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<channel>
	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/28915?offset=540</link>
	<atom:link href="https://bioinformaticsonline.com/related/28915?offset=540" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></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/news/view/20015/illumina-smartphone-chip</guid>
	<pubDate>Tue, 30 Dec 2014 23:19:54 -0600</pubDate>
	<link>https://bioinformaticsonline.com/news/view/20015/illumina-smartphone-chip</link>
	<title><![CDATA[Illumina Smartphone Chip !!!]]></title>
	<description><![CDATA[<p>Illumina, the company that claims it brought human genome sequencing down to $1000 prices, has now turned its attention to a consumer product - a chip that you can plug into your smartphone and have it read your genetic information.<br /><br />The biggest challenge ahead of Illumina is simplifying the process of genetic sequencing. Currently, Illumina&rsquo;s DNA sequencers are gigantic machines that use techinques like colorimetry to work, but while the core technology is computational, it takes some 30 steps to extract genetic data and run it through. This process will likely have to be hugely simplified on mobile devices, given the fact that some studies require extracting 10 mililiters of blood. Illumina researchers are also working on finding the optimal technology for this on-chip DNA sequencing - be it electrical, optical, or other.<br /><br />Illumina is one of the most prominent names in genetics, often said to be the Intel of genetic sequencing, as just like Intel it provides the algorithms, the processing brain that runs a DNA reading task.<br /><br />In other recent smartphone-related biotech news, drug company Pfizer launched its REMOTE project, a new type of clinical trial that does not require going to a hospital for checks - targeted at patients with overactive bladder problems, the FDA-approved REMOTE project allowed to gather data from patients from over 10 states remotely, via mobile devices.<br /><br /></p><p>This is indeed the Illumina answer to Apple's Health app, HealthBook, Google HealthFit.</p>]]></description>
	<dc:creator>Robert M Willioms</dc:creator>
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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/20449/walk-in-interview-for-the-post-of-jrf-and-project-assistant-cift</guid>
  <pubDate>Tue, 20 Jan 2015 23:03:20 -0600</pubDate>
  <link></link>
  <title><![CDATA[WALK-IN-INTERVIEW for the post of JRF and Project Assistant @ CIFT]]></title>
  <description><![CDATA[
<p>Eligible candidates are invited to attend a walk-in-Interview with all relevant documents for the following positions of Project Fellows (on contractual basis) to work in the Project “ Genetic Diversity of Clostridium botulinum in seafood and Development of Lateral Flow Immuno Assay (LFIA) for toxinotyping  funded by Department of Biotechnology.   The duration of the project is 3 years / co-terminus with the scheme.</p>

<p>Jr. Research Fellow – 2 posts</p>

<p>    Fellowship    :   Rs. 25000/- + 20% HRA pm  for Ist &amp; 2nd year and Rs.28000/- + HRA on 3rd year</p>

<p>    Qualification :    Ist class Masters Degree in Microbiology/Fishery Microbiology/Bio-technology.</p>

<p>    Desirable        :  </p>

<p>    1. CSIR/UGC NET/JRF qualified</p>

<p>    2. Excellent analytical skills and computer documentation</p>

<p>    3. Prior experience in handling microbial cultures and molecular techniques</p>

<p>Project Assistant – 1 post</p>

<p>Fellowship    :    Rs.8000/- p.m (consolidated)</p>

<p>Qualification:   Masters degree in Microbiology/Biotechnology with skill in Bioinformatics</p>

<p>Desirable:   Excellent analytical skills in Bioinformatics and computer documentation</p>

<p>Terms &amp; Conditions:</p>

<p>Registration will begin at 8.30 a.m and will close at 11.00 am<br />Age limit (as on 29.1.2015):  Below 35 years for men and 40 years for women.<br />Age relaxation of 3 year for OBC candidates and 5 years for SC/ST candidates is permissible.<br />Candidates are required to submit self-attested copies of all the Certificates in support of their claims    regarding age, educational qualifications, scheduled caste/scheduled tribe/OBC etc.  The original certificates shall be produced for verification before the interview.<br />Candidates should bring detailed bio-data (in the enclosed format)  affixing a recent passport size photograph.<br />The selected candidate will be recruited on contract basis under ICAR norms.  The post is purely temporary and is co-terminus with the project.<br />The candidates attending the interview should ensure that they fulfil all the eligibility conditions.  No correspondence will be entertained from the candidates for selection/test/appointment.<br />No TA/DA will be paid to attend the interview.<br />Canvassing in any form will render the candidate disqualified for the post.<br />The Director’s decision will be final and binding in all aspects regarding the selection to the post.</p>

