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<channel>
	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/26629?offset=1350</link>
	<atom:link href="https://bioinformaticsonline.com/related/26629?offset=1350" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
	<item>
	<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>
	
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	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/43980/useful-link-to-teach-evolution</guid>
	<pubDate>Wed, 05 Oct 2022 18:29:30 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/43980/useful-link-to-teach-evolution</link>
	<title><![CDATA[Useful link to teach evolution !]]></title>
	<description><![CDATA[<pre>Mimicry and other resources
Mimicry games:
Great Heliconius game:
http://heliconius.org/evolving_butterflies/
(See also 
https://royalsocietypublishing.org/doi/10.1098/rspb.2020.0014)
Other one, a bit less friendly:
https://ccl.northwestern.edu/netlogo/models/Mimicry
Camouflage practical
https://alexis-catherine.github.io/publication/natural-selection-and-camouflage/
(NetLogo also has one: 
https://ccl.northwestern.edu/netlogo/models/BugHuntCamouflage)
Peppered moth game:
https://askabiologist.asu.edu/peppered-moths-game/play.html

General resources
The always popular Populus:
https://cbs.umn.edu/populus/overview
Drift &amp; Gene Flow 
https://cartwrig.ht/apps/genie/
(Cock van Oosterhout has a great ppt to lead students through this)
See also https://cartwrig.ht/apps/redlynx/
https://demonstrations.wolfram.com/ReplicatorMutatorDynamicsWithThreeStrategies/
NetLogo:
http://ccl.northwestern.edu/netlogo/models/index.cgi
Population Genetics:
https://www.radford.edu/~rsheehy/Gen_flash/popgen/
Evolution in general
https://evolution.berkeley.edu/evolibrary/home.php
Mitochondrial Eve:
https://projects.ncsu.edu/cals/gn/ex/mit-eve.html
Y chromosomes:
https://projects.ncsu.edu/cals/gn/ex/y-chrom.html
A professional online package from Michael Kasumovic:
https://arludo.com/
a compilation of resources:
https://planted.botany.org/index.php?P=Home
Finally, Donald Forsdyke has some great on-line videos explaining
evolutionary principles (occasionally in a fake Scottish accent):
http://post.queensu.ca/~forsdyke/videolectures.htm</pre>]]></description>
	<dc:creator>Abhi</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/44783/when-chromosomes-shift-understanding-chromosome-rearrangement-and-human-disease</guid>
	<pubDate>Fri, 11 Apr 2025 01:07:17 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/44783/when-chromosomes-shift-understanding-chromosome-rearrangement-and-human-disease</link>
	<title><![CDATA[When Chromosomes Shift: Understanding Chromosome Rearrangement and Human Disease]]></title>
	<description><![CDATA[<p>In the vast and complex world of genetics, our chromosomes are like carefully arranged bookshelves &mdash; each holding critical information that defines who we are. But what happens when those books are shuffled, inverted, or swapped? The answer lies in a phenomenon known as <strong>chromosome rearrangement</strong>, a powerful force behind many human diseases, from developmental disorders to cancer.</p><h2>What Are Chromosome Rearrangements?</h2><p><strong>Chromosome rearrangements</strong> are structural changes that alter the normal configuration of chromosomes. These changes can involve large segments of DNA &mdash; from thousands to millions of base pairs &mdash; and can occur <strong>spontaneously</strong>, be <strong>inherited</strong>, or result from <strong>exposure to mutagens</strong> (like radiation or chemicals).</p><h3>Common Types of Rearrangements:</h3><ol>
<li>
<p><strong>Deletions</strong> &ndash; Loss of a chromosome segment</p>
</li>
<li>
<p><strong>Duplications</strong> &ndash; Repetition of a segment</p>
</li>
<li>
<p><strong>Inversions</strong> &ndash; A segment breaks off, flips, and reattaches</p>
</li>
<li>
<p><strong>Translocations</strong> &ndash; Segments exchange places between non-homologous chromosomes</p>
</li>
<li>
<p><strong>Insertions</strong> &ndash; A segment is inserted into another part of the genome</p>
</li>
