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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/42974?offset=300</link>
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	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38420/regioner-an-r-package-for-the-management-and-comparison-of-genomic-regions</guid>
	<pubDate>Tue, 11 Dec 2018 08:43:51 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38420/regioner-an-r-package-for-the-management-and-comparison-of-genomic-regions</link>
	<title><![CDATA[regioneR: an R package for the management and comparison of genomic regions]]></title>
	<description><![CDATA[<p><span>Regioner is an R package for the management and comparison of genomic regions. It offers a set of function for basic manipulation of region sets extending the functionality of GenomicRanges and a powerful and customizable permutation test framework. With it, it's possible to study the association of a set of regions with other sets of regions, functions defined over the genome or essentially any user defined function.</span></p>
<p><span>http://gattaca.imppc.org/regioner/</span></p><p>Address of the bookmark: <a href="http://gattaca.imppc.org/regioner/" rel="nofollow">http://gattaca.imppc.org/regioner/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/11107/the-minerva-research-group-for-bioinformatics</guid>
  <pubDate>Tue, 27 May 2014 15:48:14 -0500</pubDate>
  <link></link>
  <title><![CDATA[The Minerva Research Group for Bioinformatics]]></title>
  <description><![CDATA[
<p>The focus of the bioinformatics group is to use computational approaches to gain an insight into genome evolution in primates.</p>

<p>http://www.eva.mpg.de/genetics/bioinformatics/overview.html?Fsize=0%2C%20%40%2F%27</p>

<p>Kelso Group<br />Department of Evolutionary Genetics<br />Max Planck Institute for Evolutionary Anthropology<br />Deutscher Platz 6<br />04103 Leipzig<br />Germany<br />Phone: +49 341 3550 500</p>

