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	<link>https://bioinformaticsonline.com/related/4590?offset=540</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/opportunity/view/23924/embl-postdoc-position-in-bacterial-gene-gain-loss</guid>
  <pubDate>Thu, 20 Aug 2015 14:09:21 -0500</pubDate>
  <link></link>
  <title><![CDATA[EMBL Postdoc position in Bacterial Gene Gain Loss]]></title>
  <description><![CDATA[
<p>A post-doctoral fellowship is available in the research groups of Nick Goldman (EBI) and John Welch (Genetics Department, Cambridge University) under the EMBL-EBI / Cambridge Computational Biomedical Postdoctoral Fellowship scheme.</p>

<p>The project is on bacterial gene gain and loss and emerging pathogenicity, and is described in full here: https://www.ebi.ac.uk/research/postdocs/ebpods/projects/goldman-welch-2015 . The EMBL-EBI / Cambridge Computational Biomedical Postdoctoral (“EBPOD”) </p>

<p>The closing date for applications is 3 September 2015. Nick Goldman EMBL-European Bioinformatics Institute Nick Goldman </p>

<p>More at https://www.ebi.ac.uk/research/postdocs/ebpods/projects/goldman-welch-2015</p>
]]></description>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/10262/research-fellow-phd-candidate-in-computational-biology-%E2%80%93-2-positions</guid>
  <pubDate>Fri, 25 Apr 2014 20:19:58 -0500</pubDate>
  <link></link>
  <title><![CDATA[Research fellow (PhD candidate) in computational biology – 2 positions]]></title>
  <description><![CDATA[
<p>At the Department of Informatics two 4-year positions as research fellow are available in the field of computational biology connected to the Computational Biology Unit. The positions are linked to the project “Integrated genomics - linking transcriptional and translational regulation over developmental time” supported by the Bergen Research Foundation</p>

<p>The fate of a cell is ultimately the product of the regulation of its genes. Gene regulation is a coordinated process acting at multiple levels of which transcription and translation are the most prominent. The Valen group is dedicated to the fundamental question of how transcription and translation is integrated to obtain the desired protein abundance. The recent development of high-throughput next generation sequencing techniques to monitor both active translation and transcription has made it possible to study this connection at the genome scale.</p>

<p>This project aims to elucidate the links between regulation of translation and transcription. The applicant will analyze next generation sequencing data and model gene regulation on a genome-wide level to identify the features that affect the translational output of transcripts. The work will be done in close collaboration with experimental scientists who will test the predictions of the computational models.</p>

<p>Additional information on the position can be obtained by contacting Eivind Valen (eivind.valen@ii.uib.no).</p>

<p>The research fellow must take part in the University’s approved PhD program leading to the degree within a time limit of 3 years. Application for admission to the PhD program, including a project plan outline for the training module, will be worked out in collaboration with the research group in question.</p>

<p>In total, the fellowship period is 4 years, 25 % of this will be allocated to teaching and/or administrative duties. The fellowship period may be reduced if the successful applicant has held previous employment as a research fellow or similar.</p>