</ol><p>These changes can disrupt genes directly or affect gene regulation, leading to disease.</p><h2>How Do Chromosome Rearrangements Cause Disease?</h2><p>The impact of a rearrangement depends on <strong>which genes are involved</strong>, <strong>how much DNA is affected</strong>, and <strong>when the rearrangement occurs</strong> (in development vs. adulthood). Here are some key mechanisms:</p><ul>
<li>
<p><strong>Gene disruption</strong>: Breaking a gene can lead to loss of function or the creation of a non-functional protein.</p>
</li>
<li>
<p><strong>Gene fusion</strong>: Joining parts of two genes may form a novel hybrid gene with new functions (common in cancer).</p>
</li>
<li>
<p><strong>Dosage effects</strong>: Extra or missing gene copies can disturb the balance of gene expression.</p>
</li>
<li>
<p><strong>Position effects</strong>: Moving a gene to a new regulatory environment may silence or over-activate it.</p>
</li>
</ul><h2>Chromosome Rearrangements in Human Disease</h2><h3>1. <strong>Developmental Disorders</strong></h3><ul>
<li>
<p><strong>Cri-du-chat syndrome</strong>: Caused by a deletion on chromosome 5p. Affected infants often have a high-pitched cry and intellectual disability.</p>
</li>
<li>
<p><strong>Williams syndrome</strong>: Results from a microdeletion on chromosome 7q, affecting genes related to cardiovascular and cognitive function.</p>
</li>
</ul><h3>2. <strong>Cancer</strong></h3><p>Cancer is perhaps the most striking example of disease caused by chromosome rearrangements.</p><ul>
<li>
<p><strong>Chronic Myeloid Leukemia (CML)</strong>: Caused by a translocation between chromosomes 9 and 22, forming the <em>Philadelphia chromosome</em>. This creates the <strong>BCR-ABL fusion gene</strong>, which drives uncontrolled cell growth.</p>
</li>
<li>
<p><strong>Burkitt lymphoma</strong>: Involves translocation of the <strong>MYC</strong> gene, leading to excessive cell division.</p>
</li>
<li>
<p><strong>Ewing sarcoma</strong>: A fusion of EWSR1 and FLI1 genes through translocation promotes tumor development.</p>
</li>
</ul><h3>3. <strong>Infertility and Miscarriages</strong></h3><p>Balanced rearrangements (like inversions or translocations) in carriers may not cause disease directly but can result in:</p><ul>
<li>
<p><strong>Recurrent miscarriages</strong></p>
</li>
<li>
<p><strong>Infertility</strong></p>
</li>
<li>
<p><strong>Birth defects in offspring</strong></p>
</li>
</ul><h2>Detecting Rearrangements</h2><p>Thanks to modern genomics, chromosome rearrangements can now be detected with high precision using:</p><ul>
<li>
<p><strong>Karyotyping</strong> &ndash; Classic method for detecting large rearrangements</p>
</li>
<li>
<p><strong>FISH (Fluorescence In Situ Hybridization)</strong> &ndash; Uses fluorescent probes to target specific DNA sequences</p>
</li>
<li>
<p><strong>Array CGH (Comparative Genomic Hybridization)</strong> &ndash; Detects copy number changes across the genome</p>
</li>
<li>
<p><strong>Whole Genome Sequencing (WGS)</strong> &ndash; Identifies even small or complex rearrangements at base-pair resolution</p>
</li>
</ul><h2>Looking Forward: The Future of Chromosome Medicine</h2><p>Understanding chromosome rearrangements is now central to:</p><ul>
<li>
<p><strong>Personalized medicine</strong></p>
</li>
<li>
<p><strong>Genetic counseling</strong></p>
</li>
<li>
<p><strong>Targeted therapies</strong>, especially in cancer (e.g., tyrosine kinase inhibitors for BCR-ABL fusion)</p>
</li>
</ul><p>With the rise of long-read sequencing and single-cell genomics, even previously &ldquo;invisible&rdquo; rearrangements are being uncovered, offering new insights into both rare diseases and common conditions.</p><h2>Final Thoughts</h2><p>Chromosome rearrangements remind us that genetics isn't just about which genes we have &mdash; but where they are, how they're arranged, and when they're active. As our tools grow sharper, so does our ability to diagnose, understand, and treat diseases rooted in genomic architecture.</p><p>In a way, the genome is like a book not just defined by its words, but also by how the chapters are ordered. Rearranging them can create a new story &mdash; sometimes harmful, sometimes insightful &mdash; and understanding these changes is key to writing a healthier future.</p>]]></description>
