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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/1161?offset=390</link>
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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/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/opportunity/view/5621/genome2014</guid>
  <pubDate>Tue, 15 Oct 2013 12:47:32 -0500</pubDate>
  <link></link>
  <title><![CDATA[Genome2014]]></title>
  <description><![CDATA[
<p>Genomics has profoundly changed our way of conducting research in microbiology. The power of high–throughput DNA sequencing technologies, in particular the recent development of next generation sequencing allows researchers now to address an increasingly diverse range of biological problems. The scale and efficiency of sequence-based analyses that can now be achieved is providing unprecedented progress in diverse areas that range from the analyses of genomes to related disciplines such as transcriptional profiling - or protein - nucleic acid interaction studies: Population and metagenomics studies can now be conducted in an unprecedented large scale, regulatory processes can be studied genome-wide under hundreds of different conditions. The genome wide study of the interaction of DNA or RNA with proteins brings completely new insight into regulatory processes and even single cell analyses become now possible. The many diverse applications of next–generation sequencing and the importance of the insights that are being gained through these methods are very exiting and challenging. It is the perfect time to come together and exchange new knowledge and technologies in this area.<br /> <br />Thus the conference on "Microbiology after the genomics revolution - Genomes 2014" will be an appropriate and timely occasion to offer an outstanding discussion forum for the best international researchers in all fields of cutting edge microbiology research to discuss newly discovered aspects of microbiology.</p>

<p>More @ http://www.genomes-2014.org/</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/13852/ebola-virus-disease-evdor-ebola-haemorrhagic-fever</guid>
	<pubDate>Sun, 10 Aug 2014 13:08:13 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/13852/ebola-virus-disease-evdor-ebola-haemorrhagic-fever</link>
	<title><![CDATA[Ebola virus disease (EVD)or Ebola haemorrhagic fever !!!]]></title>
	<description><![CDATA[<p>Ebola virus disease (EVD)or Ebola haemorrhagic fever is a severe and often deadly illness in humans, caused by the Ebola virus. The disease has high mortality rate, killing upto 90% of people who are infected.</p><p><img src="http://s4.reutersmedia.net/resources/r/?m=02&amp;d=20140808&amp;t=2&amp;i=959839176&amp;w=580&amp;fh=&amp;fw=&amp;ll=&amp;pl=&amp;r=LYNXMPEA770BX" width="580" height="452" alt="image" style="border: 0px;"></p><p><br />The ongoing 2014 West Africa Ebola outbreak is considered to be the largest and longest outbreak ever recorded of Ebola, killing at least 932 people and infecting more than 1,700 till date since March in Sierra Leone, Guinea, Nigeria and Liberia.<br /><br />Hence, the World Health Organisation (WHO) on 8 August, 2014 declared the killer Ebola epidemic ravaging parts of West Africa an international health emergency.<br /><br />Causes<br /><br />EVD is caused by infection with a virus of the family Filoviridae, genus Ebolavirus. While there are five identified sub-species of Ebolavirus, four viruses cause disease in humans. They are Bundibugyo virus (BDBV), Ebola virus (EBOV), Sudan virus (SUDV), Ta&iuml; Forest virus (TAFV).<br /><br />The fifth virus, Reston virus (RESTV), is not considered to be disease-causing in humans.<br /><br />According to WHO, EVD first appeared in 1976 in two simultaneous outbreaks, in Nzara, Sudan, and in Yambuku, Democratic Republic of Congo. The latter was in a village situated near the Ebola River from which the disease takes its name.</p><p>How does it spread?<br /><br />It is still unclear how Ebola spreads. However, it is believed that the first pateint becomes infected through contact with an infected animal's body fluids.<br /><br />Human-to-human transmission can occur through direct contact with blood, organs or other body fluids of infected people or exposure to objects such as needles and syringes that have been contaminated with infected secretions.<br /><br />Ebola can also be transmitted from men who have recovered from the disease through semen as it is infectious for up to 7 weeks.<br /><br />Infected dead bodies can spread Ebola as they are still infectious. So mourners who have direct contact with the body of deceased person can also get the disease.<br /><br />Who is most at risk?<br /><br />Health-care workers who do not wear appropriate protective clothing and family members who are in close contact with infected people or deceased patients.<br /><br />Signs and symptoms:<br /><br />Symptoms may occur between 2 and 21 days after contracting the infection. Common signs of Ebola include:</p><p><img src="https://scontent-b-sin.xx.fbcdn.net/hphotos-xap1/t1.0-9/p720x720/10494629_873450929332827_3274653669306581755_n.jpg" width="720" height="720" alt="image" style="border: 0px;"></p><p>Fever<br /><br />Headache<br /><br />Muscle, abdominal and joint pain<br /><br />Sore throat<br /><br />Weakness<br /><br />Diarrhea<br /><br />Vomit or cough up blood<br /><br />Chest pain<br /><br />Difficulty in breathing and swallowing<br /><br />Rash<br /><br />Hiccups<br /><br />Bleeding inside and outside the body<br /><br />Prevention<br /><br />Currently there is no vaccine available for humans. But the infection can be controlled through the use of recommended protective measures such as:<br /><br />Avoid contacting infected blood or secretions, including from those who are dead .<br /><br />Using standard precautions for all patients in the healthcare setting.<br /><br />Sterilizing equipment, and wearing protective clothing including masks, gloves, gowns and goggles.<br /><br />Washing your hands with soaps or detergents.<br /><br />Disinfecting your surroundings.<br /><br />Isolate people who have Ebola symptoms.<br /><br />Culling of infected animals, with close supervision of burial or incineration of carcasses.<br /><br />Yet, not travelling to the areas or countries where the virus is found is the best way to avoid Ebola.</p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
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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>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34088/sequence-evolution-function-computational-approaches-in-comparative-genomics</guid>
	<pubDate>Sun, 06 Aug 2017 06:58:12 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34088/sequence-evolution-function-computational-approaches-in-comparative-genomics</link>
	<title><![CDATA[Sequence - Evolution - Function; Computational Approaches in Comparative Genomics]]></title>
	<description><![CDATA[<p><em>Sequence - Evolution - Function</em><span>&nbsp;is an introduction to the computational approaches that play a critical role in the emerging new branch of biology known as functional genomics. The book provides the reader with an understanding of the principles and approaches of functional genomics and of the potential and limitations of computational and experimental approaches to genome analysis.</span></p><p>Address of the bookmark: <a href="https://www.ncbi.nlm.nih.gov/books/NBK20260/" rel="nofollow">https://www.ncbi.nlm.nih.gov/books/NBK20260/</a></p>]]></description>
	<dc:creator>Jit</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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  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/34929/shendurelab</guid>
  <pubDate>Thu, 28 Dec 2017 09:57:50 -0600</pubDate>
  <link></link>
  <title><![CDATA[ShendureLab]]></title>
  <description><![CDATA[
<p>The mission of our lab is to develop and apply new technologies and methods for genetics, genomics and molecular biology. Most of our work exploits next-generation DNA sequencing which is effectively emerging as a broadly enabling microscope for the measurement of biological phenomena. Our ongoing work generally falls into six areas. These are listed below as links to representative publications in each area.</p>

