<?xml version='1.0'?><rss version="2.0" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:georss="http://www.georss.org/georss" xmlns:atom="http://www.w3.org/2005/Atom" >
<channel>
	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/30216?offset=680</link>
	<atom:link href="https://bioinformaticsonline.com/related/30216?offset=680" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/10260/%E2%80%9Con%E2%80%9D-and-%E2%80%9Coff%E2%80%9D-the-neuron</guid>
	<pubDate>Fri, 25 Apr 2014 19:31:13 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/10260/%E2%80%9Con%E2%80%9D-and-%E2%80%9Coff%E2%80%9D-the-neuron</link>
	<title><![CDATA[“On” and “Off” the neuron !!!]]></title>
	<description><![CDATA[<p><span>Optogenetics is a recent innovation in neuroscience that gives researchers the ability to control the activity of neurons with light. With this powerful tool, researchers are teasing apart the biological basis of memory, behavior, and disease (see &ldquo;<a href="http://www.technologyreview.com/news/517226/scientists-make-mice-remember-things-that-didnt-happen/"><span>Scientists Make Mice &lsquo;Remember&rsquo; Things That Didn&rsquo;t Happen</span></a>&rdquo; and &ldquo;<a href="http://www.technologyreview.com/news/423254/an-on-off-switch-for-anxiety/"><span>An On-Off Switch for Anxiety</span></a>,&rdquo;). But for the first several years of this technology&rsquo;s existence, the proteins that scientists added to neurons to make them react to light were only good at activating neurons. That limited researchers&rsquo; ability to understand neuronal circuits, sets of interconnected neurons that are thought to control behavior and, when misfiring, to underlie many brain conditions. Problems can arise from any imbalance in circuit activity, whether too much or too little.&nbsp;</span></p><p><span>Now, two research groups have engineered new optogenetic proteins that can be used to efficiently silence neurons.&nbsp;<span><span>One of the two new proteins comes from the lab of<span>&nbsp;</span><a href="http://www.stanford.edu/group/dlab/about_pi.html" target="_blank">Karl Deisseroth</a>, a psychiatrist and neuroscientist at Stanford University who helped develop optogenetics as a research tool.&nbsp;His group&rsquo;s new &ldquo;off&rdquo; switch for neurons was created by changing 10 of the 333 amino acids in an existing optogenetic protein, which itself had been engineered by combining natural proteins from<span>&nbsp;</span></span></span><a href="http://genome.jgi-psf.org/Chlre3/Chlre3.home.html" target="_blank"><span>green algae</span></a><span><span>. That advance&nbsp;</span><span>&ldquo;creates a powerful tool that allows neuroscientists to apply a brake in any specific circuit with millisecond precision,&rdquo; said Thomas&nbsp;Insel, director of the National Institute of Mental Health, in a released statement.&nbsp;</span><a href="http://www.sciencemag.org/content/344/6182/409" target="_blank"><span>The other new silencing protein</span></a>, developed by scientists at the H</span><span>umboldt University of Berlin and collaborators, was created by changing amino acids in the same existing optogenetic protein.&nbsp;</span></span></p><p><span><span>Some researchers are also looking to optogenetics as a potential treatment for patients with a variety of conditions (see &ldquo;</span></span><span><a href="http://www.technologyreview.com/news/524771/for-mice-and-maybe-men-pain-is-gone-in-a-flash/"><span>For Mice, and Maybe Men, Pain Is Gone in a Flash</span></a><span><span>,&rdquo; and &ldquo;</span></span><a href="http://www.technologyreview.com/news/506981/flipping-on-the-lights-to-halt-seizures/"><span>Flipping on the Lights to Halt Seizures</span></a><span><span>&rdquo;) but there are huge challenges to overcome. The method requires genetic modification of cells to make them light-sensitive. It also requires implanted light sources for all but the shallowest of nerve endings. <br /></span></span></span></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/44371/steps-to-find-all-the-repeats-in-the-genome</guid>
	<pubDate>Thu, 31 Aug 2023 02:43:28 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/44371/steps-to-find-all-the-repeats-in-the-genome</link>
	<title><![CDATA[Steps to find all the repeats in the genome !]]></title>
	<description><![CDATA[<div><p>To find repeats in a genome from 2 to 9 length using a Perl script, you can use the RepeatMasker tool with the "--length" option<a href="https://mobilednajournal.biomedcentral.com/articles/10.1186/1759-8753-5-13" target="_blank">[0]</a>. Here's a step-by-step guide:</p></div><div><ol>
<li>Install RepeatMasker: First, you need to install RepeatMasker on your system. You can download it from the RepeatMasker website<a href="https://mobilednajournal.biomedcentral.com/articles/10.1186/1759-8753-5-13" target="_blank">[0]</a>.</li>
</ol></div><div><ol>
<li>Prepare the genome sequence: Make sure you have the genome sequence in a FASTA file format. Let's assume the file is named "genome.fasta".</li>
</ol><blockquote><p>./RepeatMasker -pa &lt;number_of_processors&gt; -nolow -norna -no_is -div &lt;divergence_value&gt; -lib RepeatMaskerLib.embl -gff -xsmall -small -poly -species &lt;species_name&gt; -dir &lt;output_directory&gt; -length &lt;min_length&gt;-&lt;max_length&gt; genome.fasta</p></blockquote><div><p>Replace the following placeholders with appropriate values:</p><ul>