	<dc:creator>BioStar</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/34146/phylogenetic-molecular-genetics-terms-and-definitions</guid>
	<pubDate>Tue, 08 Aug 2017 08:20:31 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/34146/phylogenetic-molecular-genetics-terms-and-definitions</link>
	<title><![CDATA[Phylogenetic &amp; Molecular Genetics Terms and Definitions]]></title>
	<description><![CDATA[<p><strong>analog </strong>-- A feature that appears similar in two taxa which have originated from two different ancestors.</p><p><strong>ancestor</strong> -- Any organism, population, or species from which some other organism, population, or species is descended by reproduction.</p><p><strong>apomorphy </strong>-- specialized (=derived) characters of an organism.</p><p><strong>basal group</strong> -- The earliest diverging group within a clade; for instance, to hypothesize that sponges are basal animals is to suggest that the lineage(s) leading to sponges diverged from the lineage that gave rise to all other animals.</p><p><strong>biological classification </strong>-- The orderly arrangement of organisms in hierarchical system that ideally reflects evolutionary history.</p><p><strong>cDNA</strong> -- Complementary DNA; DNA that is synthesized, by reverse transcriptase, from a Messenger RNA template ( Messenger RNA contains the coded information for protein synthesis).</p><p><strong>character</strong> -- Heritable trait possessed by an organism.</p><p><strong>character state</strong> -- characters are usually described in terms of their states, for example: "hair present" vs. "hair absent," where "hair" is the character, and "present" and "absent" are its states.</p><p><strong>clade</strong> -- A monophyletic taxon; a group of organisms which includes the most recent common ancestor of all of its members and all of the descendants of that most recent common ancestor. From the Greek word "klados", meaning branch or twig.</p><p><strong>cladogenesis</strong> -- The development of a new clade; the splitting of a single lineage into two distinct lineages; speciation.</p><p><strong>cladogram</strong> -- A diagram, resulting from a cladistic analysis, which depicts a hypothetical branching sequence of lineages leading to the taxa under consideration. The points of branching within a cladogram are called nodes. All taxa occur at the endpoints of the cladogram.</p><p><strong>convergence</strong> -- Similarities which have arisen independently in two or more organisms that are not closely related. Contrast with homology.&nbsp;</p><p><strong>crown group</strong> -- All the taxa descended from a major cladogenesis event, recognized by possessing the clade's synapomorphy. See: stem group.</p><p><strong>derived</strong> -- Describes a character state that is present in one or more subclades, but not all, of a clade under consideration. A derived character state is inferred to be a modified version of the primitive condition of that character, and to have arisen later in the evolution of the clade. For example, "presence of hair" is a primitive character state for all mammals, whereas the "hairlessness" of whales is a derived state for one subclade within the Mammalia.</p><p><strong>diversity</strong> -- Term used to describe numbers of taxa, or variation in morphology.&nbsp;</p><p><strong>evolution</strong> -- Darwin's definition: descent with modification. The term has been variously used and abused since Darwin to include everything from the origin of man to the origin of life.</p><p><strong>evolutionary tree</strong> -- A diagram which depicts the hypothetical phylogeny of the taxa under consideration. The points at which lineages split represent ancestor taxa to the descendant taxa appearing at the terminal points of the cladogram.</p><p><strong>expressed sequence tag (EST)</strong> -- A partial coding sequence isolated at random from a cDNA library, used for identification and mapping of coding sequences, for discovery of new genes and (by reference to sequence data banks) for discovery of identities with other genes.