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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/44518?offset=620</link>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44288/upset-plots</guid>
	<pubDate>Fri, 24 Mar 2023 22:30:23 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44288/upset-plots</link>
	<title><![CDATA[Upset plots !]]></title>
	<description><![CDATA[<p>Upset plots are a type of visualization used to analyze the intersection of sets or categories. They are particularly useful for displaying data with multiple categories and analyzing their overlaps.</p>
<p>In an upset plot, each row represents a category or set, and each column represents a data point. The length of the bar for each category indicates the number of data points that belong to that category. The plot also shows the intersections between categories, represented by overlapping bars.</p>
<p>Upset plots are useful for visualizing complex data with multiple categories and intersections, and can help identify patterns and relationships between categories. They are often used in fields such as bioinformatics, where they can be used to analyze gene expression data or to compare the results of different experimental conditions.</p>
<p>https://jokergoo.github.io/ComplexHeatmap-reference/book/upset-plot.html#example-with-the-genomic-regions</p><p>Address of the bookmark: <a href="https://jokergoo.github.io/ComplexHeatmap-reference/book/upset-plot.html#example-with-the-genomic-regions" rel="nofollow">https://jokergoo.github.io/ComplexHeatmap-reference/book/upset-plot.html#example-with-the-genomic-regions</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/12936/assistant-professor-medical-bioinformatics</guid>
  <pubDate>Wed, 23 Jul 2014 05:00:38 -0500</pubDate>
  <link></link>
  <title><![CDATA[Assistant Professor - Medical Bioinformatics]]></title>
  <description><![CDATA[
<p>Advt. No : ME-I/A-IV/03/14</p>

<p>No.of Posts:01 (SC)</p>

<p>Pay Scale:</p>

<p>Pay Band of Rs.15600-39100 + Rs.6000/- GP +NPA @ 25% of Basic Pay +Learning Resource Allowance @ Rs.20,000/-P.A.+ Conveyance Allowance @ Rs. 1650/-P.M.+ Academic Allowance @ Rs.2500/- P.M. and other admissible allowances.</p>

<p>Qualifications:</p>

<p>Area of Specialization:-</p>

<p>Bioinformatics/Computational/Biology/Genomics/ Proteomics/ Structural Biology</p>

<p>1. Postgraduate qualification, e.g. Master’s Degree in Biotechnology/Bioinformatics/ Biophysics.</p>

<p>2. A Doctorate Degree of recognized University/Institute in a basic or allied Medical Science subject e.g. Medical Biotechnology/Biophysics. Bioinformatics/X-ray Crystallography/</p>

<p>Immunology/Structural Biology etc</p>

<p>Experience:</p>

<p>1.Minimum three years teaching and/or research experience in a recognized medical/research Institution in an allied medical subject after obtaining doctorate degree and preferably in Medical</p>

<p>Molecular Biology/ Biophysics/Structural Biology/Genomics and Clinical Proteomics/Computational Biology.</p>

<p>2. Minimum two publication with atleast one in international journal and atleast one as first author</p>

<p>Desirable:-</p>

<p>Consistently excellent scholastic/academic record, demonstrated ability to write grant proposal/(s) successfully, Post Doctoral training in a frontier area of medical Bioinformatics Research and of direct relevance to clinical diagnosis or patient care (preferably from a recognized top-ranking medical institution abroad)</p>

<p>Send your applications to O/O, Deputy Registrar, Recruitment &amp; Establishment Cell, University of Health Sciences, Rohtak by 08.7.2014</p>