<li><code>&lt;number_of_processors&gt;</code>: The number of processors/threads you want to use for parallel processing.</li>
<li><code>&lt;divergence_value&gt;</code>: The divergence value for the species you are analyzing. You can find divergence values for different species in the RepeatMasker documentation<a href="https://mobilednajournal.biomedcentral.com/articles/10.1186/1759-8753-5-13" target="_blank">[0]</a>.</li>
<li><code>&lt;species_name&gt;</code>: The name of the species you are analyzing.</li>
<li><code>&lt;output_directory&gt;</code>: The directory where you want the output files to be saved.</li>
<li><code>&lt;min_length&gt;</code>&nbsp;and&nbsp;<code>&lt;max_length&gt;</code>: The minimum and maximum lengths of the repeats you want to find (in this case, 2 and 9).</li>
</ul></div><div><ol>
<li>Analyze the output: RepeatMasker will generate several output files, including a .out file. You can parse this file to extract the information you need. There is a Perl tool called "one_code_to_find_them_all.pl" that can help you parse RepeatMasker output files<a href="https://mobilednajournal.biomedcentral.com/articles/10.1186/1759-8753-5-13" target="_blank">[0]</a>. You can download it from the source provided.</li>
</ol></div><div><ol>
<li>Use the provided Perl script: Once you have the "one_code_to_find_them_all.pl" script, you can run it to conveniently parse the RepeatMasker output files. Here's an example of how to use it:</li>
</ol><blockquote><p>perl one_code_to_find_them_all.pl --rm &lt;RepeatMasker_out_file&gt; --length &lt;length_file&gt;</p></blockquote></div><p>&nbsp;</p></div><div><div><p>Replace&nbsp;<code>&lt;RepeatMasker_out_file&gt;</code>&nbsp;with the path to your RepeatMasker .out file, and&nbsp;<code>&lt;length_file&gt;</code>&nbsp;with the path to a file containing the lengths of the reference elements.</p></div><div><p>This script will generate several output files, including .log.txt and .copynumber.csv, which contain quantitative information about the identified repeat elements.</p></div><div><p>Remember to adjust the parameters and options according to your specific needs and the characteristics of your genome.</p></div></div>]]></description>
	<dc:creator>Neel</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/10409/check-linux-server-configuration</guid>
	<pubDate>Tue, 06 May 2014 01:10:57 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/10409/check-linux-server-configuration</link>
	<title><![CDATA[Check Linux server configuration !!]]></title>
	<description><![CDATA[<p>Bioinformatician uses servers for computational analysis. Sometime we need to check the server details before running our programs or tools. Here I am showing some basic commands using them you can gather the system/server information.<br /><br />To check what version of Operating System is installed on the server you can use the following commands:-<br />&nbsp;=================================================================<br />1.cat /etc/issue<br />[root@localhost ~]# cat /etc/issue<br />Red Hat Enterprise Linux Server release 5.5 (Tikanga)<br />Kernel \r on an \m<br /><br />2.cat /etc/redhat-release<br />[root@localhost ~]# cat /etc/redhat-release<br />Red Hat Enterprise Linux Server release 5.5 (Tikanga)<br /><br /><br />3.lsb_release -a<br />[root@localhost ~]# lsb_release -a<br />LSB Version:&nbsp;&nbsp;&nbsp; :core-3.1-ia32:core-3.1-noarch:graphics-3.1-ia32:graphics-3.1-noarch<br />Distributor ID: RedHatEnterpriseServer<br />Description:&nbsp;&nbsp;&nbsp; Red Hat Enterprise Linux Server release 5.5 (Tikanga)<br />Release:&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 5.5<br />Codename:&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Tikanga<br /><br /><br /><br />To check whether the operating system is 32 or 64bit:-<br />================================<br /># uname -i<br />[root@localhost ~]# uname -i<br />i386<br />(i386 represents that server is having 32bit operating system)<br /><br />[root@localhost ~]# uname -i<br />x86_64<br />(x86_64 represents that server is having 64bit operating system)<br /><br />To see the processor/CPU information:-<br />=============================<br /># cat /proc/cpuinfo<br />[root@localhost ~] cat /proc/cpuinfo<br />processor&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; : 0<br />vendor_id&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; : GenuineIntel<br />cpu family&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; : 6<br />model&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; : 15<br />model name&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; : Intel(R) Xeon(R) CPU&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 5130&nbsp; @ 2.00GHz<br />stepping&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; : 6<br />cpu MHz&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; : 1995.087<br />cache size&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; : 4096 KB<br />physical id&nbsp;&nbsp;&nbsp;&nbsp; : 0<br />siblings&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; : 2<br />core id&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; : 0<br />cpu cores&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; : 2<br />apicid&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; : 