</p><p><strong>extinction</strong> -- When all the members of a clade or taxon die, the group is said to be extinct.</p><p><strong>genetic marker -- </strong>A DNA sequence that can be recognized and thus used to characterize the larger DNA sequence and the chromosome in which it occurs.&nbsp;</p><p><strong>homolog </strong>-- A feature that appears similar in two or more taxa with a common ancestor that also possessed that feature.</p><p><strong>homology</strong> -- Two structures are considered homologous when they are inherited from a common ancestor which possessed the structure. This may be difficult to determine when the structure has been modified through descent.</p><p><strong>hypothesis</strong> -- A concept or idea that can be falsified by various scientific methods.</p><p><strong>ingroup</strong> -- In a cladistic analysis, the set of taxa which are hypothesized to be more closely related to each other than any are to the outgroup.</p><p><strong>lineage</strong> -- Any continuous line of descent; any series of organisms connected by reproduction by parent of offspring.</p><p><strong>monophyletic</strong> -- Term applied to a group of organisms which includes the most recent common ancestor of all of its members and all of the descendants of that most recent common ancestor. A monophyletic group is called a clade.</p><p><strong>outgroup</strong> -- In a cladistic analysis, any taxon used to help resolve the polarity of characters, and which is hypothesized to be less closely related to each of the taxa under consideration than any are to each other.</p><p><strong>paraphyletic</strong> -- Term applied to a group of organisms which includes the most recent common ancestor of all of its members, but not all of the descendants of that most recent common ancestor.</p><p><strong>parsimony</strong> -- Refers to a rule used to choose among possible cladograms, which states that the cladogram implying the least number of changes in character states is the best.</p><p><strong>phylogenetics</strong> -- Field of biology that deals with the relationships between organisms. It includes the discovery of these relationships, and the study of the causes behind this pattern.</p><p><strong>phylogeny</strong> -- The evolutionary relationships among organisms; the patterns of lineage branching produced by the true evolutionary history of the organisms being considered.</p><p><strong>plesiomorphy</strong> -- A primitive character state for the taxa under consideration.</p><p><strong>polarity of characters</strong> -- The states of characters used in a cladistic analysis, either original or derived. Original characters are those acquired by an ancestor deeper in the phylogeny than the most recent common ancestor of the taxa under consideration. Derived characters are those acquired by the most recent common ancestor of the taxa under consideration.</p><p><strong>polyphyletic</strong> -- Term applied to a group of organisms which does not include the most recent common ancestor of those organisms; the ancestor does not possess the character shared by members of the group.</p><p><strong>primitive</strong> -- Describes a character state that is present in the common ancestor of a clade. A primitive character state is inferred to be the original condition of that character within the clade under consideration. For example, "presence of hair" is a primitive character state for all mammals, whereas the "hairlessness" of whales is a derived state for one subclade within the Mammalia.</p><p><strong>radiation</strong> -- Event of rapid cladogenesis, believed to occur under conditions where a new feature permits a lineage to move into a new niche or new habitat, and is then called an adaptive radiation.</p><p><strong>rank</strong> -- In traditional taxonomy, taxa are ranked according to their level of inclusiveness. Thus a genus contains one or more species, a family includes one or more genera, and so on.</p><p><strong>relatedness</strong> -- Two clades are more closely related when they share a more recent common ancestor between them than they do with any other clade.