<p>http://www.jobbnorge.no/en/available-jobs/job/102235/research-fellow-phd-candidate-in-computational-biology-2-positions</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/35106/alien-hunter-prediction-of-putative-horizontal-gene-transfer-hgt-events</guid>
	<pubDate>Sun, 07 Jan 2018 19:11:18 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/35106/alien-hunter-prediction-of-putative-horizontal-gene-transfer-hgt-events</link>
	<title><![CDATA[Alien_Hunter : prediction of putative Horizontal Gene Transfer (HGT) events]]></title>
	<description><![CDATA[<p>Alien_hunter is an application for the prediction of putative Horizontal Gene Transfer (HGT) events with the implementation of Interpolated Variable Order Motifs (IVOMs).</p>
<p>An IVOM approach exploits compositional biases using variable order motif distributions and captures more reliably the local composition of a sequence compared to fixed-order methods. Optionally the predictions can be parsed into a 2-state 2nd order Hidden Markov Model (HMM), in a change-point detection framework, to optimize the localization of the boundaries of the predicted regions. The predictions (embl format) can be automatically loaded into the freely available Artemis genome viewer.</p><p>Address of the bookmark: <a href="http://www.sanger.ac.uk/science/tools/alien-hunter" rel="nofollow">http://www.sanger.ac.uk/science/tools/alien-hunter</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37827/genomethreader-gene-prediction-software</guid>
	<pubDate>Wed, 03 Oct 2018 15:34:08 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37827/genomethreader-gene-prediction-software</link>
	<title><![CDATA[GenomeThreader: Gene Prediction Software]]></title>
	<description><![CDATA[<p><em>GenomeThreader</em><span>&nbsp;is a software tool to compute gene structure predictions. The gene structure predictions are calculated using a similarity-based approach where additional cDNA/EST and/or protein sequences are used to predict gene structures via spliced alignments.&nbsp;</span><em>GenomeThreader</em><span>&nbsp;was motivated by disabling limitations in&nbsp;</span><a href="http://bioinformatics.iastate.edu/cgi-bin/gs.cgi"><em>GeneSeqer</em></a><span>, a popular gene prediction program which is widely used for plant genome annotation.</span></p><p>Address of the bookmark: <a href="http://genomethreader.org/" rel="nofollow">http://genomethreader.org/</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43698/mimilook-a-phylogenetic-workflow-for-detection-of-gene-acquisition-in-major-orthologous-groups-of-megavirales</guid>
	<pubDate>Mon, 10 Jan 2022 06:32:22 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43698/mimilook-a-phylogenetic-workflow-for-detection-of-gene-acquisition-in-major-orthologous-groups-of-megavirales</link>
	<title><![CDATA[MimiLook: A Phylogenetic Workflow for Detection of Gene Acquisition in Major Orthologous Groups of Megavirales]]></title>
	<description><![CDATA[<p><span>This tool detects statistically validated events of gene acquisitions with the help of the T-REX algorithm by comparing individual gene tree with NCBI species tree. In between the steps, the workflow decides about handling paralogs, filtering outputs, identifying Megavirale specific OGs, detection of HGTs, along with retrieval of information about those OGs that are monophyletic with organisms from cellular domains of life.&nbsp;</span></p>
<p>https://www.readcube.com/articles/10.3390%2Fv9040072</p><p>Address of the bookmark: <a href="https://pubmed.ncbi.nlm.nih.gov/28387730/" rel="nofollow">https://pubmed.ncbi.nlm.nih.gov/28387730/</a></p>]]></description>
	<dc:creator>Abhi</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/45299/the-gene-detectives-how-a-new-computational-tool-is-helping-us-read-the-history-written-in-our-genes</guid>
	<pubDate>Thu, 10 Sep 2026 21:23:42 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/45299/the-gene-detectives-how-a-new-computational-tool-is-helping-us-read-the-history-written-in-our-genes</link>
