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<channel>
	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/43042?offset=210</link>
	<atom:link href="https://bioinformaticsonline.com/related/43042?offset=210" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
	
<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/10739/science-for-life-laboratory-scilifelab-sweden</guid>
  <pubDate>Sat, 10 May 2014 06:22:30 -0500</pubDate>
  <link></link>
  <title><![CDATA[Science for Life Laboratory (SciLifeLab)-Sweden]]></title>
  <description><![CDATA[
<p>Science for Life Laboratory (SciLifeLab) is a national center for molecular biosciences with focus on health and environmental research. The center combines frontline technical expertise with advanced knowledge of translational medicine and molecular bioscience. SciLifeLab is a national resource and a collaboration between four universities: Karolinska Institutet, KTH Royal Institute of Technology, Stockholm University and Uppsala University.</p>

<p>Webpage : https://www.scilifelab.se/about-us/<br />Opportunity: https://www.scilifelab.se/about-us/career/</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43431/code-golf</guid>
	<pubDate>Wed, 06 Oct 2021 04:17:29 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43431/code-golf</link>
	<title><![CDATA[Code Golf]]></title>
	<description><![CDATA[<p>Code Golf is a game designed to let you show off your code-fu by solving problems in the least number of characters.</p>
<p>Since this is your first time here, I suggest starting with something simple like&nbsp;<a href="https://code.golf/fizz-buzz">Fizz Buzz</a>.</p><p>Address of the bookmark: <a href="https://code.golf/" rel="nofollow">https://code.golf/</a></p>]]></description>
	<dc:creator>Abhi</dc:creator>
</item>