<p>Venue: CIFT, Matsyapuri.P.O, Cochin                  Date of interview:  29.01.2015          Time:  10.00 am</p>

<p>http://www.cift.res.in/uploads/userfiles/file/file/srf%20appn.doc</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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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/20387/walk-in-interview-for-project-assistant-bharathidasan-university</guid>
  <pubDate>Mon, 12 Jan 2015 21:54:10 -0600</pubDate>
  <link></link>
  <title><![CDATA[WALK-IN-INTERVIEW FOR PROJECT ASSISTANT @ BHARATHIDASAN UNIVERSITY]]></title>
  <description><![CDATA[
<p>BHARATHIDASAN UNIVERSITY<br />DEPARTMENT OF BIOINFORMATICS, SCHOOL OF LIFE SCIENCES, TIRUCHIRAPPALLI – 620024</p>

<p>Project title: “Genome-scale metabolic modeling and simulation of rumen methanogens An in silico attempt to methane attenuation”</p>

<p>Funding Agency: University Grants Commission, New Delhi</p>

<p>Tenure of the project: Two years or till the end of the project period.</p>

<p>Position: Project Assistant (1 no.)</p>

<p>Essential qualification: First class M.Sc. in Bioinformatics/Microbiology/ Biotechnology and other related discipline.</p>

<p>Desirable qualification: Experience in an area relevant (Molecular Systems Engineering) to the project.</p>

<p>Fellowship: Rs. 5000 per month as per the UGC norms.</p>

<p>Upper age limit: 28 years</p>

<p>Date of Venue of interview: 22.01.2015, Department of Bioinformatics, School of Life Sciences, Bharathidasan University, Tiruchirappalli -620 024, Tamil Nadu</p>

<p>The above post is purely temporary and will be terminated with three month notice.</p>

<p>The Terms and the condition of the appointment shall be governed according to UGC, Govt. of India. The eligible candidates will bring their original certificates and documents at the time of interview. No TA/DA will be paid for attending the interview.</p>

<p>Dr. P. CHELLAPANDI<br />UGC-Research Awardee,<br />Department of Bioinformatics,<br />School of Life Sciences,<br />Bharathidasan University,<br />Tiruchirappalli -620 024, Tamil Nadu</p>