	<title><![CDATA[The Gene Detectives: How a New Computational Tool Is Helping Us Read the History Written in Our Genes]]></title>
	<description><![CDATA[<p>Imagine opening an ancient family album with no names, dates, or captions. Some photographs are missing, others have been copied, and a few show people who look almost identical. Your challenge is to discover who is related to whom and reconstruct the family story. In evolutionary biology, scientists face a similar mystery when they study genes. Every genome contains clues about its past, but genes can be duplicated, lost, and changed over millions of years, making their history difficult to trace.</p><p>A recent study published in PLOS Computational Biology introduces REvolutionH-tl 2.0 (https://pypi.org/project/revolutionhtl/), a computational tool designed to help solve this mystery. The software analyzes protein sequences and identifies evolutionary relationships between genes. It can help researchers detect important events such as gene duplication, gene loss, and speciation, allowing them to reconstruct how genes evolved across different organisms.</p><p>What makes the tool especially interesting is its focus on both speed and interpretation. The researchers compared REvolutionH-tl 2.0 with several existing computational tools and reported that it achieved competitive accuracy while requiring less computational time in their tests. The tool also includes visualization features, helping researchers turn complicated genetic data into evolutionary stories that are easier to explore.</p><p>Genes are more than simple sequences of DNA; they are records of life&rsquo;s long history. Each surviving gene carries traces of the changes that shaped it. By bringing together computational analysis and visualization, REvolutionH-tl 2.0 acts like a detective, helping scientists uncover these hidden stories. Ultimately, tools like this can improve our understanding of how genomes evolved and how genes acquired the roles they perform today.</p><p>More at&nbsp;https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1013017</p>]]></description>
	<dc:creator>BioStar</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/35802/bioinformatics-tools-to-detect-horizontal-gene-transfer-hgt-in-genomes</guid>
	<pubDate>Fri, 02 Mar 2018 04:56:23 -0600</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/35802/bioinformatics-tools-to-detect-horizontal-gene-transfer-hgt-in-genomes</link>
	<title><![CDATA[Bioinformatics tools to detect horizontal gene transfer (HGT) in genomes]]></title>
	<description><![CDATA[<p>Horizontal gene transfer (HGT), the &ldquo;non-sexual movement of genetic material between two organisms&rdquo; , is relatively common in prokaryotes&nbsp;and single-celled eukaryotes, but a number of factors combine to make it far rarer in multicellular eukaryotes. In order for a eukaryotic species to gain a gene by HGT, foreign DNA must enter the host nucleus, integrate into the genome, and in more complex organisms it must enter the sequestered germline in order to be transmitted to offspring. Once there, it must not experience strong negative selection, despite potential for genetic incompatibility with the host genome and mismatch between the niche of the donor and the host. Over the longer term, foreign DNA may become &ldquo;domesticated&rdquo; in the recipient genome and provide novel function.</p><p>Following are the popular tool to detect HGT in genomes:</p><p><a href="http://www.trex.uqam.ca/index.php?action=hgt&amp;project=trex">T-REX</a>&nbsp;/&nbsp;<a href="http://www.trex.uqam.ca/download/hgt-detection_3.22.zip">3.22</a></p><p>HGT detection /&nbsp;download &amp; compile</p><p><a href="https://www.ncbi.nlm.nih.gov/pubmed/20525630">20525630</a></p><p>&nbsp;</p><p><a href="http://compbio.engr.uconn.edu/software/RANGER-DTL/">RANGER-DTL</a>&nbsp;/&nbsp;<a href="http://compbio.engr.uconn.edu/software/RANGER-DTL/Linux.zip">2.0</a></p><p>HGT detection /&nbsp;download binary</p><p><a href="https://www.ncbi.nlm.nih.gov/pubmed/22689773">22689773</a></p><p>&nbsp;</p><p><a href="https://bioinfocs.rice.edu/phylonet">PhyloNet</a>&nbsp;/&nbsp;<a href="https://bioinfocs.rice.edu/sites/g/files/bxs266/f/kcfinder/files/PhyloNet_3.6.1.jar">3.6.1</a></p><p>HGT detection /&nbsp;download binary</p><p><a href="https://www.ncbi.nlm.nih.gov/pubmed/18662388">18662388</a></p><p>&nbsp;</p><p><a href="https://www.cs.hmc.edu/~hadas/jane/index.html">Jane</a>&nbsp;/&nbsp;<a href="https://www.cs.hmc.edu/~hadas/jane/form.html">4.01</a></p><p>HGT detection /&nbsp;download binary (!license!)