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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/3013?offset=1080</link>
	<atom:link href="https://bioinformaticsonline.com/related/3013?offset=1080" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
	
<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/10841/ra-at-iisr-kozhikode</guid>
  <pubDate>Thu, 15 May 2014 10:08:09 -0500</pubDate>
  <link></link>
  <title><![CDATA[RA at IISR Kozhikode]]></title>
  <description><![CDATA[
<p>INDIAN INSTITUTE OF SPICES RESEARCH<br />(Indian Council of Agricultural Research)<br />Marikunnu P.O., Kozhikode – 673 012, Kerala</p>

<p>Walk- in- Test cum Interview (based on test) for the selection of Research Associate</p>

<p>under the scheme “Distributed Information Sub Centre –DISC” &amp; Research Assistant under scheme “Phytophthora, Fusarium and Ralstonia diseases of Horticultural and Field Crops” will be held at this Institute as per details indicated below.</p>

<p>WALK -IN- TEST CUM INTERVIEW</p>

<p>Name of the post : Research Associate</p>

<p>Date of Interview : 21-05-2014 at 10.00 AM</p>

<p>No. of posts : One</p>

<p>Qualifications : a)Essential</p>

<p>Ph.D Degree in Bioinformatics OR :  Masters degree in Bioinformatics with a minimum of<br />60% marks or equivalent OGPA with at least two years research experience as evidenced from fellowship/ associateship/training/published papers etc.</p>

<p>b)Desirable: Experience in NGS data analysis.</p>

<p>Emoluments : Rs. 23,000/- per month + HRA (Masters Degree Holders)</p>

<p>Rs. 24,000/- per month + HRA (Ph.D Degree Holders)</p>

<p>Upper age limit : 40 years for Men &amp; 45 years for Women as on date of Interview (Upper Age limits are relaxable for SC, ST and OBC candidates as per Govt. of India norms (at present 5 years for SC/ST and 3 years for OBC)</p>

<p>Duration of Project : Till 31-03-2017.</p>

<p>Title of Assigment : Research Assistant (on contract basis)</p>

<p>No. of vacancy : One</p>

<p>Qualification : Essential : Post Graduation in Bioinformatics and  Minimum one year experience in NGS data analysis</p>

<p>Desirable : Experience in Perl/Python/R</p>

<p>Remuneration : Rs. 20,000/- per month (consolidated)</p>

<p>Scope of work :</p>

<p>1. Analysis of different file formats and their conversions.</p>

<p>2. Assessing the quality of data and filtering of raw reads.<br />3. Assembling the raw reads-de novo as well as reference  mapping.<br />4. Compression of aligned reads using Jam tools<br />5. RNA-seq. Analysis<br />6. Differential expression testing involving Normalization,  Statistical testing, heat map generation &amp; hierarchical  clustering<br />7. Annotating the assembled genome and geneet testing  and their validation<br />8. Metabolic pathway analysis<br />9. Comparative genomics<br />10. Setting up of genome browsers.</p>

<p>Period of Assigment : Initially for six months.</p>

<p>Date &amp; Venue of Interview : 21-05-2014 at IISR, Kozhikode at 10.00 AM</p>

<p>More at http://www.spices.res.in/pdf/disc-advtmnt.pdf</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40834/nucleus-python-and-c-code-for-reading-and-writing-genomics-data</guid>
	<pubDate>Sun, 02 Feb 2020 08:14:19 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40834/nucleus-python-and-c-code-for-reading-and-writing-genomics-data</link>
	<title><![CDATA[Nucleus: Python and C++ code for reading and writing genomics data.]]></title>
	<description><![CDATA[<p>Nucleus is a library of Python and C++ code designed to make it easy to read, write and analyze data in common genomics file formats like SAM and VCF. In addition, Nucleus enables painless integration with the TensorFlow machine learning framework, as anywhere a genomics file is consumed or produced, a TensorFlow tfrecords file may be used instead.</p><p>Address of the bookmark: <a href="https://github.com/google/nucleus" rel="nofollow">https://github.com/google/nucleus</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/11000/professorassociate-professor-assistant-professor-at-chettinad-academy-of-research-and-education</guid>
  <pubDate>Sat, 24 May 2014 00:00:15 -0500</pubDate>
  <link></link>
  <title><![CDATA[Professor/Associate Professor/ Assistant Professor at Chettinad Academy of Research and Education]]></title>
  <description><![CDATA[
<p>OPEN FACULTY POSITION</p>

<p>Chettinad Academy of Research and Education (CARE) invites applications from eligible and translational research-oriented candidates to the posts of Professor/Associate Professor/ Assistant Professor  Computational Biology, Bioinformatics, and Pharmaceutical Chemistry.</p>

<p>Emoluments: As per UGC norms (Adequate Compensation for Postdoctoral/Teaching experience)</p>

<p>Candidates fulfilling the eligibility criteria as per the UGC norms can send their full CV with copies of certificates and reference letters to the following address by post or by e-mail on or before 31st May 2014</p>

