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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/44614?offset=50</link>
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<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/38551/gupta-lab</guid>
  <pubDate>Sat, 29 Dec 2018 13:18:31 -0600</pubDate>
  <link></link>
  <title><![CDATA[Gupta Lab]]></title>
  <description><![CDATA[
<p>Work include (i) understanding the evolutionary relationships among different prokaryotic and eukaryotic organisms; (ii) Understanding the cellular functions of these lineage-specific signature proteins as well as lineage-specific conserved inserts and deletions in important housekeeping proteins by genetic and biochemical studies; (iii) Development of novel diagnostic methods (PCR based and immunological) for identification of different groups of organisms based upon these signature proteins and conserved indels; (iv) The use of these lineage-specific probes with predicitive ability to identify/explore the presence of different groups of organisms in metagenomic sequences from various environments.</p>

<p>https://fhs.mcmaster.ca/gupta-lab/index.html</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42794/tmrca-calculator</guid>
	<pubDate>Wed, 03 Feb 2021 05:07:30 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42794/tmrca-calculator</link>
	<title><![CDATA[TMRCA Calculator]]></title>
	<description><![CDATA[<p><span>This program calculates the probability that two people have a certain number of generations between them, based on the standard&nbsp;</span><em>infinite alleles</em><span>&nbsp;formula of Walsh. It calculates both the probability of being at an exact number of generations back to the Most Recent Common Ancestor (MRCA) of a certain pair of people and the cumulative probability that the actual number of generations is less than a certain value. Note that the convention using generations is changed from an earlier version of this calculator which used "transmission events". It can list both result types in a table or graph. In either case the horizontal axis stops at the point where the cumulative probability reaches 95% or 10 generations, whichever is longer, or an absolute max of 50,000. Beyond 90% the calculation becomes inaccurate.</span></p>
<p>https://clandonaldusa.org/index.php/tmrca-calculator</p><p>Address of the bookmark: <a href="https://clandonaldusa.org/index.php/tmrca-calculator" rel="nofollow">https://clandonaldusa.org/index.php/tmrca-calculator</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43806/genomicus-genome-browser-that-enables-users-to-navigate-in-genomes-in-several-dimensions</guid>
	<pubDate>Mon, 28 Feb 2022 23:27:37 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43806/genomicus-genome-browser-that-enables-users-to-navigate-in-genomes-in-several-dimensions</link>
	<title><![CDATA[Genomicus: genome browser that enables users to navigate in genomes in several dimensions]]></title>
	<description><![CDATA[<p>Genomicus is a genome browser that enables users to navigate in genomes in several dimensions: linearly along chromosome axes, transversaly across different species, and chronologicaly along evolutionary time.</p>
<p>Once a query gene has been entered, it is displayed in its genomic context in parallel to the genomic context of all its orthologous and paralogous copies in all the other sequenced metazoan genomes. Moreover, Genomicus stores and displays the predicted ancestral genome structure in all the ancestral species within the phylogenetic range of interest.</p>
<p>All the data on extant species displayed in this browser are from&nbsp;<a href="http://www.ensembl.org/">Ensembl</a>.</p>
<p><br><strong>Summary statistics of Genomicus version 105.01:</strong><span>&nbsp;(view species tree in&nbsp;</span><a href="https://www.genomicus.bio.ens.psl.eu/genomicus-105.01/data/SpeciesTree.pdf">pdf</a><span>&nbsp;or&nbsp;</span><a href="https://www.genomicus.bio.ens.psl.eu/genomicus-105.01/data/SpeciesTree.nwk">newick</a><span>)</span><br><br></p>
<table id="introstats">
<tbody>
<tr><th>Number of extant species</th>
<td>200</td>
</tr>