0<br />fdiv_bug&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; : no<br />hlt_bug&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; : no<br />f00f_bug&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; : no<br />coma_bug&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; : no<br />fpu&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; : yes<br />fpu_exception&nbsp;&nbsp; : yes<br />cpuid level&nbsp;&nbsp;&nbsp;&nbsp; : 10<br />wp&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; : yes<br />flags&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; : fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush dts acpi mmx fxsr sse sse2 ss ht tm pbe nx lm constant_tsc pni monitor ds_cpl vmx tm2 ssse3 cx16 xtpr lahf_lm<br />bogomips&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; : 3990.17<br />(Here processor number 0 indicates that the system is having one process(processor number starts with zero))<br /><br /><br /><br /><br />To check memory information:-<br />===========================<br /># free -m<br />[root@localhost ~]# free -m<br />&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; total&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; used&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; free&nbsp;&nbsp;&nbsp;&nbsp; shared&nbsp;&nbsp;&nbsp; buffers&nbsp;&nbsp;&nbsp;&nbsp; cached<br />Mem:&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 5066&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 3513&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 1552&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 0&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 612&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 2319<br />-/+ buffers/cache:&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 582&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 4484<br />Swap:&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 1983&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 0&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 1983<br /><br /><br /><br /># cat /proc/meminfo<br />[root@localhost ~]# cat /proc/meminfo<br />MemTotal:&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 5187752 kB<br />MemFree:&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 1639300 kB<br />Buffers:&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 627024 kB<br />Cached:&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 2374944 kB<br />SwapCached:&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 0 kB<br />Active:&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 2458788 kB<br />Inactive:&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 920964 kB<br />HighTotal:&nbsp;&nbsp;&nbsp;&nbsp; 4325164 kB<br />HighFree:&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 1561936 kB<br />LowTotal:&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 862588 kB<br />LowFree:&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 77364 kB<br />SwapTotal:&nbsp;&nbsp;&nbsp;&nbsp; 2031608 kB<br />SwapFree:&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 2031608 kB<br />Dirty:&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 704 kB<br />Writeback:&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 0 kB<br />AnonPages:&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 377892 kB<br />Mapped:&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 35328 kB<br />Slab:&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 153036 kB<br />PageTables:&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 6316 kB<br />NFS_Unstable:&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 0 kB<br />Bounce:&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 0 kB<br />CommitLimit:&nbsp;&nbsp; 4625484 kB<br />Committed_AS:&nbsp;&nbsp; 977132 kB<br />VmallocTotal:&nbsp;&nbsp; 116728 kB<br />VmallocUsed:&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 4492 kB<br />VmallocChunk:&nbsp;&nbsp; 112124 kB<br />HugePages_Total:&nbsp;&nbsp;&nbsp;&nbsp; 0<br />HugePages_Free:&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 0<br />HugePages_Rsvd:&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 0<br />Hugepagesize:&nbsp;&nbsp;&nbsp;&nbsp; 2048 kB<br /><br /><br />To check the model and serial name of the server:-<br />=======================================<br />[root@localhost ~]#&nbsp; dmidecode | egrep -i "product name|Serial number"<br />Product Name: PowerEdge R710<br />Serial Number: AB8CDE1<br />&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; &nbsp;<br /><br />To check the host name:-<br />=====================<br />[root@localhost ~]# uname -n<br />localhost<br /><br />[root@localhost ~]# hostname<br />localhost<br /><br />To check the kernel version:-<br />========================<br />[root@localhost ~]# uname -r<br />2.6.18-238.9.1.el5PAE</p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
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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>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/10460/assistant-professor-at-jawaharlal-nehru-university-in-delhi</guid>
  <pubDate>Wed, 07 May 2014 00:29:22 -0500</pubDate>
  <link></link>
  <title><![CDATA[Assistant Professor at Jawaharlal Nehru University in Delhi]]></title>
  <description><![CDATA[
<p>Advt. No. RC/48/2014</p>

