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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/44663?offset=60</link>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/45338/dna-in-pieces-survival-in-progress-the-rotifer%E2%80%99s-incredible-secret</guid>
	<pubDate>Fri, 18 Sep 2026 03:07:47 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/45338/dna-in-pieces-survival-in-progress-the-rotifer%E2%80%99s-incredible-secret</link>
	<title><![CDATA[DNA in Pieces, Survival in Progress: The Rotifer’s Incredible Secret]]></title>
	<description><![CDATA[<p>A creature smaller than a grain of sand has discovered a surprising method of surviving damage that can break its DNA apart. It lives in the mosses and lichens, in the thin films of water that show up after rain and disappear when the area dries out. Although it has no hard armor, no sharp claws, and no venom, it is still able to survive even when its chromosomes are shattered by radiation and can pass on some of that damaged DNA to its offspring so that the repair process can go on for several generations. The animal in question is a bdelloid rotifer named Adineta vaga, and its unusual method of survival is providing scientists with new ideas regarding how DNA damage can be repaired.</p><p>Bdelloid rotifers are small animals well known for their ability to survive in harsh conditions. They can endure extreme dehydration by entering a state of dormancy and then revive when water becomes available again. Scientists have always been interested in the degree to which these animals resist radiation, since radiation can severely damage DNA by causing both of its strands to break. Interestingly, Adineta vaga's ability to survive radiation may be connected to the way in which it tolerates drying out, as dehydration can also damage DNA. The rotifer probably evolved strong DNA protection and repair mechanisms primarily as a response to its severe environment. Its resistance to radiation is merely a byproduct of adapting to the cycles of drying and rehydration.</p><p>In order to find out more about this ability, the researchers subjected A. vaga to proton radiation and then examined what effect it had on its chromosomes. The radiation caused serious damage, resulting in hundreds of breaks in the DNA. For the vast majority of organisms, such extensive chromosome damage would be disastrous; it's similar to going through an instruction manual in a shredder and ending up with a large number of separate fragments. The scientists believed that the rotifers would repair their chromosomes before producing offspring. However, what they discovered was unexpected: some of the broken pieces of chromosome did survive and were passed on to the next generations, where the repair process continued.</p><p>The discovery took on even greater interest when the scientists examined the offspring of the irradiated rotifers. Rather than observing the same DNA damage in all the generations, they found different sized sections missing and evidence that some of the genetic regions which had been lost were being slowly restored. The researchers proposed that the rotifers use a repair mechanism known as Break-Induced Homologous Extension Repair, or BIHER. In simple terms, a broken piece of DNA can locate a matching sequence on the other chromosome and use it as a guide to rebuild itself. If the damage is beyond what can be repaired in one generation, the repair process can continue in the next.</p><p>What makes the rotifer's method of repairing DNA so unusual is that, normally, we consider DNA repair to take place immediately after damage has occurred, with the cell rapidly repairing the damaged DNA. In A. vaga, however, the repair process can be a lot longer. Certain pieces of chromosome survive the initial damage, are inherited, and then serve as the basis for further repairs in later generations. It's as if one generation begins mending a broken book, the next one continues the work, and another eventually completes the job until all the missing parts have been restored.</p><p>One reason why this might work is that bdelloid rotifers have holocentric chromosomes. Rather than having a single point, as most chromosomes do, which controls movement during cell division, the ability to move is distributed along the entire length of their chromosomes. As a result, fragments of chromosomes are sometimes able to retain the parts that are necessary for them to move and divide, and this may account for how broken pieces of chromosome can last long enough to be passed on and then repaired.