<tr><th>Number of extant genes</th>
<td>4303993</td>
</tr>
<tr><th>&nbsp;</th></tr>
<tr><th>Number of ancestral species</th>
<td>196</td>
</tr>
<tr><th>Number of ancestral genes</th>
<td>4624213</td>
</tr>
<tr><th>Number of ancestral synteny blocks</th>
<td>83342<br><br></td>
</tr>
</tbody>
</table><p>Address of the bookmark: <a href="https://www.genomicus.bio.ens.psl.eu/genomicus-105.01/cgi-bin/search.pl" rel="nofollow">https://www.genomicus.bio.ens.psl.eu/genomicus-105.01/cgi-bin/search.pl</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/44773/genetic-basis-of-tail-loss-evolution</guid>
	<pubDate>Tue, 04 Mar 2025 12:12:36 -0600</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/44773/genetic-basis-of-tail-loss-evolution</link>
	<title><![CDATA[Genetic basis of tail-loss evolution]]></title>
	<description><![CDATA[<p>The paper <em>"On the genetic basis of tail-loss evolution in humans and apes (https://www.nature.com/articles/s41586-024-07095-8)"</em>, published in <em>Nature</em>, investigates the genetic mechanisms that led to the loss of tails in humans and apes. The study suggests that a specific genetic mutation, involving the insertion of an <em>Alu</em> element (a type of transposable DNA sequence), played a critical role in the evolutionary transition from tailed primates to tailless hominoids.</p><h3><strong>Key Findings of the Study:</strong></h3><ol>
<li>
<p><strong>Alu Insertion and Tail Loss:</strong><br /> The researchers discovered an <em>Alu</em>-mediated genetic change in a common ancestor of modern apes and humans. This change disrupted the normal function of a gene involved in tail development, leading to the suppression of tail formation.</p>
</li>
<li>
<p><strong>Gene Disruption Mechanism:</strong><br /> The <em>Alu</em> insertion was found within a regulatory region of the <em>TBXT</em> gene (also known as <em>T</em> or <em>Brachyury</em>), which is crucial for tail development in vertebrates. This insertion likely altered the gene's expression patterns, leading to tail reduction over evolutionary time.</p>
</li>
<li>
<p><strong>Functional Evidence from Model Organisms:</strong><br /> To test their hypothesis, the researchers introduced similar genetic modifications in mice. The modified mice exhibited shortened or absent tails, supporting the idea that the identified mutation played a role in tail loss in hominoids.</p>
</li>
<li>
<p><strong>Evolutionary Implications:</strong><br /> The findings suggest that small, random genomic changes&mdash;such as transposable element insertions&mdash;can have profound effects on body morphology. This study provides evidence that mobile DNA elements (like <em>Alu</em>) can drive major evolutionary transitions.</p>
</li>
<li>
<p><strong>Relevance to Human Evolution:</strong><br /> Understanding the genetic basis of tail loss helps in reconstructing the evolutionary history of hominins (the lineage that includes humans and our extinct relatives). It also sheds light on how genetic variations contribute to anatomical diversity among primates.</p>
</li>
</ol><h3><strong>Significance of the Study:</strong></h3><p>This research highlights the role of transposable elements in shaping evolutionary traits and provides a concrete genetic explanation for a defining characteristic of humans and great apes. It also demonstrates how mutations in regulatory regions of developmental genes can lead to significant anatomical changes.</p>]]></description>
	<dc:creator>LEGE</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/videolist/watch/14218/pimp-your-brain-bioinformatics</guid>
	<pubDate>Wed, 20 Aug 2014 22:09:21 -0500</pubDate>
	<link>https://bioinformaticsonline.com/videolist/watch/14218/pimp-your-brain-bioinformatics</link>
	<title><![CDATA[Pimp your brain: Bioinformatics]]></title>
	<description><![CDATA[<iframe width="" height="" src="https://www.youtube-nocookie.com/embed/KqelGy6Q8nE" frameborder="0" allowfullscreen></iframe>Jan Lisec from the Max Planck Institute of Molecular Plant Physiology explains, in this "pimp your brain" episode, what bioinformatics is and why bioinformatics is so important and indispensable for biological research.