<p>SCHOOL OF COMPUTATIONAL AND INTEGRATIVE SCIENCES (SC&amp;IS)</p>

<p>ESSENTIAL QUALIFICATION : - M.Sc./M.Tech. in Physics/ Chemistry/ Biology/ Mathematics/ Statistics/ Bioinformatics/ Computational Biology. Ph.D. in the broad areas of Bioinformatics/ Computational Biology. Candidates must have demonstrated capabilities in terms of high impact research publications in either of the above mentioned areas.</p>

<p>Scale of Pay : - 15600-39100/- (PB-III) AGP Rs. 6000/-</p>

<p>For more details on Centre/School, Specializations etc. please visit JNU website www.jnu.ac.in or contact Section Officer, Room Nos. 131-132, Recruitment Cell, Administrative Block, JNU, New Delhi – 110067, Email: recruitmentjnu2013@gmail.com The last date for the receipt of application is 15 May, 2014.</p>

<p>http://www.jnu.ac.in/Career/</p>

<p>http://www.jnu.ac.in/Career/ADVTNo_RC_48_2014.pdf<br />Last Apply Date:</p>

<p>15 May 2014</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/44775/genomic-architecture-surrounding-the-fusion-site-of-human-chromosome-2</guid>
	<pubDate>Tue, 04 Mar 2025 12:26:29 -0600</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/44775/genomic-architecture-surrounding-the-fusion-site-of-human-chromosome-2</link>
	<title><![CDATA[Genomic architecture surrounding the fusion site of human chromosome 2]]></title>
	<description><![CDATA[<p>The article <strong>"Genomic Structure and Evolution of the Ancestral Chromosome Fusion Site in 2q13&ndash;2q14.1 and Paralogous Regions on Other Human Chromosomes (https://pmc.ncbi.nlm.nih.gov/articles/PMC187548/)"</strong> explores the genomic architecture surrounding the fusion site of human chromosome 2. This fusion event is a key evolutionary marker distinguishing humans from other great apes, as humans have 46 chromosomes while chimpanzees, gorillas, and orangutans possess 48. The fusion occurred through an end-to-end joining of two ancestral chromosomes, which remain separate in nonhuman primates.</p><h3><strong>Key Findings:</strong></h3><ol>
<li>
<p><strong>Chromosomal Fusion and Its Molecular Signature:</strong></p>
<ul>
<li>The fusion site is located at <strong>2q13&ndash;2q14.1</strong> and is characterized by <strong>degenerate telomeric sequences</strong> appearing interstitially, indicating the historical head-to-head joining of ancestral chromosomes.</li>
<li>Despite being a signature of a past fusion event, these telomeric repeats are no longer functional and have undergone sequence degradation over time.</li>
</ul>
</li>
<li>
<p><strong>Extensive Duplications in the Surrounding Genomic Region:</strong></p>
<ul>
<li>The study identifies <strong>large-scale segmental duplications</strong> flanking the fusion site, with several of these regions duplicated and scattered across multiple chromosomes.</li>
<li>These duplications are predominantly located in <strong>subtelomeric and pericentromeric regions</strong>, suggesting their role in genomic instability and chromosomal evolution.</li>
</ul>
</li>
<li>
<p><strong>Paralogous Regions and Their Evolutionary Relationships:</strong></p>
<ul>
<li>A <strong>168-kilobase (kb) segment</strong> near the fusion site has <strong>98%&ndash;99% sequence identity</strong> with three regions on <strong>chromosome 9 (9pter, 9p11.2, and 9q13)</strong>.</li>
<li>Another <strong>67-kb region distal to the fusion site</strong> shows a high degree of homology to sequences in <strong>chromosome 22qter</strong>.</li>
<li>Additionally, a <strong>100-kb segment</strong> exhibits <strong>96% sequence identity</strong> with a region in <strong>chromosome 2q11.2</strong>.</li>
</ul>
</li>
<li>
<p><strong>Comparative Genomics and Evolutionary Implications:</strong></p>