</p><p><a href="https://www.ncbi.nlm.nih.gov/pubmed/20181081">20181081</a></p><p>&nbsp;</p><p><a href="http://www.tree-puzzle.de/">TREE-PUZZLE</a>&nbsp;/&nbsp;<a href="http://www.tree-puzzle.de/tree-puzzle-5.3.rc16-linux.tar.gz">5.3.rc16</a></p><p>HGT detection /&nbsp;download &amp; compile</p><p><a href="https://www.ncbi.nlm.nih.gov/pubmed/11934758">11934758</a></p><p>&nbsp;</p><p><a href="http://www.sigmath.es.osaka-u.ac.jp/shimo-lab/prog/consel/">CONSEL</a>&nbsp;/&nbsp;<a href="http://www.sigmath.es.osaka-u.ac.jp/shimo-lab/prog/consel/pub/cnsls020.tgz">0.20</a></p><p>HGT detection /&nbsp;download</p><p><a href="https://www.ncbi.nlm.nih.gov/pubmed/11751242">11751242</a></p><p>&nbsp;</p><p><a href="http://darkhorse.ucsd.edu/">DarkHorse</a>&nbsp;/&nbsp;<a href="http://darkhorse.ucsd.edu/DarkHorse-1.5_rev170.tar.gz">1.5 rev170</a></p><p>HGT detection /&nbsp;download &amp; install</p><p><a href="https://www.ncbi.nlm.nih.gov/pubmed/17274820">17274820</a></p><p>&nbsp;</p><p><a href="https://github.com/DittmarLab/HGTector">HGTector</a>&nbsp;/&nbsp;<a href="https://github.com/DittmarLab/HGTector/archive/wgshgt.zip">0.2.1</a></p><p>HGT detection /&nbsp;git clone</p><p><a href="https://www.ncbi.nlm.nih.gov/pubmed/25159222">25159222</a></p><p>&nbsp;</p><p><a href="http://www5.esu.edu/cpsc/bioinfo/software/EGID/">EGID</a>&nbsp;/&nbsp;<a href="http://www5.esu.edu/cpsc/bioinfo/software/EGID/EGID_1.0.tar.gz">1.0</a></p><p>HGT detection /&nbsp;download</p><p><a href="https://www.ncbi.nlm.nih.gov/pubmed/22355228">22355228</a></p><p>&nbsp;</p><p><a href="http://exon.gatech.edu/GeneMark/">GeneMarkS</a>&nbsp;/&nbsp;<a href="http://exon.gatech.edu/GeneMark/license_download.cgi">4.30</a></p><p>HGT detection / download binary (!license!)</p><p><a href="https://www.ncbi.nlm.nih.gov/pubmed/9461475">9461475</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38752/hgtector-an-automated-method-facilitating-genome-wide-discovery-of-putative-horizontal-gene-transfers</guid>
	<pubDate>Mon, 21 Jan 2019 06:50:05 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38752/hgtector-an-automated-method-facilitating-genome-wide-discovery-of-putative-horizontal-gene-transfers</link>
	<title><![CDATA[HGTector: an automated method facilitating genome-wide discovery of putative horizontal gene transfers]]></title>
	<description><![CDATA[<p>A computational pipeline for genome-wide detection of putative horizontal gene transfer (HGT) events based on sequence homology search hit distribution statistics</p>
<p>Authors: Qiyun Zhu (<a href="mailto:qiyunzhu@gmail.com">qiyunzhu@gmail.com</a>), Katharina Dittmar (<a href="mailto:katharinad@gmail.com">katharinad@gmail.com</a>)</p>
<p>Affiliation: Department of Biological Sciences, University at Buffalo, State University of New York, Buffalo, USA</p>
<p>Zhu Q, Kosoy M, Dittmar K. HGTector: an automated method facilitating genome-wide discovery of putative horizontal gene transfers.&nbsp;<em style="font-size: 12.8px;">BMC Genomics</em>. 2014. 15:717.</p>
<p>Usage: Simply execute&nbsp;<span style="font-size: 12.8px;">perl HGTector.pl</span>, or, open&nbsp;<span style="font-size: 12.8px;">GUI.html</span>&nbsp;in a web browser to see a step-by-step wizard.</p>
<p>Download&nbsp;<a href="https://github.com/DittmarLab/HGTector/archive/0.2.2.zip">HGTector 0.2.2</a>.</p><p>Address of the bookmark: <a href="https://github.com/DittmarLab/HGTector" rel="nofollow">https://github.com/DittmarLab/HGTector</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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