<p>Developing New Molecular Methods</p>

<p>Genomic Approaches to Developmental Biology</p>

<p>Massively Parallel Functional Genomics</p>

<p>Translating Genomics to the Clinic</p>

<p>Genetic Basis of Human Disease</p>

<p>Genome Sequencing Technologies</p>

<p>http://krishna.gs.washington.edu/index.html<br />http://www.gs.washington.edu/faculty/shendure.htm</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/14186/pybedtools</guid>
	<pubDate>Wed, 20 Aug 2014 01:03:41 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/14186/pybedtools</link>
	<title><![CDATA[pybedtools]]></title>
	<description><![CDATA[<p>pybedtools is a Python wrapper for Aaron Quinlan's BEDtools programs (https://github.com/arq5x/bedtools), which are widely used for genomic interval manipulation or "genome algebra". pybedtools extends BEDTools by offering feature-level manipulations from with Python. See full online documentation, including installation instructions, at http://pythonhosted.org/pybedtools/.</p><p>More at http://pythonhosted.org/pybedtools/</p><p>A powerful toolset for genome arithmetic.http://code.google.com/p/bedtools/</p>]]></description>
	<dc:creator>Shruti Paniwala</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37257/asar-advanced-metagenomic-sequence-analysis-in-r</guid>
	<pubDate>Mon, 09 Jul 2018 05:20:50 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37257/asar-advanced-metagenomic-sequence-analysis-in-r</link>
	<title><![CDATA[ASAR: Advanced metagenomic Sequence Analysis in R]]></title>
	<description><![CDATA[<p><span>An interactive data analysis tool for selection, aggregation and visualization of metagenomic data is presented. Functional analysis with a SEED hierarchy and pathway diagram based on KEGG orthology based upon MG-RAST annotation results is available.</span></p>
<p><span><span>To read the manual, please click the link&nbsp;</span><a href="https://askarbek-orakov.github.io/ASAR/">https://askarbek-orakov.github.io/ASAR/</a></span></p><p>Address of the bookmark: <a href="https://github.com/Askarbek-orakov/ASAR" rel="nofollow">https://github.com/Askarbek-orakov/ASAR</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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