<p>The Registrar,<br />Chettinad Academy of Research and Education,<br />Chettinad Health City<br />Kelambakkam, Chennai 603 103<br />Tamil Nadu<br />T +91 (0)44 4741 1000<br />F +91 (0)44 4741 1011<br />Email: jobs @chettinadhealthcity.com</p>

<p>Advertisement: http://182.73.176.163/chc/ads2014.pdf</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43101/luigi-a-python-package-that-helps-you-build-complex-pipelines-of-batch-jobs</guid>
	<pubDate>Thu, 24 Jun 2021 05:43:31 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43101/luigi-a-python-package-that-helps-you-build-complex-pipelines-of-batch-jobs</link>
	<title><![CDATA[Luigi: a Python package that helps you build complex pipelines of batch jobs.]]></title>
	<description><![CDATA[<p>Luigi is a Python (3.6, 3.7, 3.8, 3.9 tested) package that helps you build complex pipelines of batch jobs. It handles dependency resolution, workflow management, visualization, handling failures, command line integration, and much more.</p>
<p>Run <code>pip install luigi</code> to install the latest stable version from <a href="https://pypi.python.org/pypi/luigi">PyPI</a>. <a href="https://luigi.readthedocs.io/en/stable/">Documentation for the latest release</a> is hosted on readthedocs.</p>
<p>Run <code>pip install luigi[toml]</code> to install Luigi with <a href="https://luigi.readthedocs.io/en/stable/configuration.html">TOML-based configs</a> support.</p><p>Address of the bookmark: <a href="https://github.com/spotify/luigi" rel="nofollow">https://github.com/spotify/luigi</a></p>]]></description>
	<dc:creator>Neel</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/pages/view/36502/creating-conda-environment-for-python27</guid>
	<pubDate>Mon, 07 May 2018 08:56:52 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/36502/creating-conda-environment-for-python27</link>
	<title><![CDATA[Creating conda environment for python2.7]]></title>
	<description><![CDATA[<p>TIP: By default, environments are installed into the&nbsp;<code><span>envs</span></code>&nbsp;directory in your conda directory. Run&nbsp;<code><span>conda</span>&nbsp;<span>create</span>&nbsp;<span>--help</span></code>&nbsp;for information on specifying a different path.</p><p>Use the Terminal or an Anaconda Prompt for the following steps.</p><ol>
<li>
<p>To create an environment:</p>
<div>
<div>
<pre><span></span><span>conda</span> <span>create</span> <span>--</span><span>name</span> <span>myenv</span>
</pre>
</div>
</div>
<p>NOTE: Replace&nbsp;<code><span>myenv</span></code>&nbsp;with the environment name.</p>
</li>
<li>
<p>When conda asks you to proceed, type&nbsp;<code><span>y</span></code>:</p>
<div>
<div>
<pre><span></span>proceed ([y]/n)?
</pre>
</div>
</div>
</li>
</ol><p>This creates the myenv environment in&nbsp;<code><span>/envs/</span></code>. This environment uses the same version of Python that you are currently using, because you did not specify a version.</p><p>To create an environment with a specific version of Python:</p><div><div><pre><span></span>conda create -n myenv <span>python</span><span>=</span><span>3</span>.4
</pre></div></div><p>To create an environment with a specific package:</p><div><div><pre><span></span>conda create -n myenv scipy
</pre></div></div><p>OR:</p><div><div><pre><span></span>conda create -n myenv python
conda install -n myenv scipy
</pre></div></div><p>To create an environment with a specific version of a package:</p><div><div><pre><span></span>conda create -n myenv <span>scipy</span><span>=</span><span>0</span>.15.0
</pre></div></div><p>OR:</p><div><div><pre><span></span>conda create -n myenv python
conda install -n myenv <span>scipy</span><span>=</span><span>0</span>.15.0
</pre></div></div><p>To create an environment with a specific version of Python and multiple packages:</p><div><div><pre><span></span>conda create -n myenv <span>python</span><span>=</span><span>3</span>.4 <span>scipy</span><span>=</span><span>0</span>.15.0 astroid babel
</pre></div></div><p>TIP: Install all the programs that you want in this environment at the same time. Installing 1 program at a time can lead to dependency conflicts.</p><p>To automatically install pip or another program every time a new environment is created, add the default programs to the&nbsp;<a href="https://conda.io/docs/user-guide/configuration/use-condarc.html#config-add-default-pkgs">create_default_packages</a>&nbsp;section of your&nbsp;<code><span>.condarc</span></code>&nbsp;configuration file. The default packages are installed every time you create a new environment. If you do not want the default packages installed in a particular environment, use the&nbsp;<code><span>--no-default-packages</span></code>&nbsp;flag:</p><div><div><pre><span></span>conda create --no-default-packages -n myenv python