</p><p>This finding could have implications that go beyond those concerning rotifers. Scientists are interested in understanding how genomes cope with severe chromosome damage, for example in the case of chromothripsis, where chromosomes break and are then reassembled in new configurations. Investigating A. vaga could help us to learn how cells manage large genetic issues. Moreover, its high resistance to radiation might also prove useful in research into extreme environments, such as the radiation hazards encountered on long space missions. However, these are ideas for future investigation; at present the rotifer's DNA repair mechanism cannot be used to protect people from radiation.</p><p>What is perhaps the most interesting aspect of this discovery is that the rotifer's remarkable ability could have developed for a very simple reason. Since an animal living in moss constantly undergoes periods of drying out and then getting wet again, the same mechanisms that protect its DNA when it is dehydrated might also enable it to survive radiation which would damage most other animals. Therefore, the rotifer probably did not evolve solely in order to resist radiation; instead, it became extremely good at coping with the difficult conditions it encounters, and radiation resistance was just a byproduct.</p><p>The case of Adineta vaga demonstrates that survival does not always mean avoiding damage; on some occasions it involves being able to recover from damage which appears to be impossible to repair. This small animal can survive having its chromosomes broken into many pieces, retain some of those pieces, pass them on to its offspring, and continue to repair them over successive generations. Although we generally regard DNA as something fragile that must always remain intact, the rotifer indicates an alternative possibility: perhaps a genome does not have to be perfect in order to survive, since sometimes the pieces last long enough for life to reassemble them, bit by bit, generation after generation.</p><p>Ream more at&nbsp;https://www.science.org/doi/10.1126/sciadv.aee0891</p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/file/view/42693/dna-rna-meme</guid>
	<pubDate>Thu, 28 Jan 2021 11:23:14 -0600</pubDate>
	<link>https://bioinformaticsonline.com/file/view/42693/dna-rna-meme</link>
	<title><![CDATA[DNA RNA MEME]]></title>
	<description><![CDATA[<p>Explain the DNA and RNA with picture ...</p>]]></description>
	<dc:creator>Neel</dc:creator>
	<enclosure url="https://bioinformaticsonline.com/file/download/42693" length="41627" type="image/jpeg" />
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36518/mix-combining-multiple-assemblies-from-ngs-data</guid>
	<pubDate>Tue, 08 May 2018 04:58:05 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36518/mix-combining-multiple-assemblies-from-ngs-data</link>
	<title><![CDATA[MIX: Combining multiple assemblies from NGS data]]></title>
	<description><![CDATA[<p>Mix is a tool that combines two or more draft assemblies, without relying on a reference genome and has the goal to reduce contig fragmentation and thus speed-up genome finishing. The proposed algorithm builds an extension graph where vertices represent extremities of contigs and edges represent existing alignments between these extremities. These alignment edges are used for contig extension. The resulting output assembly corresponds to a path in the extension graph that maximizes the cumulative contig length.</p>
<p>The Mix algorithm, approach and results were published in BMC bioinformatics :&nbsp;<a href="http://www.biomedcentral.com/1471-2105/14/S15/S16">http://www.biomedcentral.com/1471-2105/14/S15/S16</a>.</p><p>Address of the bookmark: <a href="https://github.com/cbib/MIX" rel="nofollow">https://github.com/cbib/MIX</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/39689/msaprobs-parallel-and-accurate-multiple-sequence-alignment</guid>
	<pubDate>Tue, 09 Jul 2019 23:58:44 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/39689/msaprobs-parallel-and-accurate-multiple-sequence-alignment</link>
	<title><![CDATA[MSAProbs - Parallel and accurate multiple sequence alignment]]></title>