<p>For more details,please visit website:http://pgimsrohtak.nic.in/2014%20AP%20Advt.pdf</p>
]]></description>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/1471/24-mb-genome-size-for-worlds-biggest-virus</guid>
	<pubDate>Thu, 08 Aug 2013 10:05:37 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/1471/24-mb-genome-size-for-worlds-biggest-virus</link>
	<title><![CDATA[2.4 Mb Genome Size for World's Biggest Virus]]></title>
	<description><![CDATA[<p>The genome size of new discovered Pandoraviruses have roughly twice the size of the record-holding Megavirus genomic code. Interestingly only 6 percent of its genes resembled the genes other organisms. It is assume that it may come from a different origin.</p><p>For detail : http://www.sciencemag.org/content/341/6143/281</p><p>http://www.npr.org/blogs/health/2013/07/18/203298244/worlds-biggest-virus-may-have-ancient-roots</p><p>&nbsp;</p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/13025/the-5-reasons-to-mistakes-at-bioinformatics-work</guid>
	<pubDate>Thu, 24 Jul 2014 02:51:41 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/13025/the-5-reasons-to-mistakes-at-bioinformatics-work</link>
	<title><![CDATA[The 5 reasons to mistakes at bioinformatics work !!!]]></title>
	<description><![CDATA[<p>When you're just starting out with biological programming, it's easy to run into complex problems that make you wonder how anyone has ever managed to write a program. There are some problems that trip up nearly every bioinformatician--everything from getting started understanding the biological problems to dealing with program design. Some random mistakes are so prominent that even experienced biological programmers do it. The 8 years in bioinformatics and my few random observations, most of them are snarky. These reasons will always take longer than expected and compel you to postpone your project deadline.</p><p><strong>1.Stupid for biologist:</strong> Biology is so complex that it will make bioinformatician feel stupid. There are no any universal fixed rules; it can surprise you any time. So be nice to biologists who ask questions and resolve your biological puzzles. Sometime you will have no idea what the hell you were doing either.<br /><br /><strong>2.Puzzling why:</strong> Do not hesitate to ask question. Especially. at the beginning of project you will have to ask a lot of questions. Instead of puzzling it out at end check out and clear your doubt even for a single error. It may can leads to wrong conclusion.<br /><br /><strong>3.Running marathon:</strong> The most of the biological software&rsquo;s documentation is always incomplete. In other word they are no more than 95 percent complete. Sometime a single problem can halt your entire project for months. Compilation and running the pipelines in tedious because almost all are interdependent and need proper configuration. I face the same kind of problem with Evolver :( &hellip; <br /><br /><strong>4.Folders missing:</strong> The pipelines generate lots of data, and we keep them in several folders for future use. But sometime we delete them by mistake and move to recovery&hellip;<br /><br /><strong>5.Digging deeper:</strong> Digging deeper is fruitful, but some time it can be catastrophic. You may get frustrated or direction less. So keep a biologist with you for rescue &hellip;. Sometime an expert computer programmer to handle your server. Remember, the server will always go down when you need it the most.<br /><br />The most common frustrating&nbsp; common line: Why do we do this again?</p>]]></description>
	<dc:creator>Jit</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/videolist/watch/5933/virus-3d-animation</guid>
	<pubDate>Sat, 26 Oct 2013 09:01:27 -0500</pubDate>
	<link>https://bioinformaticsonline.com/videolist/watch/5933/virus-3d-animation</link>
	<title><![CDATA[Virus 3D Animation]]></title>
	<description><![CDATA[<iframe width="" height="" src="https://www.youtube-nocookie.com/embed/67ays2ZYr48" frameborder="0" allowfullscreen></iframe>piranha.dl facebook site: http://www.facebook.com/home.php?#!/pages/piranhadl-3D/131721586891915]]></description>
	
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/13337/phd-opportunity-at-universite-de-liege-belgium</guid>
  <pubDate>Sat, 02 Aug 2014 01:12:43 -0500</pubDate>
  <link></link>
  <title><![CDATA[PhD opportunity at Université de Liège - Belgium]]></title>
  <description><![CDATA[
<p>PhD opportunity at Université de Liège - Belgium</p>

<p>The Bioinformatics and Systems Biology Unit of Université de Liège (Belgium) is looking for a highly motivated master student with programming skills for a PhD thesis project (4 years, fully funded) with the goal of designing computational tools that use literature, genomic and structural data in order to infer regulatory and metabolic networks.  </p>

<p>Applicants are invited to send their resume and a recommendation letter to Prof. Patrick Meyer (more details at   www.biosys.ulg.ac.be )</p>

