em;">The researchers also observed that Minerva was able to detect patterns associated with protein-coding areas, even though it had not been trained to do so. This indicates that genome language models may pick up on biological signals that go beyond what they were intended to identify.</div><div style="margin-top: 0.5em; margin-bottom: 0.5em;"><span style="font-weight: bold;">Implications for future genomic research</span></div><div style="margin-top: 0.5em; margin-bottom: 0.5em;">The fact that artificial intelligence is becoming increasingly important in the field of microbial genomics is shown by the fact that models such as Minerva are able to predict interactions and identify patterns in areas which have not been extensively studied, thus helping researchers to decide what to study next and enabling them to gain a better understanding of biological systems that are still not well understood.</div><div style="margin-top: 0.5em; margin-bottom: 0.5em;">Yet the predictions do not reveal the exact function of each element identified. In order to verify which of the predicted interactions actually take place in living cells and the way in which they affect the microbes, experiments will be necessary. Although the study has undergone peer review, it does nonetheless offer a promising illustration of how machine learning can complement traditional genomics and assist scientists in moving from the identification of known genes to the exploration of the complex relationships that shape microbial life.</div><div style="margin-top: 0.5em; margin-bottom: 0.5em;">More at https://www.biorxiv.org/content/10.64898/2026.09.22.753630v2.full.pdf</div><div style="color: #000000; font-size: medium;">&nbsp;</div>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/19556/genome-origami</guid>
	<pubDate>Fri, 12 Dec 2014 22:48:17 -0600</pubDate>
	<link>https://bioinformaticsonline.com/news/view/19556/genome-origami</link>
	<title><![CDATA[Genome Origami]]></title>
	<description><![CDATA[<p>There are several interesting factoid about our genomes, one of them is their folding. If we stretched out the DNA in a single cell, which is only a few millionths of an inch wide, it would span more than six feet. In other word, the size of six feet DNA fold themself to fit in a few millionths of an inch wide space. These DNA folding is a dynamic process that changes over time (!!). Researchers around the world have been trying to understand how DNA folds itself up so efficiently, and a recent post on the NIH Director&rsquo;s Blog highlights new research illustrating how the human genome folds inside the cell&rsquo;s nucleus, as well as how DNA folding affects gene regulation. The research team created this delightful video that demonstrates the principles involved using origami art.</p><p>http://bioinformaticsonline.com/videolist/watch/19555/a-3d-map-of-the-human-genome<br /><br />Researchers have been working to determine how cells regulate gene expression for nearly as long as we&rsquo;ve known about DNA. How, for example, do nerve cells know to turn off only nerve cell genes and turn off bone cell genes? DNA folding loops are part of the answer. This research team, which published their findings in a paper in Cell http://www.cell.com/cell/abstract/S0092-8674%2814%2901497-4 , found that the number of loops is much lower than expected. There are only 10,000 loops instead of the predicted millions, and they form on/off switches in DNA.<br /><br /></p><p>More at http://www.eurekalert.org/pub_releases/2014-12/ru-3mr121114.php</p><p>Reference http://www.cell.com/cell/abstract/S0092-8674%2814%2901497-4</p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/5436/the-anatomy-of-successful-computational-biology-software</guid>
	<pubDate>Thu, 10 Oct 2013 11:53:08 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/5436/the-anatomy-of-successful-computational-biology-software</link>
	<title><![CDATA[The anatomy of successful computational biology software]]></title>
	<description><![CDATA[<p>Creators of software widely used in computational biology discuss the factors that contributed to their success</p><p><em>Nature Biotechnology</em><span>&nbsp;spoke with Altschul and several other originators of computational biology software programs widely used today (</span><a href="http://www.nature.com/nbt/journal/v31/n10/full/nbt.2721.html#t1">Table 1</a><span>). The conversations explored what makes certain software tools successful, the unique challenges of developing them for biological research and how the field of computational biology, as a whole, can move research agendas forward. What follows is an edited compilation of interviews.</span></p><p>Detail @&nbsp;<a href="http://www.nature.com/nbt/journal/v31/n10/full/nbt.2721.html">http://www.nature.com/nbt/journal/v31/n10/full/nbt.2721.html</a></p><p>News Source @ Nature</p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/4433/upcoming-r-webinar</guid>
	<pubDate>Wed, 11 Sep 2013 10:30:16 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/4433/upcoming-r-webinar</link>
	<title><![CDATA[Upcoming R Webinar]]></title>
	<description><![CDATA[<p>This webinar will describe an R based approach to considerably speed GWAS computation time on a notebook book computer.</p><p>More http://www.extension.org/pages/68354/upcoming-webinar:-fast-semi-parallel-linear-and-logistic-regression-for-genome-wide-association-studi#.UjCL9azyPqV</p><p>Register @ https://www1.gotomeeting.com/register/237810425</p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/4419/a-fast-package-to-parse-blast</guid>
	<pubDate>Tue, 10 Sep 2013 16:58:56 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/4419/a-fast-package-to-parse-blast</link>
	<title><![CDATA[A fast package to parse BLAST]]></title>