	<description><![CDATA[<p><strong>MSAProbs</strong><span>&nbsp;is a well-established state-of-the-art multiple sequence alignment algorithm for protein sequences. The design of MSAProbs is based on a combination of pair hidden Markov models and partition functions to calculate posterior probabilities. Assessed using the popular benchmarks: BAliBASE, PREFAB, SABmark and OXBENCH, MSAProbs achieves statistically significant accuracy improvements over the existing top performing aligners, including ClustalW, MAFFT, MUSCLE, ProbCons and Probalign. In addition, MSAProbs is optimized for shared-memory CPUs by employing a multi-threaded design, and further parallelized for distributed-memory systems using MPI to overcome high memory overhead barrier and achieve good parallel and data-size scalability.</span></p><p>Address of the bookmark: <a href="http://msaprobs.sourceforge.net/homepage.htm#latest" rel="nofollow">http://msaprobs.sourceforge.net/homepage.htm#latest</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40940/consed-a-finishing-package-bam-file-viewer-assembly-editor-autofinish-autoreport-autoedit-and-align-reads-to-reference-sequence</guid>
	<pubDate>Fri, 07 Feb 2020 07:16:22 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40940/consed-a-finishing-package-bam-file-viewer-assembly-editor-autofinish-autoreport-autoedit-and-align-reads-to-reference-sequence</link>
	<title><![CDATA[Consed--A Finishing Package (BAM File Viewer, Assembly Editor, Autofinish, Autoreport, Autoedit, and Align Reads To Reference Sequence)]]></title>
	<description><![CDATA[<ul>
<li>Supports Illumina, 454, other Next-Gen and Sanger Reads and allows mixtures of these read types</li>
<li>Consed includes BamScape which can view bam files with unlimited numbers of reads. BamScape can bring up consed to edit reads and the reference sequence in targeted regions.</li>
<li>Consed is compatible with Newbler, Cross_match, Phrap, MIRA, Velvet and PCAP output.</li>
<li>Quickly takes the user to each variant site for viewing (also available as an automated report)</li>
<li>Overview of assembly can help detect and fix misassemblies</li>
<li>Editing time reduced by the program's ability to pin-point problem areas</li>
<li>Editing is guided by error probabilities</li>
</ul><p>Address of the bookmark: <a href="http://www.phrap.org/consed/consed.html" rel="nofollow">http://www.phrap.org/consed/consed.html</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/40596/igblast-a-popular-ncbi-package-for-classifying-and-analyzing-immunoglobulin-ig-and-t-cell-receptor-tcr-variable-domain-sequences</guid>
	<pubDate>Thu, 23 Jan 2020 11:34:37 -0600</pubDate>
	<link>https://bioinformaticsonline.com/news/view/40596/igblast-a-popular-ncbi-package-for-classifying-and-analyzing-immunoglobulin-ig-and-t-cell-receptor-tcr-variable-domain-sequences</link>
	<title><![CDATA[IgBLAST: a popular NCBI package for classifying and analyzing immunoglobulin (IG) and T cell receptor (TCR) variable domain sequences]]></title>
	<description><![CDATA[<p>NCBI team released a new version of IgBLAST with four new improvements. IgBLAST is a popular NCBI package for classifying and analyzing immunoglobulin (IG) and T cell receptor (TCR) variable domain sequences. Improvements are:<span style="text-decoration: underline;"></span><span style="text-decoration: underline;"></span></p><p>&nbsp;&nbsp;&nbsp; 1. Support for the new FWR4 annotation feature in the AIRR format, both in standard format and in the AIRR alignment format.<span style="text-decoration: underline;"></span><span style="text-decoration: underline;"></span></p><p>&nbsp;&nbsp;&nbsp; 2. The previous &ldquo;-penalty&rdquo; parameter was renamed as -V_penalty to be consistent with other IgBLAST penalty options.<span style="text-decoration: underline;"></span><span style="text-decoration: underline;"></span></p><p>&nbsp;&nbsp;&nbsp; 3. Restored constant internal BLAST search parameters for domain annotation (i.e., FWR/CDR) such that this process is not influenced by user parameters.<span style="text-decoration: underline;"></span><span style="text-decoration: underline;"></span></p><p>&nbsp;&nbsp;&nbsp; 4. Corrected FWR/CDR annotations for certain mouse VK and rat VH germline genes.<span style="font-size: 12.8px;">&nbsp;</span></p><p><span style="text-decoration: underline;"></span></p><p>IgBLAST 1.15.0 is available for&nbsp;<a href="https://ftp.ncbi.nih.gov/blast/executables/igblast/release/LATEST/" target="_blank">download</a>&nbsp;from the BLAST FTP area. See the the new&nbsp;<a href="https://ncbi.github.io/igblast/" target="_blank">manual</a>&nbsp;on GitHub for information about setting up and running IgBLAST.</p><p><span style="text-decoration: underline;"></span></p><p>&nbsp;If you have any questions or concerns, please contact&nbsp;<a href="mailto:blast-help@ncbi.nlm.nih.gov" target="_blank" title="Follow link">blast-help@ncbi.nlm.nih.gov</a><span style="text-decoration: underline;"></span><span style="text-decoration: underline;"></span></p><p><span style="text-decoration: underline;"></span>&nbsp;</p>]]></description>