<ul>
<li>By comparing the duplicated sequences and their arrangement in primates, the researchers traced the order of duplication events leading to their present distribution.</li>
<li>The presence of specific repetitive elements within these duplicated segments serves as <strong>evolutionary markers</strong> that help infer their historical rearrangements.</li>
<li>Some of these <strong>duplicated regions are associated with chromosomal inversion breakpoints</strong>, potentially contributing to evolutionary changes in primates.</li>
<li>Recurrent <strong>structural rearrangements</strong> in these regions have been linked to human chromosomal disorders.</li>
</ul>
</li>
</ol><h3><strong>Conclusions and Implications:</strong></h3><ul>
<li>The findings provide valuable insights into <strong>the structural evolution of human chromosome 2</strong>, which played a crucial role in human speciation.</li>
<li>Understanding these <strong>segmental duplications</strong> and their evolutionary trajectories sheds light on <strong>genomic instability</strong>, which may contribute to <strong>human genetic diseases</strong>.</li>
<li>The study highlights how large-scale chromosomal rearrangements, such as fusion and duplication, have influenced the <strong>evolutionary divergence of humans</strong> from other primates.</li>
</ul><p>This research advances our understanding of <strong>human genome evolution</strong> and offers a foundation for studying the effects of <strong>structural variants in genetic disorders</strong>.</p>]]></description>
	<dc:creator>LEGE</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/videolist/watch/10749/memories-can-be-passed-down-through-dna</guid>
	<pubDate>Sat, 10 May 2014 21:24:10 -0500</pubDate>
	<link>https://bioinformaticsonline.com/videolist/watch/10749/memories-can-be-passed-down-through-dna</link>
	<title><![CDATA[Memories Can Be Passed Down Through DNA]]></title>
	<description><![CDATA[<iframe width="" height="" src="https://www.youtube-nocookie.com/embed/tbPwzII_g6o" frameborder="0" allowfullscreen></iframe>The premise of Assassin's Creed is the reliving of other people's memories stored inside DNA. Well scientists have found that in mice, it actually happens! Anthony is joined by special guest and our friend Tara Long from Hard Science to explain how this process works, and if it might apply to humans as well.

Read More: 
Parental olfactory experience influences behavior and neural structure in subsequent generations
http://www.nature.com/neuro/journal/vaop/ncurrent/abs/nn.3594.html
"Using olfactory molecular specificity, we examined the inheritance of parental traumatic exposure, a phenomenon that has been frequently observed, but not understood."

What Is Epigenetics?
http://www.sciencemag.org/content/330/6004/611
"The cells in a multicellular organism have nominally identical DNA sequences (and therefore the same genetic instruction sets), yet maintain different terminal phenotypes. This nongenetic cellular memory, which records developmental and environmental cues (and alternative cell states in unicellular organisms), is the basis of epi-(above)-genetics."

Epigenetics
http://en.wikipedia.org/wiki/Epigenetics

Watch More:
How to Change Your Genes
https://www.youtube.com/watch?v=B5DU9lgbsSE
TestTube Wild Card
http://testtube.com/dnews/dnews-231-how-too-many-screens-affect-our-brain?utm_source=YT&utm_medium=DNews&utm_campaign=DNWC
Is Sexiness Hereditary?
https://www.youtube.com/watch?v=z6STRCncvM8
____________________

DNews is dedicated to satisfying your curiosity and to bringing you mind-bending stories & perspectives you won't find anywhere else! New videos twice daily. 