</p><p><strong>repetitive DNA</strong> -- Sequences of DNA that are found to be repeated, sometimes thousands of times over.&nbsp;&nbsp;</p><p><strong>reticulation</strong> -- Joining of separate lineages on a phylogenetic tree, generally through hybridization or through lateral gene transfer. Fairly common in certain land plant clades; reticulation is thought to be rare among metazoans.</p><p><strong>selection</strong> -- Process which favors one feature of organisms in a population over another feature found in the population. This occurs through differential reproduction -- those with the favored feature produce more offspring than those with the other feature, such that they become a greater percentage of the population in the next generation.</p><p><strong>sister group</strong> -- The two clades resulting from the splitting of a single lineage.</p><p><strong>stem group</strong> -- All the taxa in a clade preceding a major cladogenesis event. They are often difficult to recognize because they may not possess synapomorpies found in the crown group.</p><p><strong>sympleisiomorphy</strong> &ndash; A ancestral character shared by the taxa under consideration</p><p><strong>synapomorphy</strong> -- A character which is derived, and because it is shared by the taxa under consideration, is used to infer common ancestry (shared derived state).</p><p><strong>synteny</strong> -- Portions of chromosomes in which gene order is conserved.&nbsp;</p><p><strong>systematics</strong> -- Field of biology that deals with the diversity of life. Systematics is usually divided into the two areas of phylogenetics and taxonomy.</p><p><strong>taxon</strong> -- Any named group of organisms, not necessarily a clade</p><p><strong>taxonomy</strong> -- The science of naming and classifying organisms.&nbsp;</p>]]></description>
	<dc:creator>Poonam Mahapatra</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/13477/research-associate-at-indian-institute-of-chemical-technology-iict-hyderabad</guid>
  <pubDate>Thu, 07 Aug 2014 01:55:21 -0500</pubDate>
  <link></link>
  <title><![CDATA[Research Associate at Indian Institute of Chemical Technology (IICT), Hyderabad]]></title>
  <description><![CDATA[
<p>Indian Institute of Chemical Technology (IICT), Hyderabad, a constituent of CSIR is a leading research Institute in the area of chemical sciences. The core strength of IICT lies in Organic Chemistry, and it continues to excel in this field for over six decades. The research efforts during these years have resulted in the development of several innovative processes for a variety of products necessary for human welfare such as drugs, agrochemicals, food, organic intermediates, adhesives etc. More than 150 technologies developed by IICT are now in commercial production.</p>

<p>CSIR-IICT is conducting Walk in Interview for the following position on a purely temporary basis for the sponsored project "GENESIS (BSC-0121) at 10.00 AM on 19th August 2014 at IICT, Hyderabad</p>

<p>    Position : Research Associate<br />    No of Post : One<br />    Desired Profile : PhD in computation biology or M.Tech in Computational Biology with three years experience in relevant subject and atleast one research paper in SCI journal</p>

<p>    Experience : Knowledge in vector and vector borne disease, disease modeling, GIS mapping and modeling.<br />    Age : 35 years<br />    Stipend : Rs 22000/- + HRA</p>

<p>Eligible candidate may download the application form from our website http://www.iictindia.org and appear for interview along with the duly filled in application form supported by bio-data and one set of attested photo copies of certificates of educational qualification, age, experience, caste, latest photograph and the cadndidates are required to bring all the original certificates for verification</p>

<p>Walk in Interview : 19.08.14</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/9695/learn-genetics-online</guid>
	<pubDate>Wed, 09 Apr 2014 19:12:42 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/9695/learn-genetics-online</link>
	<title><![CDATA[Learn Genetics Online]]></title>