<p>Advertisement: www.bdu.ac.in/adv/PA_UGC_Bioinformatics.pdf</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/3868/next-generation-sequencing-ngs-tutorials</guid>
	<pubDate>Sat, 24 Aug 2013 06:01:37 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/3868/next-generation-sequencing-ngs-tutorials</link>
	<title><![CDATA[Next Generation Sequencing (NGS) Tutorials]]></title>
	<description><![CDATA[<p>Institute of computational biomedicine, Cornell University provide an NGS workshop tutorial at&nbsp;<a href="http://chagall.med.cornell.edu/NGScourse/">http://chagall.med.cornell.edu/NGScourse/</a>&nbsp;</p>
<p>You can also add your favourite NGS educational material, or workshop tutorial by commenting on this bookmarks for user benefit.&nbsp;</p>
<p>Understanding the basics of genome sequencing:</p>
<p>Tutorial by Luke Jostins.</p>
<p>http://www.genetic-inference.co.uk/blog/2009/04/basics-sequencing-dna-part-1/</p>
<p>http://www.genetic-inference.co.uk/blog/2009/08/basics-sequencing-dna-part-2/</p>
<p>A window into third-generation sequencing</p>
<p>http://hmg.oxfordjournals.org/content/19/R2/R227.full.pdf</p>
<p>==============================================</p>
<p>NGS data analysis pipelines</p>
<ul>
<li><strong>Detecting and annotating genetic variations using the HugeSeq pipeline</strong>&nbsp; DOI: <a href="http://dx.doi.org/10.1038/nbt.2134">10.1038/nbt.2134</a></li>
<li><strong> NARWHAL, a primary analysis pipeline for NGS data</strong> <a href="http://bioinformatics.oxfordjournals.org/cgi/content/abstract/28/2/284?etoc">http://bioinformatics.oxfordjournals.org/cgi/content/abstract/28/2/284?etoc</a></li>
<li><strong>RseqFlow: Workflows for RNA-Seq data analysis</strong>&nbsp; DOI: <a href="http://dx.doi.org/10.1093/bioinformatics/btr441">10.1093/bioinformatics/btr441</a></li>
<li><strong>ngs_backbone: a pipeline for read cleaning, mapping and SNP calling using Next Generation Sequence</strong>&nbsp;&nbsp;<a href="http://dx.doi.org/10.1186/1471-2164-12-285">10.1186/1471-2164-12-285</a></li>
<li><strong>A framework for variation discovery and genotyping using next-generation DNA sequencing data</strong>&nbsp; PubMed: <a href="http://www.ncbi.nlm.nih.gov/pubmed/21478889">21478889</a></li>
<li><strong>SNiPlay: a web-based tool for detection, management and analysis of SNPs. Application to grapevine diversity projects</strong>&nbsp; DOI: <a href="http://dx.doi.org/10.1186/1471-2105-12-134">10.1186/1471-2105-12-134</a> Abstract: <a href="http://www.biomedcentral.com/1471-2105/12/134/abstract">http://www.biomedcentral.com/1471-2105/12/134/abstract</a></li>
<li><strong>WEP: a high-performance analysis pipeline for whole-exome data&nbsp;</strong>http://www.biomedcentral.com/1471-2105/14/S7/S11</li>
<li><strong>DDBJ read annotation pipeline: a cloud computing-based pipeline for high-throughput analysis of next-generation sequencing data.&nbsp;</strong>http://www.ncbi.nlm.nih.gov/pubmed/23657089</li>
<li><strong>GATK: a Toolkit for Genome Analysis&nbsp;</strong>http://www.broadinstitute.org/gatk/</li>
<li><strong>Metagenomics</strong>:http://www.nbic.nl/education/nbic-phd-school/course-schedule/ngsmetagenomics/</li>
<li><strong>RNASeq</strong>:http://www.nbic.nl/education/nbic-phd-school/course-schedule/ngsrnaseq/</li>
<li><strong>Bioinformatics and Seq courses</strong>:&nbsp;http://www.isb-sib.ch/training/training-activities-schedule/archive-2013.html</li>
<li><strong>Variant Detection (Model organism) Advanced tutorial</strong> https://docs.google.com/document/pub?id=1CuKkKylVDb03tnN7RSWl5EUzleetn0ctjmvaidPKLxM</li>
<li><strong>Variant Detection Introductory tutorial</strong> https://docs.google.com/document/pub?id=1ZRzrjjOCvtAu3m-IKL-rbJ1f4On60dDL_IEwG7oejdI</li>
<li><strong>Microbial de novo Assembly for Illumina Data Introductory tutorial</strong> https://docs.google.com/document/pub?id=1N3AB9ptISUu4zULqe1kXpVF0BDyGb5f5yzxWSJd_WNM</li>
<li><strong>RNAseq Differential Gene Expression Introductory tutorial</strong> https://docs.google.com/document/pub?id=1KbTiBHtvHLfPRZ39AY3uriazrINA8TJzgjjwn1zPP7Y</li>
</ul>
<blockquote>
<p>" Please add your favourite NGS link below in comment section for the benefit of bioinformatics community ".&nbsp;</p>
</blockquote><p>Address of the bookmark: <a href="http://chagall.med.cornell.edu/NGScourse/" rel="nofollow">http://chagall.med.cornell.edu/NGScourse/</a></p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/20440/linux-operating-system-aimed-at-scientists</guid>
	<pubDate>Mon, 19 Jan 2015 08:30:49 -0600</pubDate>
	<link>https://bioinformaticsonline.com/news/view/20440/linux-operating-system-aimed-at-scientists</link>
	<title><![CDATA[Linux operating system aimed at scientists]]></title>