Watch More DNews on TestTube http://testtube.com/dnews

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Discovery News http://discoverynews.com]]></description>
	
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	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/45267/when-thousands-of-bacterial-genomes-become-one-giant-map</guid>
	<pubDate>Thu, 27 Aug 2026 10:56:47 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/45267/when-thousands-of-bacterial-genomes-become-one-giant-map</link>
	<title><![CDATA[When Thousands of Bacterial Genomes Become One Giant Map]]></title>
	<description><![CDATA[<p>Imagine trying to understand a city by studying just one house.</p><p>You might learn a lot about that house&mdash;the rooms, the doors, the furniture&mdash;but you would miss the bigger story: the streets, the neighborhoods, and all the ways the city changes from one place to another.</p><p>Something similar happens when scientists study bacterial genomes one at a time.</p><p>Over the past decade, researchers have collected thousands of bacterial genomes. These genomes contain an enormous amount of information about how bacteria survive, adapt, and evolve. But comparing thousands of individual genomes can quickly become a computational maze.</p><p>That is where PANORAMA enters the story.</p><p>Developed by J&eacute;r&ocirc;me Arnoux and colleagues, PANORAMA is a computational tool designed to explore bacterial pangenomes&mdash;the complete collection of genetic possibilities found across a species or group of related organisms. Instead of looking at every genome as an isolated object, the approach represents their shared and variable genetic features as a graph.</p><p>Think of this graph as a giant subway map.</p><p>Some stations appear on almost every route. These represent genes that are highly conserved. Other stations appear only on certain routes, representing genes that some bacteria possess while others do not. By looking at the entire network, scientists can begin to see not just *what genes exist*, but how they are organized and how biological systems are distributed across populations.</p><p>The researchers put PANORAMA to the test using 941 genomes of Pseudomonas aeruginosa, a bacterium important in human health. They used the tool to investigate biological systems, including bacterial defense mechanisms against viruses known as bacteriophages. They then expanded the analysis to more than 6,000 genomes from four Enterobacteriaceae species.</p><p>The result is more than a faster way to process data.</p><p>PANORAMA allows researchers to ask a bigger question: What can an entire microbial species do, genetically speaking?</p><p>By comparing pangenomes, the researchers could identify systems shared between species as well as distinctive features. They could also find recurring genomic locations where genetic material is inserted&mdash;clues that may reveal common evolutionary processes.</p><p>And this is perhaps the most exciting part of the story.</p><p>Every bacterial genome is like a page in a huge evolutionary book. Until recently, reading thousands of those pages together was difficult. PANORAMA provides a way to turn those pages into a map, allowing scientists to see patterns that might disappear when each genome is studied separately.</p><p>The study, published in PLOS Computational Biology in July 2026, presents PANORAMA as a foundation for large-scale comparative pangenomics. The software and accompanying analysis resources are openly available, giving other researchers the opportunity to explore microbial diversity themselves.</p><p>So the story is not really about one bacterium or one genome.</p><p>It is about changing the way we look at life.</p><p>Instead of asking, &ldquo;What is inside this genome?&rdquo;, scientists can increasingly ask, &ldquo;What is the full genetic landscape of this species&mdash;and how did it become this way?&rdquo;</p><p>And sometimes, when you stop looking at one house and finally see the whole city, the most interesting discoveries are hiding in the streets between them.</p><p>Read more at&nbsp;https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1013856</p>]]></description>
	<dc:creator>LEGE</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/10773/bioinformatics-jrfsrf-position-at-national-research-centre-on-plant-biotechnology</guid>
  <pubDate>Sun, 11 May 2014 22:29:12 -0500</pubDate>
  <link></link>
  <title><![CDATA[Bioinformatics JRF/SRF position at NATIONAL RESEARCH CENTRE ON PLANT BIOTECHNOLOGY]]></title>
  <description><![CDATA[
<p>NATIONAL RESEARCH CENTRE ON PLANT BIOTECHNOLOGY<br />LBS, CENTRE, PUSA CAMPUS, IARI NEW DELHI<br />NEW DELHI – 110 012</p>

<p>WALK- IN –INTERVIEWS</p>

<p>Eligible candidates may appear in Walk-in-Interview on May 23, 2014 at 10 AM for the posts of Research Associates &amp; Senior Research Fellows (SRF) in the following DST/DBT/ICAR funded projects.</p>

<p>1 NPTC Project on Bioinformatics and Comparative Genomics</p>

<p>Research Associate (One)</p>

<p>Rs. 24000/- + 30% HRA for masters degree holder with more than 4 years experience</p>

<p>Essential: Ph D in Plant Molecular Biology &amp; Biotechnology/Genetics 0r Candidates who have already submitted their Ph D thesis in above subjects</p>

<p>Desirable: Research experience in Genomics, Molecular biology, Microarrays analysis, Gene cloning, transgenic Techniques , and computational analysis.</p>