	<description><![CDATA[<p>Great source to learn genetics and other relevant stuffs online.</p><p>Address of the bookmark: <a href="http://learn.genetics.utah.edu/" rel="nofollow">http://learn.genetics.utah.edu/</a></p>]]></description>
	<dc:creator>Rahul Agarwal</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/videolist/watch/3918/the-human-genome-project-video-3d-animation-introduction-low</guid>
	<pubDate>Sat, 24 Aug 2013 19:01:19 -0500</pubDate>
	<link>https://bioinformaticsonline.com/videolist/watch/3918/the-human-genome-project-video-3d-animation-introduction-low</link>
	<title><![CDATA[The Human Genome Project Video   3D Animation Introduction Low)]]></title>
	<description><![CDATA[<iframe width="" height="" src="https://www.youtube-nocookie.com/embed/YxoQFSBwyms" frameborder="0" allowfullscreen></iframe>]]></description>
	
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	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/21150/webinar-on-an-integrated-rna-and-dna-approach-to-unravel-genetic-regulation-in-cancer</guid>
	<pubDate>Wed, 11 Feb 2015 04:59:57 -0600</pubDate>
	<link>https://bioinformaticsonline.com/news/view/21150/webinar-on-an-integrated-rna-and-dna-approach-to-unravel-genetic-regulation-in-cancer</link>
	<title><![CDATA[Webinar on 'An integrated RNA and DNA approach to unravel genetic regulation in cancer']]></title>
	<description><![CDATA[<div><p><strong>Webinar on 'An integrated RNA and DNA approach to unravel genetic regulation in cancer'</strong></p><p><strong>Abstract</strong></p><p>Whole exome DNA sequencing (WES) or whole genome DNA sequencing (WGS) allows detection of mutations and polymorphisms in all exonic and genomic regions, respectively, while messenger RNA sequencing (RNA-Seq) enables quantitative analysis of gene expression. Mutations in the genome result in diverse transcriptional aberrations that can be missed in a stand-alone WES/WGS analysis. An integration of DNA variant analysis and RNA-Seq analysis enables one to investigate the consequences of genomic changes in the RNA transcripts including germline and somatic changes, imprinting, RNA editing and allele specific expression (ASE). In this webinar, we will demonstrate this integrated approach using Strand NGS to identify high confidence mutations, RNA editing events and ASE in cancer.</p><p><strong>Webinar Details</strong></p><table width="100%" border="1" cellspacing="0" cellpadding="0">
<tbody>
<tr>
<td valign="top">
<p style="text-align: center;"><br /> <strong>Sessions</strong></p>
</td>
<td valign="top">
<p style="text-align: center;"><a href="http://www.strand-ngs.com/webinar_registration"><strong>San Francisco Time<br /> (PST)</strong></a></p>
</td>
<td valign="top">
<p style="text-align: center;"><a href="http://www.strand-ngs.com/webinar_registration"><strong>Tokyo Time<br /> (GMT+09:00)</strong></a></p>
</td>
<td valign="top">
<p style="text-align: center;"><a href="http://www.strand-ngs.com/webinar_registration"><strong>Berlin Time<br /> (GMT+01:00)</strong></a></p>
</td>
<td valign="top">
<p style="text-align: center;"><a href="http://www.strand-ngs.com/webinar_registration"><strong>Mumbai Time<br /> (GMT+05:30)</strong></a></p>
</td>
</tr>
<tr>
<td>
<p style="text-align: center;"><a href="http://www.strand-ngs.com/webinar_registration"><strong>Session 1</strong></a></p>
</td>
<td valign="top">
<p style="text-align: center;">25 Feb&nbsp;<br /> 12:30 AM</p>
</td>
<td>
<p style="text-align: center;">25 Feb&nbsp;<br /> 5:30 PM</p>
</td>
<td>
<p style="text-align: center;">25 Feb&nbsp;<br /> 9:30 AM</p>
</td>
<td>
<p style="text-align: center;">25 Feb&nbsp;<br /> 2:00 PM</p>
</td>
</tr>
<tr>
<td valign="top">
<p style="text-align: center;"><a href="http://www.strand-ngs.com/webinar_registration"><strong>Session 2</strong></a></p>
</td>
<td valign="top">
<p style="text-align: center;">25 Feb&nbsp;<br /> 9:00 AM</p>
</td>
<td>
<p style="text-align: center;">26 Feb<br /> 2:00 AM</p>
</td>
<td>
<p style="text-align: center;">25 Feb&nbsp;<br /> 6:00 PM</p>
</td>
<td>
<p style="text-align: center;">25 Feb&nbsp;<br /> 10:30 PM</p>
</td>
</tr>
</tbody>