	<description><![CDATA[<p>In current era, we are handling huge amount of genomics data, and analysing it to make some biological sense out of it. Large-scale sequence studies requiring BLAST-based analysis produce huge amounts of data to be parsed. There are several BLAST parsers are available, but they are often missing some important features, such as keeping all information from the raw BLAST output, allowing direct access to single results, and performing logical operations over them.</p><p>Massimiliano Orsini and Simone Carcangiu develope a new and fast fast package "BlaSTorage" to parse and store BLAST results. BlaSTorage shows comparable speed of more basic parser written in compiled languages as C++ and can be easily integrated into web applications or software pipelines.</p><p>Find more @ http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3571973/</p><p>http://biowiki.crs4.it/biowiki/MassimilianoOrsini</p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/4408/fourth-branch-of-life</guid>
	<pubDate>Mon, 09 Sep 2013 21:48:37 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/4408/fourth-branch-of-life</link>
	<title><![CDATA[Fourth Branch of Life]]></title>
	<description><![CDATA[<p>Scientist have found the biggest viruses known, pandoraviruses which opened up entirely /completely... new questions questions and raise objections to in science. It even suggesting a fourth domain of life.</p><p>The new visrus are about one micron&mdash;a thousandth of a millimeter&mdash;in length, the newfound genus Pandoravirus dwarfs other viruses, which range in size from about 50 nanometers up to 100 nanometers. A genus is a taxonomic ranking between species and family.</p><p>Find&nbsp; more at @ http://www.nature.com/scitable/blog/viruses101/newly_found_pandoraviruses_hint_at</p><p>http://news.nationalgeographic.co.uk/news/2013/07/130718-viruses-pandoraviruses-science-biology-evolution/</p><p>&nbsp;</p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/4295/rcsb-pdb-sept13-release</guid>
	<pubDate>Thu, 05 Sep 2013 15:07:48 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/4295/rcsb-pdb-sept13-release</link>
	<title><![CDATA[RCSB PDB Sept'13 Release]]></title>
	<description><![CDATA[<p>RCSB PDB Sept'13 Release offers following new features:</p><p>- New tools to search for drugs and drug targets<br />- Improved interface for 3D visualisation using Jmol/JSmol<br />- An update to the representation of protein symmetry and stoichiometry.<br />- Improvements when performing sequence searches.</p><p>Reference</p><p><a href="http://www.rcsb.org/pdb/static.do?p=general_information/whats_new.jsp?b=1308">http://www.rcsb.org/pdb/static.do?p=general_information/whats_new.jsp?b=1308</a></p><p>&nbsp;</p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/4162/4273%CF%80-bioinformatics-education-on-low-cost-arm-hardware</guid>
	<pubDate>Mon, 02 Sep 2013 07:02:43 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/4162/4273%CF%80-bioinformatics-education-on-low-cost-arm-hardware</link>
	<title><![CDATA[4273π: Bioinformatics education on low cost ARM hardware]]></title>
	<description><![CDATA[<p>Are you teaching bioinformatics at universities and found it complicated by typical computer classroom settings. As well as running software locally and online, students should gain experience of systems administration. Hmm don't worry there is one new OS for the rescue. 4273<em>&pi;</em>, an operating system image for Raspberry Pi based on Raspbian Linux. It provides an attractive, general-purpose computing environment, within which the course 4273&pi; Bioinformatics for Biologists is embedded.<br /><br />Though far slower than current desktop and laptop computers, the Raspberry Pi is notably faster than the Cray 1 supercomputer, a marvel of computer speed in its day. The Raspberry Pi approach includes all the benefits of the laptop approach, above, but at lower cost. In addition, the Raspberry Pi is a new and exciting computer system, which in itself can add interest to the course.<br /><br />As the Raspbian operating system, Raspberry Pi firmware and hardware and 4273&pi; Bioinformatics for Biologists teaching material develop, further releases of 4273&pi; will be made available. It is anticipated that there will be a minimum of two releases per year during the next four years.</p><p>4273<em>&pi;</em> is a means to teach bioinformatics, including systems administration tasks, to undergraduates at low cost.</p><p>Descriptive paper @ http://www.biomedcentral.com/1471-2105/14/243</p><p>Image source: BMC Bioinformatics</p><p><img src="http://www.biomedcentral.com/content/download/figures/1471-2105-14-243-1.png" alt="image" style="border: 0px; border: 0px;"></p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/3854/user-dashboard</guid>
	<pubDate>Sat, 24 Aug 2013 05:13:10 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/3854/user-dashboard</link>
	<title><![CDATA[User Dashboard]]></title>
	<description><![CDATA[<p>Added a new feature "User Dashboard" that lets you track the activity and content on this site that matters to you.</p><p>Now you can customized your BOL website view on your own dashboard.</p><p>Cheers</p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/2778/mom-knows-best</guid>
	<pubDate>Thu, 22 Aug 2013 13:30:43 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/2778/mom-knows-best</link>
	<title><![CDATA[Mom Knows Best]]></title>
	<description><![CDATA[<p>We always get instructions to wash our hands, sterilize kitchen stuff and bla bla. However, recent findings suggest something else. Perhaps we can't survive, or will face lots of problems if bacteria&rsquo;s colonies are absent in mother womb. Please find the detail sources of microbial transmission in humans from mother to child in recently published PLOS paper.</p><p><a href="http://www.plosbiology.org/article/info%3Adoi%2F10.1371%2Fjournal.pbio.1001631">http://www.plosbiology.org/article/info%3Adoi%2F10.1371%2Fjournal.pbio.1001631</a></p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
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