<p>Senior Research Fellow ( UGCCSIR/ DBT/ ICAR Net qualified only): (One)</p>

<p>Rs. 16000/- + 30% HRA and Rs. 18000+30 HRA from 3rd year onwards</p>

<p>Essential:</p>

<p>1. ICAR/ UGCCSIR/DBT Net qualified only</p>

<p>2. M. Sc. (with thesis) in Biotechnology, Life Sciences, Biosciences/ Bioinformatics, Genetics/ Plant Pathology with experience in molecular biology.</p>

<p>Or M.Sc with more than 3 years research experiences</p>

<p>3. B.Sc. Agriculture or Biology</p>

<p>Desirable:<br />1. M. Sc. with thesis<br />2. Experience in molecular biology, plant tissue culture<br />3. Bioinformatics knowledge is important</p>

<p>2 DST JC Bose National Fellowship</p>

<p>Research Associate (Bioinformatics) : One</p>

<p>Rs.22000/- + 30% HRA for 1 &amp; 2nd Yr., Rs. 23000+ 30% HRA for 3rd year and Rs. 24000+30% HRA for 4th &amp;5th yr</p>

<p>Essential: M Ph D in Plant Molecular Biology &amp; Biotechnology/Genetics</p>

<p>Desirable: Research experience in Genomics, Molecular biology, Microarrays analysis, Gene cloning, transgenic Techniques , and computational analysis.</p>

<p>Age limit: Max.35 years (Age relaxation of 5 years for SC/ST &amp; women and 3 years for OBC)</p>

<p>The posts are purely temporary in nature and are co-terminus with the project. Initially the offer will be made for one year only and may be further extendable based on performance of the candidate. The interview will be held on May 23 , 2014 at 10:00 AM at NRCPB, LBS Building, Pusa Campus, IARI, New Delhi- 110012. The candidates must bring four copies of biodata (in the prescribed proforma), original certificates, attested photocopies of each of the certificates and an attested copy of recent passport size photograph. No. TA/DA would be given for the appearance in interview. Only the candidates having essential qualification would be entertained for the interviews. Short-listing of candidates based on academic merit and experience will be done in case of large number of applicants.</p>

<p>Advertisement: http://www.nrcpb.org/sites/default/files/Advertisement%20for%20RA%20and%20SRF%20Position.pdf</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/45303/the-tree-that-learned-to-read-genomes</guid>
	<pubDate>Fri, 11 Sep 2026 00:51:02 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/45303/the-tree-that-learned-to-read-genomes</link>
	<title><![CDATA[The Tree That Learned to Read Genomes]]></title>
	<description><![CDATA[<p>Imagine trying to reconstruct a family tree when many family photographs are missing, some names are unclear, and different relatives remember the past differently. This is similar to the challenge scientists face when trying to understand how organisms are related. Their family records are genomes, and the family tree is a phylogenetic tree. With modern sequencing technologies, scientists now have access to thousands of genomes, but comparing them can be difficult, especially when genomes are incomplete or poorly annotated.</p><p>A recent study by Webster and Chapman introduces Buscogeny (https://github.com/Jwebster89/Buscogeny), an open-source bioinformatics pipeline designed to make this process easier. The tool uses BUSCO (Benchmarking Universal Single-Copy Orthologs), which identifies conserved genes that are expected to occur as single copies in particular groups of organisms. These genes act like evolutionary landmarks, allowing researchers to compare genomes and investigate their relationships.</p><p>Buscogeny brings several steps of phylogenomic analysis into one workflow. It identifies BUSCO genes, extracts and aligns their sequences, removes unreliable regions, combines information from multiple genes, and uses the resulting data to construct a phylogenetic tree. It also provides quality-control information, helping researchers identify genomes that may be too incomplete for reliable analysis.</p><p>The authors demonstrate the usefulness of Buscogeny with bacterial and fungal genomes, including Alternaria. This is particularly valuable because fungal genomes can vary greatly in quality and annotation. Ultimately, Buscogeny helps transform massive amounts of genomic data into an understandable evolutionary story. Each DNA sequence becomes a clue, each conserved gene becomes a landmark, and together these clues reveal a picture of how life is connected.</p><p>More at&nbsp;https://link.springer.com/article/10.1007/s10123-025-00752-6?</p>]]></description>
	<dc:creator>BioStar</dc:creator>
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