</table><p><strong style="font-size: 12.8000001907349px;">Register here: </strong><a href="http://www.strand-ngs.com/webinar_registration">http://www.strand-ngs.com/webinar_registration</a></p><p><strong>About Speaker:</strong></p><p>Dr. Veena Hedatale, has a PhD in Plant Genetics from The Radboud University, Netherlands focused on meiosis and recombination. Her prior academic experience at Cornell University was on genetic mapping and gene transformation in Rice. She has worked with Monsanto, and contributed to data mining, database development as well as gene/promoter/pathway discovery for traits related to yield and stress in crop species. At Strand, Veena has worked on Pharmacogenomic analysis of targets and Gene family analysis projects. Currently, she is part of the Strand NGS Application Science team and is involved in the analysis of next generation sequencing data.</p><p>Please feel free to contact us 24/5, for availing free online training or if you have any questions.</p></div><div><p><strong style="font-size: 12.8000001907349px;">Email:</strong> sales@strandngs.com</p><p><strong>Phone (USA):</strong> 1-800-752-9122</p><p><strong>Phone (ROW):</strong> +1-650-353-5060</p><p>&nbsp;</p></div>]]></description>
	<dc:creator>Yeshodari</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/videolist/watch/14338/biology-computers-collide-in-high-demand-field-of-bioinformatics</guid>
	<pubDate>Mon, 25 Aug 2014 00:56:10 -0500</pubDate>
	<link>https://bioinformaticsonline.com/videolist/watch/14338/biology-computers-collide-in-high-demand-field-of-bioinformatics</link>
	<title><![CDATA[Biology, Computers Collide in High-Demand Field of Bioinformatics]]></title>
	<description><![CDATA[<iframe width="" height="" src="https://www.youtube-nocookie.com/embed/fk0z7KOTyMo" frameborder="0" allowfullscreen></iframe>Dr. Shivas Amin calls bioinformatics a "collision of biology and computers." Students learn how to use computers and skills in math and biology to analyze genome and proteome projects to prepare for high-demand jobs in the life sciences. Learn more about Amin and hear from student Medina Baitemirova and alumnus Lukas Simon about the fast-growing field of bioinformatics.]]></description>
	
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	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/29407/live-webinar-on-rna-seq-data-analysis-on-9-nov-2016</guid>
	<pubDate>Wed, 19 Oct 2016 05:25:27 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/29407/live-webinar-on-rna-seq-data-analysis-on-9-nov-2016</link>
	<title><![CDATA[Live Webinar on RNA-Seq Data Analysis on 9 Nov 2016]]></title>
	<description><![CDATA[<p><strong><a href="http://www.strand-ngs.com/webinar_registration">Live Webinar on RNA-Seq Data Analysis</a></strong></p><p><a href="http://www.strand-ngs.com/webinar_registration">Abstract: </a>Strand NGS supports an extensive workflow for the analysis and visualization of RNA-Seq data. The workflow includes Transcriptome / Genome alignment, Differential expression analysis with Statistical approach and Splicing events detection. Strand NGS also supports novel discovery like identification of novel genes, exons and Novel splice junctions, alongside it can also detect gene fusion events. Further downstream analysis such as GO and pathway analysis can be performed on the set of interesting genes. The product has an option to create pipelines for time consuming jobs which automates analysis and leaves more time for end data interpretation. This webinar will give an overview of the features in the RNA-Seq data analysis workflow in Strand NGS and also highlights on parameters within each feature that can be optimized depending on datasets and analysis needs.</p><p><a href="http://www.strand-ngs.com/webinar_registration">Speaker:</a> Mr. Sugandan Sivamani, Senior Application Scientist, Strand Life Sciences</p><p>Date: 9th Nov, <a href="http://www.strand-ngs.com/webinar_registration">Session 1</a> for SAPK/ APFO: 2:30 PM IST Date: 9th Nov, <a href="http://www.strand-ngs.com/webinar_registration">Session 2</a> for AFO/ EMEA: 9:00 AM PST</p><p>Register here <a href="http://www.strand-ngs.com/webinar_registration">http://www.strand-ngs.com/webinar_registration</a></p>]]></description>
	<dc:creator>Strand</dc:creator>
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