	<description><![CDATA[<p>The Bio-Linux operating system is based on Ubuntu 14.04 LTS (Trusty Tahr), and the previous version was using Ubuntu 12.04 LTS. The developers only use LTS releases and that means that upgrades for this distro don't come along all that often.<br /> <br /> This Linux distribution is aimed at scientists and it comes with more than 250 bioinformatics packages, 50 graphical applications and several hundred command line tools. And this is just skimming the surface of what the OS can do. Users have access to even more apps from the official repositories.</p><h3>Bio-Linux is using an Ubuntu LTS version as its base</h3><p>The fact that it uses Ubuntu LTS versions for the base is a good thing because it means its users won't have to worry about the support. Ubuntu 14.04 LTS is supported until 2019, so people who are using Bio-Linux shouldn't have a problem.<br /> <br /> "An updated Bio-Linux 8 version is now on the website in ISO and OVA versions. As usual, there is no need to download this version if you are an existing user. All updates to existing packages will be applied to your system through the update manager and new packages are all available via apt-get or Synaptic," reads the <a href="http://nebclists.nerc.ac.uk/pipermail/bio-linux-announce/2015-January/000020.html" target="_blank">announcement</a>.<br /> <br /> The changelog also states that a problem that was preventing the desktop to not start on VirtualBox has been fixed, the QIIME and Bowtie-Bio tools have been upgraded, the pandaseq paired end assembler has been added, and the beginners tutorial specific to Bio-Linux 8 has been improved.<br /> <br /> Check out the official announcement for a complete list of changes and updates. You can <a href="http://linux.softpedia.com/get/System/Operating-Systems/Linux-Distributions/Bio-Linux-45495.shtml" target="_blank"><strong>download Bio-Linux 8.0.5</strong></a> right now from Softpedia and give it a spin. It has the Unity desktop and now it runs very well in virtual environments.</p><p>Reference @ http://news.softpedia.com/news/Bioinformatics-Distro-Bio-Linux-8-0-5-Now-Available-for-Download-469867.shtml</p>]]></description>
	<dc:creator>Pranjali Yadav</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/23174/scaffolding-of-a-bacterial-genome-using-minion-nanopore-sequencing</guid>
	<pubDate>Tue, 07 Jul 2015 16:59:25 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/23174/scaffolding-of-a-bacterial-genome-using-minion-nanopore-sequencing</link>
	<title><![CDATA[Scaffolding of a bacterial genome using MinION nanopore sequencing]]></title>
	<description><![CDATA[<p><span>Second generation sequencing has revolutionized genomic studies. However, most genomes contain repeated DNA elements that are longer than the read lengths achievable with typical sequencers, so the genomic order of several generated contigs cannot be easily resolved. A new generation of sequencers offering substantially longer reads is emerging, notably the Pacific Biosciences (PacBio) RS II system and the MinION system, released in early 2014 by Oxford Nanopore Technologies through an early access program.</span></p><p>Address of the bookmark: <a href="http://www.nature.com/srep/2015/150707/srep11996/full/srep11996.html" rel="nofollow">http://www.nature.com/srep/2015/150707/srep11996/full/srep11996.html</a></p>]]></description>
	<dc:creator>Rahul Agarwal</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/videolist/watch/20585/dna-transcription-advanced</guid>
	<pubDate>Thu, 29 Jan 2015 05:31:42 -0600</pubDate>
	<link>https://bioinformaticsonline.com/videolist/watch/20585/dna-transcription-advanced</link>
	<title><![CDATA[DNA Transcription (Advanced)]]></title>
	<description><![CDATA[<iframe width="" height="" src="https://www.youtube-nocookie.com/embed/SMtWvDbfHLo" frameborder="0" allowfullscreen></iframe><p>Transcription is the process by which the information in DNA is copied into messenger RNA (mRNA) for protein production. Originally created for DNA Interactive ( http://www.dnai.org ). TRANSCRIPT: The Central Dogma of Molecular Biology: "DNA makes RNA makes protein" Here the process begins. Transcription factors assemble at a specific promoter region along the DNA. The length of DNA following the promoter is a gene and it contains the recipe for a protein. A mediator protein complex arrives carrying the enzyme RNA polymerase. It manoeuvres the RNA polymerase into place... inserting it with the help of other factors between the strands of the DNA double helix. The assembled collection of all these factors is referred to as the transcription initiation complex... and now it is ready to be activated. The initiation complex requires contact with activator proteins, which bind to specific sequences of DNA known as enhancer regions. These regions may be thousands of base pairs distant from the start of the gene. Contact between the activator proteins and the initiation-complex releases the copying mechanism. The RNA polymerase unzips a small portion of the DNA helix exposing the bases on each strand. Only one of the strands is copied. It acts as a template for the synthesis of an RNA molecule which is assembled one sub-unit at a time by matching the DNA letter code on the template strand. The sub-units can be seen here entering the enzyme through its intake hole and they are joined together to form the long messenger RNA chain snaking out of the top.</p>]]></description>
	
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