<p>Job: <br />http://www.eva.mpg.de/genetics/bioinformatics/jobs.html?Fsize=0%2C%2B%40</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/39244/chromomap-an-r-package-for-interactive-visualization-and-annotation-of-chromosomes</guid>
	<pubDate>Fri, 12 Apr 2019 05:30:41 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/39244/chromomap-an-r-package-for-interactive-visualization-and-annotation-of-chromosomes</link>
	<title><![CDATA[chromoMap-An R package for Interactive Visualization and Annotation of Chromosomes]]></title>
	<description><![CDATA[<p>Provides interactive, configurable and elegant graphics visualization of the chromosomes or chromosome regions of any living organism allowing users to map chromosome elements (like genes, SNPs etc.) on the chromosome plot. It introduces a special plot viz. the "chromosome heatmap" that, in addition to mapping elements, can visualize the data associated with chromosome elements (like gene expression) in the form of heat colors which can be highly advantageous in the scientific interpretations and research work. The package provide multiple features like visualizing multiple sets, chromosome heat-maps, group annotations, adding hyperlinks, and labelling. The plots can be saved as HTML documents that can be customized and shared easily. In addition, you can include them in R Markdown or in R 'Shiny' applications.</p><p>Address of the bookmark: <a href="https://cran.r-project.org/web/packages/chromoMap/vignettes/chromoMap.html" rel="nofollow">https://cran.r-project.org/web/packages/chromoMap/vignettes/chromoMap.html</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/11582/monitor-running-jobs-on-linux-server</guid>
	<pubDate>Fri, 06 Jun 2014 16:18:43 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/11582/monitor-running-jobs-on-linux-server</link>
	<title><![CDATA[Monitor running jobs on Linux server]]></title>
	<description><![CDATA[<p>You as a bioinformatican run lots of program on your servers. Sometime the shared server is also used by your colleague. If server is busy you sometime need to check the running programs and want to monitor the running programs as well. The "top" command will come in handy when you need to find out if things are still running, how long they&rsquo;ve been running, or how much memory is being used.<br /><br />&lsquo;top&rsquo; is very simple to run: type<br /><br />%% top<br /><br />You&rsquo;ll get a screen that looks like this, and is updated regularly:<br /><br /><img src="http://bioinformaticsonline.com/mod/photo/top.png" width="659" height="582" alt="image" style="border: 0px;"><br />Simple, right? Heh.<br /><br />First! Note that you can use &lsquo;q&rsquo; or &lsquo;CTRL-C&rsquo; to exit from &lsquo;top&rsquo;.<br /><br />Now let&rsquo;s read and understand at each line independently.<br /><br />The first line:<br /><br />top - 23:00:48 up 39 days,&nbsp; 2 user,&nbsp; load average: 0.00, 0.00, 0.00<br /><br />The first line tells you the current time, how long the machine has been up, how many users are logged in, and the short/medium/long-term compute load on the machine. If you run something for a long time, you&rsquo;ll see these numbers go up. Right now, the machine is basically just sitting there, so these are all close to 0.<br /><br />The second line:</p><p>Tasks:&nbsp; 239 total,&nbsp;&nbsp; 1 running,&nbsp; 238 sleeping,&nbsp;&nbsp; 0 stopped,&nbsp;&nbsp; 0 zombie<br /><br />This line tells you how many processes are running. If you are using laptops machines it&rsquo;s not so interesting because you really are the only one using this machine.<br /><br />Cpu(s):&nbsp; 0.0%us,&nbsp; 0.0%sy,&nbsp; 0.0%ni,100.0%id,&nbsp; 0.0%wa,&nbsp; 0.0%hi,&nbsp; 0.0%si,&nbsp; 0.0%st<br /><br />This line contains the CPU load. The first two numbers are how busy the system is doing computation (&ldquo;us&rdquo; stands for &ldquo;user&rdquo;) and how busy the system is doing system-y things like accessing disks or network (&ldquo;sy&rdquo; stands for &ldquo;system&rdquo;). We&rsquo;ll talk more about this later.<br /><br />Mem:&nbsp;&nbsp; 49457320k total,&nbsp;&nbsp;&nbsp; 3492174k used,&nbsp; 14535596k free,&nbsp;&nbsp;&nbsp; 1435148k buffers<br /><br />This should be easy to understand &ndash; how much memory you&rsquo;re using! <br /><br />Swap:&nbsp;&nbsp; 539356k total,&nbsp;&nbsp; 28332k used,&nbsp;&nbsp; 836562k free,&nbsp;&nbsp;&nbsp; 29862014k cached<br /><br />Swap is just on-disk memory that can be used to &ldquo;swap&rdquo; out programs from main memory. Again, we&rsquo;ll talk about this later.:<br /><br />PID USER&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; PR&nbsp; NI&nbsp; VIRT&nbsp; RES&nbsp; SHR S %CPU %MEM&nbsp;&nbsp;&nbsp; TIME+&nbsp; COMMAND<br />&nbsp; 1 root&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 39 &nbsp; 19&nbsp; 0&nbsp; 0&nbsp; 0 S&nbsp; 0.0&nbsp; 0.0&nbsp;&nbsp; 246:57.22 kipmi0<br />&nbsp; 2 root&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; RT&nbsp;&nbsp; 0&nbsp;&nbsp;&nbsp;&nbsp; 0&nbsp;&nbsp;&nbsp; 0&nbsp;&nbsp;&nbsp; 0 S&nbsp; 0.0&nbsp; 0.0&nbsp;&nbsp; 0:00.00 migration/0<br /><br />And... finally! What&rsquo;s actually running! The two most important numbers are the %CPU and %MEM towards the right, as well as the COMMAND. This tells you how compute- and memory-intensive your program is. Right now, nothing&rsquo;s running so the numbers aren&rsquo;t very interesting, but just wait until we run something...</p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41006/netgo-r-shiny-package-for-network-integrated-pathway-enrichment-analysis</guid>
	<pubDate>Wed, 12 Feb 2020 12:40:54 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41006/netgo-r-shiny-package-for-network-integrated-pathway-enrichment-analysis</link>
	<title><![CDATA[netGO: R-Shiny package for network-integrated pathway enrichment analysis]]></title>
	<description><![CDATA[<p>netGO is an R/Shiny package for network-integrated pathway enrichment analysis.<br>netGO provides user-interactive visualization of enrichment analysis results and related networks.</p>
<p>Currently, netGO supports analysis for four species (<em><a href="https://github.com/unistbig/netGO-Data/tree/master/Human">Human</a>,&nbsp;<a href="https://github.com/unistbig/netGO-Data/tree/master/Mouse">Mouse</a>,&nbsp;<a href="https://github.com/unistbig/netGO-Data/tree/master/Arabidopsis">Arabidopsis thaliana</a>,and&nbsp;<a href="https://github.com/unistbig/netGO-Data/tree/master/Yeast">Yeast</a></em>)<br>These data are available from&nbsp;<a href="https://github.com/unistbig/netGO-Data">netGO-Data</a>&nbsp;repository.</p>
<p><a href="https://academic.oup.com/bioinformatics/advance-article/doi/10.1093/bioinformatics/btaa077/5728635">https://academic.oup.com/bioinformatics/advance-article/doi/10.1093/bioinformatics/btaa077/5728635</a></p><p>Address of the bookmark: <a href="https://github.com/unistbig/netGO" rel="nofollow">https://github.com/unistbig/netGO</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/videolist/watch/11355/genomics-and-personalized-medicine-breakthroughs</guid>
	<pubDate>Sun, 01 Jun 2014 23:40:14 -0500</pubDate>
	<link>https://bioinformaticsonline.com/videolist/watch/11355/genomics-and-personalized-medicine-breakthroughs</link>
	<title><![CDATA[Genomics and Personalized Medicine Breakthroughs]]></title>
	<description><![CDATA[<iframe width="" height="" src="https://www.youtube-nocookie.com/embed/VAR-1vNc0TE" frameborder="0" allowfullscreen></iframe>http://bit.ly/e8QGzY Human genome mapping is now enabling a breakthrough in medical innovation -- personalized medicine. What does this mean for patients? We can now identify predispositions to disease, predict how we metabolize drugs, and figure out what kinds of treatments we may respond to, and even determine when a drug may give us an adverse reaction. All medical specialties benefit from human genome intelligence -- oncology saw the first impacts -- but advances are now being seen in cardiology, obstetrics and gynecology, pediatric diseases, gastroenterology, rheumatology, immunology and other areas. This video covers the areas that genetic medicine is impacting and where the future of genomic medicine is heading.]]></description>
	