</pre></div></div><p>TIP: You can add much more to the&nbsp;<code><span>conda</span>&nbsp;<span>create</span></code>&nbsp;command. For details, run&nbsp;<code><span>conda</span>&nbsp;<span>create</span>&nbsp;<span>--help</span></code>.</p><p>➜ redundans git:(master) ✗ conda create --name py27 python=2.7<br />Solving environment: done</p><p><br />==&gt; WARNING: A newer version of conda exists. &lt;==<br /> current version: 4.5.0<br /> latest version: 4.5.2</p><p>Please update conda by running</p><p>$ conda update -n base conda</p><p>&nbsp;</p><p>## Package Plan ##</p><p>environment location: /home/urbe/anaconda3/envs/py27</p><p>added / updated specs: <br /> - python=2.7</p><p><br />The following packages will be downloaded:</p><p>package | build<br /> ---------------------------|-----------------<br /> wheel-0.31.0 | py27_0 61 KB<br /> python-2.7.15 | h1571d57_0 12.1 MB<br /> certifi-2018.4.16 | py27_0 142 KB<br /> sqlite-3.23.1 | he433501_0 1.5 MB<br /> setuptools-39.1.0 | py27_0 582 KB<br /> openssl-1.0.2o | h20670df_0 3.4 MB<br /> pip-10.0.1 | py27_0 1.7 MB<br /> ca-certificates-2018.03.07 | 0 124 KB<br /> ------------------------------------------------------------<br /> Total: 19.6 MB</p><p>The following NEW packages will be INSTALLED:</p><p>ca-certificates: 2018.03.07-0 <br /> certifi: 2018.4.16-py27_0 <br /> libedit: 3.1-heed3624_0 <br /> libffi: 3.2.1-hd88cf55_4 <br /> libgcc-ng: 7.2.0-hdf63c60_3 <br /> libstdcxx-ng: 7.2.0-hdf63c60_3 <br /> ncurses: 6.0-h9df7e31_2 <br /> openssl: 1.0.2o-h20670df_0<br /> pip: 10.0.1-py27_0 <br /> python: 2.7.15-h1571d57_0<br /> readline: 7.0-ha6073c6_4 <br /> setuptools: 39.1.0-py27_0 <br /> sqlite: 3.23.1-he433501_0<br /> tk: 8.6.7-hc745277_3 <br /> wheel: 0.31.0-py27_0 <br /> zlib: 1.2.11-ha838bed_2</p><p>Proceed ([y]/n)? y</p><p><br />Downloading and Extracting Packages<br />wheel 0.31.0: #################################################################################################################################################################################################### | 100% <br />python 2.7.15: ################################################################################################################################################################################################### | 100% <br />certifi 2018.4.16: ############################################################################################################################################################################################### | 100% <br />sqlite 3.23.1: ################################################################################################################################################################################################### | 100% <br />setuptools 39.1.0: ############################################################################################################################################################################################### | 100% <br />openssl 1.0.2o: ################################################################################################################################################################################################## | 100% <br />pip 10.0.1: ###################################################################################################################################################################################################### | 100% <br />ca-certificates 2018.03.07: ###################################################################################################################################################################################### | 100% <br />Preparing transaction: done<br />Verifying transaction: done<br />Executing transaction: done<br />#<br /># To activate this environment, use:<br /># &gt; source activate py27<br />#<br /># To deactivate an active environment, use:<br /># &gt; source deactivate<br />#</p><p>➜ redundans git:(master) ✗ source activate py27</p>]]></description>
	<dc:creator>Jit</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>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44179/python-mini-projects</guid>
	<pubDate>Mon, 16 Jan 2023 02:14:03 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44179/python-mini-projects</link>
	<title><![CDATA[Python Mini Projects !]]></title>
	<description><![CDATA[<p><span>There is a directory for each chapter of the book. Each directory contains a&nbsp;</span><code>test.py</code><span>&nbsp;program you can use with&nbsp;</span><code>pytest</code><span>&nbsp;to check that you have written the program correctly. I have included a short README to describe each exercise. If you have problems writing code (or if you would like to support this project!), the book contains details about the skills you need.</span></p>
<p>https://github.com/kyclark/tiny_python_projects</p><p>Address of the bookmark: <a href="https://github.com/kyclark/tiny_python_projects" rel="nofollow">https://github.com/kyclark/tiny_python_projects</a></p>]]></description>
	<dc:creator>BioStar</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/news/view/1737/perl-in-a-day</guid>
	<pubDate>Sat, 10 Aug 2013 21:14:03 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/1737/perl-in-a-day</link>
	<title><![CDATA[Perl in a day !!]]></title>
	<description><![CDATA[<p>This pdf based tutorial in good resource to understand the basic of Perl in a day</p><p><a href="http://ritg.med.harvard.edu/training/perl/RC_Perl_Intro.pdf">http://ritg.med.harvard.edu/training/perl/RC_Perl_Intro.pdf</a></p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
</item>

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