<p>For more information : www.biosys.ulg.ac.be</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43110/quasimodo-quasispecies-metric-determination-on-omics</guid>
	<pubDate>Sat, 26 Jun 2021 15:22:56 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43110/quasimodo-quasispecies-metric-determination-on-omics</link>
	<title><![CDATA[QuasiModo - Quasispecies Metric Determination on Omics]]></title>
	<description><![CDATA[<p><span>This repository contains the scripts and pipeline that reproduces the results of the HCMV benchmarking study. In this study we evaluated genome assemblers and variant callers on 10 in vitro generated, mixed strain HCMV sequence samples, each consisting of two lab strains in different abundance ratios. This tool can also be used to evaluate assemblies and variant calling results on other similar datasets.</span></p>
<p><span>https://academic.oup.com/bib/article/22/3/bbaa123/5868070</span></p><p>Address of the bookmark: <a href="https://github.com/hzi-bifo/Quasimodo" rel="nofollow">https://github.com/hzi-bifo/Quasimodo</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/13523/megadock-40</guid>
	<pubDate>Thu, 07 Aug 2014 18:08:54 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/13523/megadock-40</link>
	<title><![CDATA[MEGADOCK 4.0]]></title>
	<description><![CDATA[<p>An ultra&ndash;high-performance protein&ndash;protein docking software for heterogeneous supercomputers</p>
<p id="p-4"><strong>Summary:</strong> The application of protein&ndash;protein docking in large-scale interactome analysis is a major challenge in structural bioinformatics and requires huge computing resources. In this work, we present MEGADOCK 4.0, an FFT-based docking software that makes extensive use of recent heterogeneous supercomputers and shows powerful, scalable performance of over 97% strong scaling.</p>
<p id="p-5"><strong>Availability and Implementation:</strong> MEGADOCK 4.0 is written in C++ with OpenMPI and NVIDIA CUDA 5.0 (or later) and is freely available to all academic and non-profit users at: <a href="http://www.bi.cs.titech.ac.jp/megadock">http://www.bi.cs.titech.ac.jp/megadock</a>.</p>
<p id="p-6"><strong>Contact:</strong> <a href="mailto:akiyama@cs.titech.ac.jp">akiyama@cs.titech.ac.jp</a></p><p>Address of the bookmark: <a href="http://bioinformatics.oxfordjournals.org/content/early/2014/08/06/bioinformatics.btu532.short" rel="nofollow">http://bioinformatics.oxfordjournals.org/content/early/2014/08/06/bioinformatics.btu532.short</a></p>]]></description>
	<dc:creator>Suleman Khan</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/44506/mosquito-species-known-for-transmitting-the-dengue-virus</guid>
	<pubDate>Wed, 03 Apr 2024 00:05:51 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/44506/mosquito-species-known-for-transmitting-the-dengue-virus</link>
	<title><![CDATA[Mosquito species known for transmitting the Dengue virus]]></title>
	<description><![CDATA[<p><span>Here is a list of mosquito species known for transmitting the Dengue virus along with essential and applied information about each species:</span><br /><br /><span>1. Aedes aegypti:</span><br /><span>- Geographical Distribution: Found in tropical and subtropical regions worldwide.</span><br /><span>- Biting Behavior: Daytime biter, prefers feeding indoors, often around human dwellings.</span><br /><span>- Role in Dengue Transmission: Primary vector responsible for transmitting Dengue virus to humans.</span><br /><br /><span>2. Aedes albopictus (Asian tiger mosquito):</span><br /><span>- Geographical Distribution: Found in tropical, subtropical, and temperate regions worldwide.</span><br /><span>- Biting Behavior: Daytime biter, feeds both indoors and outdoors, aggressive feeder.</span><br /><span>- Role in Dengue Transmission: Secondary vector, can transmit Dengue virus to humans.</span><br /><br /><span>3. Aedes polynesiensis:</span><br /><span>- Geographical Distribution: Found in Pacific Islands and coastal regions.</span><br /><span>- Biting Behavior: Daytime biter, prefers feeding outdoors, often near coastal areas.</span><br /><span>- Role in Dengue Transmission: Vector of Dengue virus in specific geographic regions.</span><br /><br /><span>4. Aedes scutellaris:</span><br /><span>- Geographical Distribution: Found in Southeast Asia, Pacific Islands, and coastal regions.</span><br /><span>- Biting Behavior: Daytime feeder, active in shaded areas, prefers outdoor environments.</span><br /><span>- Role in Dengue Transmission: Vector of Dengue virus, particularly in coastal areas.</span><br /><br /><span>5. Aedes africanus:</span><br /><span>- Geographical Distribution: Found in parts of Africa, including forested areas.</span><br /><span>- Biting Behavior: Daytime feeder, prefers shaded areas, bites humans and other animals.</span><br /><span>- Role in Dengue Transmission: Vector of Dengue virus in African regions.</span><br /><br /><span>Understanding the geographical distribution and biting behavior of these mosquito species is crucial for implementing effective control and prevention strategies to reduce Dengue virus transmission.</span></p>]]></description>
	<dc:creator>BioStar</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/14024/grapher</guid>
	<pubDate>Thu, 14 Aug 2014 14:02:17 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/14024/grapher</link>
	<title><![CDATA[GrapheR !!!]]></title>
	<description><![CDATA[<p>What a wonderful gem <em>GrapheR</em> is.... Oh yes it is. <em>GrapheR</em> is a GUI for base graphics in R by http://www.maximeherve.com/. The package provides a graphical user interface for creating base charts in R. It is ideal for beginners in R, as the user interface is very clear and the code is written along side into a text file, allowing users to recreate the charts directly in the console. <br /><br />Adding and changing legends? Messing around with the plotting window settings? It is much easier/quicker with this GUI than reading the help file and trying to understand the various parameters.<br />Here is a little example using the iris data set.<br /><br />library(GrapheR)<br />data(iris)<br />run.GrapheR()<br /><br />This will bring up a window that helps me to create the chart and tweak the various parameters.</p><p><img src="http://4.bp.blogspot.com/-NbnCM1dPh3E/U9aW9YxJ9oI/AAAAAAAABgo/gEPzPhOpf2Y/s1600/GrapheR.png" alt="image" width="878" height="868" style="border: 0px; border: 0px;"><br /><br />Finally, I find the underlying R code in a file created by <em>GrapheR</em>. For more details read also the <a href="http://cran.r-project.org/web/packages/GrapheR/index.html" target="_blank">package vignette</a>, which is available in <a href="http://cran.r-project.org/web/packages/GrapheR/vignettes/manual_en.pdf" target="_blank">English</a>, <a href="http://cran.r-project.org/web/packages/GrapheR/vignettes/manual_fr.pdf" target="_blank">French</a> and <a href="http://cran.r-project.org/web/packages/GrapheR/vignettes/manual_de.pdf" target="_blank">German</a>!</p>]]></description>
	<dc:creator>John Parker</dc:creator>
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