	<dc:creator>BioJoker</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43290/the-snakemake-wrappers-repository</guid>
	<pubDate>Thu, 19 Aug 2021 04:39:34 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43290/the-snakemake-wrappers-repository</link>
	<title><![CDATA[The Snakemake Wrappers repository]]></title>
	<description><![CDATA[<p><span>The Snakemake Wrapper Repository is a collection of reusable wrappers that allow to quickly use popular tools from&nbsp;</span><a href="https://snakemake.readthedocs.io/">Snakemake</a><span>&nbsp;rules and workflows.</span></p>
<p>More at&nbsp;https://github.com/snakemake/snakemake-wrappers</p><p>Address of the bookmark: <a href="https://snakemake-wrappers.readthedocs.io/en/stable/" rel="nofollow">https://snakemake-wrappers.readthedocs.io/en/stable/</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/120/user</guid>
	<pubDate>Wed, 10 Jul 2013 14:41:49 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/120/user</link>
	<title><![CDATA[useR!]]></title>
	<description><![CDATA[<p><span>The R project actively supports two conference series, organized regularly by members from the R community: useR! - providing a forum to the R user community - and DSC - a platform for developers of statistical software.</span></p><p><span>Recently useR! conference have been organized&nbsp;<span>University of Castilla-La Mancha, Albacete, Spain.</span></span></p><p><a href="http://www.edii.uclm.es/~useR-2013//">http://www.edii.uclm.es/~useR-2013//</a></p><p>&nbsp;</p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/2457/rdataminingcom-r-and-data-mining</guid>
	<pubDate>Thu, 15 Aug 2013 18:37:23 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/2457/rdataminingcom-r-and-data-mining</link>
	<title><![CDATA[Rdatamining.com : R and Data Mining]]></title>
	<description><![CDATA[<p>This website presents examples, documents and resources on data mining with R. <br>Documents on using R for data mining are available to download for non-commercial personal use, including&nbsp;R Reference card for Data Mining, R and Data Mining: Examples and Case Studies and Time Series Analysis and Mining with R.</p><p>Address of the bookmark: <a href="http://www.rdatamining.com/" rel="nofollow">http://www.rdatamining.com/</a></p>]]></description>
	<dc:creator>Poonam Mahapatra</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/8848/upgrade-r-303</guid>
	<pubDate>Mon, 10 Mar 2014 11:23:51 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/8848/upgrade-r-303</link>
	<title><![CDATA[Upgrade R 3.0.3]]></title>
	<description><![CDATA[<p>R is a free software programming language and software environment for statistical computing and graphics. The R language is widely used among statisticians and data miners for developing statistical software and data analysis. Polls and surveys of data miners are showing R's popularity has increased substantially in recent years. Recently the new version of R codename &ldquo;Warm Puppy" have been released.<br /><br />You can download the latest version from here http://cran.rstudio.com/ . Or, if you are using Windows, you can upgrade to the latest version using the installr package http://cran.r-project.org/web/packages/installr/ . Simply run the following code:<br /><br /># installing/loading the package:<br />if(!require(installr)) { <br />install.packages("installr"); require(installr)} #load / install+load installr<br />&nbsp;<br />updateR()<br /><br />I try to keep the installr package updated and useful. If you have any suggestions or remarks on the package, you&rsquo;re invited to leave a comment below.<br /><br />If you use the global library system http://www.r-statistics.com/2010/04/changing-your-r-upgrading-strategy-and-the-r-code-to-do-it-on-windows/ , you can run the following in the new version of R:<br /><br />source("http://www.r-statistics.com/wp-content/uploads/2010/04/upgrading-R-on-windows.r.txt")<br />New.R.RunMe()</p><p>Reference:</p><p>http://www.r-statistics.com/2014/03/r-3-0-3-is-released/</p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
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