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42299/platypus-%E2%80%93-r-package-for-object-detection-and-image-segmentation</guid>
	<pubDate>Mon, 09 Nov 2020 02:56:25 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42299/platypus-%E2%80%93-r-package-for-object-detection-and-image-segmentation</link>
	<title><![CDATA[Platypus – R package for object detection and image segmentation.]]></title>
	<description><![CDATA[<p><a href="https://github.com/maju116/platypus" target="_blank">platypus</a>&nbsp;is an R package for object detection and semantic segmentation. Currently using&nbsp;</p>
<div>platypus&nbsp;you can perform:</div>
<ul>
<li>multi-class semantic segmentation using&nbsp;U-Net&nbsp;architecture</li>
<li>multi-class object detection using&nbsp;YOLOv3&nbsp;architecture</li>
</ul>
<p>You can install the latest version of&nbsp;platypus&nbsp;with&nbsp;remotes&nbsp;package:</p>
<div>
<div>
<div>
<div>remotes::install_github("maju116/platypus")</div>
</div>
</div>
</div>
<p>Note that in order to install&nbsp;platypus&nbsp;you need to install&nbsp;keras&nbsp;and&nbsp;tensorflow&nbsp;packages and&nbsp;Tensorflow&nbsp;version&nbsp;&gt;= 2.0.0&nbsp;(&nbsp;Tensorflow 1.x&nbsp;will not be supported!)</p><p>Address of the bookmark: <a href="https://github.com/maju116/platypus" rel="nofollow">https://github.com/maju116/platypus</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
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<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/11441/assistant-professor-in-bioinformatics-at-dr-d-y-patil-biotechnology-bioinformatics-institute</guid>
  <pubDate>Tue, 03 Jun 2014 19:54:15 -0500</pubDate>
  <link></link>
  <title><![CDATA[Assistant Professor 	in Bioinformatics at Dr. D. Y. Patil Biotechnology &amp; Bioinformatics Institute]]></title>
  <description><![CDATA[
<p>Dr. D. Y. Patil Biotechnology &amp; Bioinformatics Institute <br />Tathawade, Pune 411033.</p>