In the video serial "Pimp your brain" scientists from the Max Planck Institute of Molecular Plant Physiology describe their research. More videos from the 'Pimp your brain' serial are available on www.youtube.com/playlist?list=PL-l9VItC9Gn2Ur2Xj6PTOAkjLUlVPbIOO

More videos are available on www.mpimp-golm.mpg.de]]></description>
	
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/32076/ngs-teaching-material</guid>
	<pubDate>Wed, 05 Apr 2017 04:29:06 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/32076/ngs-teaching-material</link>
	<title><![CDATA[NGS teaching material]]></title>
	<description><![CDATA[<p><span>High throughput sequencing (HTS) technologies are being applied to a wide range of important topics in biology. However, the analyses of non-model organisms, for which little previous sequence information is available, pose specific problems. This course addresses the specific strengths and weaknesses of alternative HTS technologies, the computational resources needed for HTS, and how to analyze non-model species using HTS. The course consists of a practical training module, HTS bioinformatics training, and lecturing/seminars of HTS approaches specifically targeting non-model organisms.</span></p><p>Address of the bookmark: <a href="http://marinetics.org/teaching/hts/Assembly.html" rel="nofollow">http://marinetics.org/teaching/hts/Assembly.html</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/36605/hello-python-world</guid>
	<pubDate>Mon, 14 May 2018 16:41:01 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/36605/hello-python-world</link>
	<title><![CDATA[Hello Python World !]]></title>
	<description><![CDATA[<p>As I mentioned earlier, I will keep on posting one Python script per day to introduce you to Python programming. Whether you are an experienced programmer or not, this tutorial is intended for everyone who wishes to learn the Python programming language.</p><p>Python is a very simple language, and has a very straightforward syntax. The simplest directive in Python is the "print" directive - it simply prints out a line (and also includes a newline).</p><p>Create a file Hello.py</p><blockquote><p>print("Hello, Python World !.")</p></blockquote><p>Run</p><p>python3 Hello.py</p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/42811/bioinformatics-in-africa-part-4-morocco</guid>
	<pubDate>Sat, 06 Feb 2021 13:31:24 -0600</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/42811/bioinformatics-in-africa-part-4-morocco</link>
	<title><![CDATA[Bioinformatics in Africa: Part 4 - Morocco]]></title>
	<description><![CDATA[<p>Bioinformatics, in the UFR in Artificial Intelligence and Bioinformatics, deals with the management, the analysis, the modelling and the visualization of biological databases. Since the size of the databases is often exponential, the traditional algorithms are not very effective when seeking for a good computational solution.</p><p>To take care of this issue, many ways are opened to the researchers&nbsp;to&nbsp;improve&nbsp;the&nbsp;quality&nbsp;of&nbsp;the&nbsp;algorithms:</p><p>1. Usage of new information processing methods like artificial neuronal networks, genetic algorithms,&nbsp;etc. 2. Usage&nbsp;of&nbsp;Data&nbsp;mining&nbsp;&nbsp;to&nbsp;explore&nbsp;biochemical&nbsp;databases,<br />3. Usage of Machine learning on the biological examples to solve, for example, the problem of classification&nbsp;in&nbsp;Bioinformatics.</p><p>UFR&nbsp;offers&nbsp;in&nbsp;addition&nbsp;a&nbsp;doctoral&nbsp;training&nbsp;in&nbsp;Computer&nbsp;Science&nbsp;and&nbsp;Bioinformatics.</p><p>Doctoral&nbsp;module&nbsp;which&nbsp;includes:&nbsp;a&nbsp;Dipl&ocirc;me&nbsp;des&nbsp;Etudes&nbsp;Sup&eacute;rieures&nbsp;Approfondies&nbsp;(DESA)&nbsp; of&nbsp;two&nbsp;years;&nbsp;and&nbsp;a&nbsp;doctorate&nbsp;studies&nbsp;program&nbsp;with&nbsp;a&nbsp;national&nbsp;Ph.D.&nbsp;certification. Three&nbsp;specializations&nbsp;constitute&nbsp;the&nbsp;teaching&nbsp;trunk&nbsp;of&nbsp;the&nbsp;ENSAT:&nbsp;Computer&nbsp;engineering,&nbsp;Telecom&nbsp; engineering,&nbsp;and&nbsp;electronic&nbsp;systems&nbsp;engineering.</p><p>Research&nbsp;Interest&nbsp;and&nbsp;Activities:</p><p>The&nbsp;following&nbsp;are&nbsp;the&nbsp;present&nbsp;areas&nbsp;of&nbsp;research&nbsp;interest:</p><p>1. Machine&nbsp;Learning&nbsp;and&nbsp;Profile&nbsp;Gene&nbsp;Expression&nbsp;of&nbsp;Cancer<br />2. Predicting&nbsp;Protein&nbsp;structure <br />3. Hidden&nbsp;Markov&nbsp;Models&nbsp;(HMMs)&nbsp;and&nbsp;multiple&nbsp;alignments <br />4. Transformational&nbsp;Grammar&nbsp;for&nbsp;sequence&nbsp;modelling <br />5. Physical&nbsp;Mapping:&nbsp;STSs <br />6. Evolutionary&nbsp;Computation&nbsp;applied&nbsp;to&nbsp;Genomic&nbsp;and&nbsp;Proteomic <br />7. Predicate&nbsp;Logic&nbsp;and&nbsp;Protein&nbsp;Structure</p><p>Web&nbsp;site&nbsp;and&nbsp;links:</p><p>http://www.ensat.ac.ma/udiab http://www.pasteur.fr/pasteur/international/annonce_coursBioinfoannonce06_casa.pdf</p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/43008/list-of-useful-machine-ai-learning-resources</guid>
	<pubDate>Tue, 30 Mar 2021 08:56:06 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/43008/list-of-useful-machine-ai-learning-resources</link>
	<title><![CDATA[List of useful machine / ai learning resources !]]></title>
	<description><![CDATA[<p>ML&nbsp;cheatsheet !</p><p>https://github.com/remicnrd/ml_cheatsheet</p><p>Visual AI / ML</p><p>https://setosa.io/ev/</p><p>Simple and efficient tools for predictive data analysis</p><p><span>https://scikit-learn.org/stable/</span></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43563/apache-server-setting</guid>
	<pubDate>Fri, 29 Oct 2021 04:29:51 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43563/apache-server-setting</link>
	<title><![CDATA[Apache server setting !]]></title>
	<description><![CDATA[<p>Apache is an open source web server that&rsquo;s available for Linux servers free of charge.</p>
<p>In this tutorial we&rsquo;ll be going through the steps of setting up an Apache server.</p>
<h3>What you&rsquo;ll learn</h3>
<ul>
<li>How to set up Apache</li>
<li>Some basic Apache configuration</li>
</ul><p>Address of the bookmark: <a href="https://ubuntu.com/tutorials/install-and-configure-apache#3-creating-your-own-website" rel="nofollow">https://ubuntu.com/tutorials/install-and-configure-apache#3-creating-your-own-website</a></p>]]></description>
	<dc:creator>Abhi</dc:creator>
</item>

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