<p>Assistant Professor 	in Bioinformatics </p>

<p>Essential :<br />First Class Master’s Degree in the appropriate branch of Life Sciences / Technology (Tech.)<br />OR<br />Ph.D in Life Sciences or in the respective subject area of specialization<br />OR<br />Good Academic record with at least 55% marks (or an equivalent grade) at the Master’s Degree level, in the relevant subject or an equivalent degree from an Indian / Foreign University.<br />Besides fulfilling the above qualifications, candidates should have cleared the eligibility test (NET) for lecturers conducted by the UGC, CSIR or similar test accredited by the UGC and as per the requirements of UGC guidelines.</p>

<p>Desirable :<br />Teaching, research industrial and/or professional experience in a reputed organization. <br />Papers presented at Conferences and/or in refereed journals</p>

<p>Note : Application are invited in prescribed form Click here for Application Form<br />Kindly send your applications to “Registrar, Dr. D. Y. Patil Vidyapeeth, Pune, Sant Tukaram Nagar, Pimpri, Pune – 411018., Maharashtra, India.” should reach in the University office within 15 days from the publication.</p>

<p>More Info: http://www.dpu.edu.in/BiotechResearchPositions.aspx</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43815/kebabs-package-provides-functionality-for-kernel-based-analysis-of-biological-sequences-via-support-vector-machine-svm-based-methods</guid>
	<pubDate>Fri, 04 Mar 2022 00:14:11 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43815/kebabs-package-provides-functionality-for-kernel-based-analysis-of-biological-sequences-via-support-vector-machine-svm-based-methods</link>
	<title><![CDATA[kebabs: package provides functionality for kernel based analysis of biological sequences via Support Vector Machine (SVM) based methods]]></title>
	<description><![CDATA[<p><span>The&nbsp;</span><tt>kebabs</tt><span>&nbsp;package provides functionality for kernel based analysis of biological sequences via Support Vector Machine (SVM) based methods. Biological sequences include DNA, RNA, and amino acid (AA) sequences. Sequence kernels define similarity measures between sequences. The package implements some of the most important kernels for sequence analysis in a very flexible and efficient way and extends the standard position-independent functionality of these kernels in a novel way to take the position of patterns in the sequences into account for the similarity measure.</span></p>
<p>http://www.bioinf.jku.at/software/kebabs/</p>
<p>http://bioconductor.org/packages/release/bioc/vignettes/kebabs/inst/doc/kebabs.pdf</p><p>Address of the bookmark: <a href="http://www.bioinf.jku.at/software/kebabs/" rel="nofollow">http://www.bioinf.jku.at/software/kebabs/</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
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<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/11656/faculty-post-at-zhejiang-university</guid>
  <pubDate>Tue, 10 Jun 2014 03:40:40 -0500</pubDate>
  <link></link>
  <title><![CDATA[Faculty post at Zhejiang University]]></title>
  <description><![CDATA[
<p>Zhejiang University (ZJU) is seeking faculty candidates for its newly launched, highly competitive and well funded “Hundred Talents Program”. This search covers all colleges and departments at ZJU. Applicants, expected to be about 35 years old, should hold PhD degree, and postdoctoral experiences are preferred for applicants in most fields. Applicants should have demonstrated commitment to excellence in teaching and research at a level comparable to the academic achievement of assistant professor or associate professor in world-renowned universities. Successful candidates must work full-time and are expected to establish internationally competitive and independent research program in cutting-edge areas of the relevant field at ZJU.</p>

<p>As one of the leading research-intensive universities in China, ZJU is located in the beautiful city of Hangzhou. Successful candidates will be employed as Principal Investigators and are qualified to supervise doctoral students. ZJU will offer an internationally competitive salary and the opportunity to purchase university's apartment at a price much lower than the market price, and will provide office and laboratory spaces as well as internationally competitive research startup packages.</p>

<p>Qualified applicants are strongly encouraged to submit their applications electronically to tr@zju.edu.cn. Applicants should include the following materials in pdf format: a comprehensive CV, a statement of research and teaching plan, and a list of 3 to 5 references with detailed contact information.</p>

<p>Contact：Talents Office, ZJU</p>

<p>Tel：+86-571-88981345, +86-571-88981390</p>

<p>Fax：+86-571-88981976</p>

<p>E-mail:tr@zju.edu.cn</p>
]]></description>
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