<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/43681/a-guide-to-machine-learning-for-biologists</guid>
	<pubDate>Tue, 28 Dec 2021 01:43:25 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43681/a-guide-to-machine-learning-for-biologists</link>
	<title><![CDATA[A guide to machine learning for biologists]]></title>
	<description><![CDATA[<p>Because of the increasing size and inherent complexity of biological data, there has been an increase in the application of machine learning in biology to create useful and predictive models of the underlying biological processes. All machine learning techniques fit models to data; nevertheless, the specific methods are highly variable and can appear baffling at first glance. In this Review, we hope to give readers a moderate introduction to a few fundamental machine learning techniques, including the most recently created and frequently used deep neural network techniques. We illustrate how different algorithms may be adapted to specific types of biological data, as well as some best practises and points to consider when embarking on machine learning studies. There is also discussion of several upcoming directions in machine learning methodology.</p><p>Address of the bookmark: <a href="https://www.nature.com/articles/s41580-021-00407-0" rel="nofollow">https://www.nature.com/articles/s41580-021-00407-0</a></p>]]></description>
	<dc:creator>Abhi</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/blog/view/44633/learn-python-with-example</guid>
	<pubDate>Tue, 06 Aug 2024 23:51:51 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/44633/learn-python-with-example</link>
	<title><![CDATA[Learn python with example]]></title>
	<description><![CDATA[<div><div><div><p>There are over 21 unique&nbsp;Python project&nbsp;walkthroughs in this content that range from beginner to advanced. See below for the timestamps for these projects:</p><p><span>00:00:00 | How To Navigate These Projects</span><br /><span>---</span><br /><span>00:01:46 | #1 - Quiz Game (Easy)</span><br /><span>Code:&nbsp;</span><a href="https://morioh.com/redirect?id=65b0752318cf2dc4d28010e1&amp;own=5ff684ea1a53c42123416f96&amp;l=https%3A%2F%2Fgithub.com%2Ftechwithtim%2F5-Python-Projects-For-Beginners%2Fblob%2Fmain%2Fquiz_game.py" target="_blank">https://github.com/techwithtim/5-Python-Projects-For-Beginners/blob/main/quiz_game.py</a><span>&nbsp;</span><br /><span>---</span><br /><span>00:22:00 | #2 - Number Guessing Game (Easy)</span><br /><span>Code:&nbsp;</span><a href="https://morioh.com/redirect?id=65b0752318cf2dc4d28010e1&amp;own=5ff684ea1a53c42123416f96&amp;l=https%3A%2F%2Fgithub.com%2Ftechwithtim%2F5-Python-Projects-For-Beginners%2Fblob%2Fmain%2Fnumber_guesser.py" target="_blank">https://github.com/techwithtim/5-Python-Projects-For-Beginners/blob/main/number_guesser.py</a><span>&nbsp;</span><br /><span>---</span><br /><span>00:39:49 | #3 - Rock, Paper, Scissors (Easy)</span><br /><span>Code:&nbsp;</span><a href="https://morioh.com/redirect?id=65b0752318cf2dc4d28010e1&amp;own=5ff684ea1a53c42123416f96&amp;l=https%3A%2F%2Fgithub.com%2Ftechwithtim%2F5-Python-Projects-For-Beginners%2Fblob%2Fmain%2Frock_paper_scissors.py" target="_blank">https://github.com/techwithtim/5-Python-Projects-For-Beginners/blob/main/rock_paper_scissors.py</a><span>&nbsp;</span><br /><span>---</span><br /><span>00:54:40 | #4 - Choose Your Own Adventure Game (Easy)</span><br /><span>Code:&nbsp;</span><a href="https://morioh.com/redirect?id=65b0752318cf2dc4d28010e1&amp;own=5ff684ea1a53c42123416f96&amp;l=https%3A%2F%2Fgithub.com%2Ftechwithtim%2F5-Python-Projects-For-Beginners%2Fblob%2Fmain%2Fchoose_your_own_adventure.py" target="_blank">https://github.com/techwithtim/5-Python-Projects-For-Beginners/blob/main/choose_your_own_adventure.py</a><span>&nbsp;</span><br /><span>---</span><br /><span>01:06:47 | #5 - Password Manager (Medium)</span><br /><span>Code:&nbsp;</span><a href="https://morioh.com/redirect?id=65b0752318cf2dc4d28010e1&amp;own=5ff684ea1a53c42123416f96&amp;l=https%3A%2F%2Fgithub.com%2Ftechwithtim%2F5-Python-Projects-For-Beginners%2F" target="_blank">https://github.com/techwithtim/5-Python-Projects-For-Beginners/</a><span>&nbsp;</span><br /><span>Fernet Cryptography Documentation:&nbsp;</span><a href="https://morioh.com/redirect?id=65b0752318cf2dc4d28010e1&amp;own=5ff684ea1a53c42123416f96&amp;l=https%3A%2F%2Fcryptography.io%2Fen%2Flatest%2Ffernet%2F" target="_blank">https://cryptography.io/en/latest/fernet/</a><span>&nbsp;</span><br /><span>---</span><br /><span>01:37:37 | #6 - PIG (Medium)</span><br /><span>Code:&nbsp;</span><a href="https://morioh.com/redirect?id=65b0752318cf2dc4d28010e1&amp;own=5ff684ea1a53c42123416f96&amp;l=https%3A%2F%2Fgithub.com%2Ftechwithtim%2F3-Mini-Python-Projects%2Fblob%2Fmain%2Fproject1.py" target="_blank">https://github.com/techwithtim/3-Mini-Python-Projects/blob/main/project1.py</a><span>&nbsp;</span><br /><span>---</span><br /><span>01:59:07 | #7 - Madlibs Generator (Medium)</span><br /><span>Code:&nbsp;</span><a href="https://morioh.com/redirect?id=65b0752318cf2dc4d28010e1&amp;own=5ff684ea1a53c42123416f96&amp;l=https%3A%2F%2Fgithub.com%2Ftechwithtim%2F3-Mini-Python-Projects%2Fblob%2Fmain%2Fproject2.py" target="_blank">https://github.com/techwithtim/3-Mini-Python-Projects/blob/main/project2.py</a><span>&nbsp;</span><br /><span>---</span><br /><span>02:15:04 | #8 - Timed Math Challenge (Medium)</span><br /><span>Code:&nbsp;</span><a href="https://morioh.com/redirect?id=65b0752318cf2dc4d28010e1&amp;own=5ff684ea1a53c42123416f96&amp;l=https%3A%2F%2Fgithub.com%2Ftechwithtim%2F3-Mini-Python-Projects%2Fblob%2Fmain%2Fproject3.py" target="_blank">https://github.com/techwithtim/3-Mini-Python-Projects/blob/main/project3.py</a><span>&nbsp;</span><br /><span>---</span><br /><span>02:28:02 | #9 - Slot Machine (Medium)</span><br /><span>Code:&nbsp;</span><a href="https://morioh.com/redirect?id=65b0752318cf2dc4d28010e1&amp;own=5ff684ea1a53c42123416f96&amp;l=https%3A%2F%2Fgithub.com%2Ftechwithtim%2FPython-Slot-Machine" target="_blank">https://github.com/techwithtim/Python-Slot-Machine</a><span>&nbsp;</span><br /><span>---</span><br /><span>03:20:43 | #10 - Turtle Racing (Medium)</span><br /><span>Code:&nbsp;</span><a href="https://morioh.com/redirect?id=65b0752318cf2dc4d28010e1&amp;own=5ff684ea1a53c42123416f96&amp;l=https%3A%2F%2Fgithub.com%2Ftechwithtim%2FTurtle-Racing-V2" target="_blank">https://github.com/techwithtim/Turtle-Racing-V2</a><span>&nbsp;</span><br /><span>Turtle Docs:&nbsp;</span><a href="https://morioh.com/redirect?id=65b0752318cf2dc4d28010e1&amp;own=5ff684ea1a53c42123416f96&amp;l=https%3A%2F%2Fdocs.python.org%2F3%2Flibrary%2Fturtle.html" target="_blank">https://docs.python.org/3/library/turtle.html</a><span>&nbsp;</span><br /><span>---</span><br /><span>04:13:09 | #11 - WPM Typing Test (Medium)</span><br /><span>Code:&nbsp;</span><a href="https://morioh.com/redirect?id=65b0752318cf2dc4d28010e1&amp;own=5ff684ea1a53c42123416f96&amp;l=https%3A%2F%2Fgithub.com%2Ftechwithtim%2FWPM_Typing_Test" target="_blank">https://github.com/techwithtim/WPM_Typing_Test</a><span>&nbsp;</span><br /><span>Curses Docs:&nbsp;</span><a href="https://morioh.com/redirect?id=65b0752318cf2dc4d28010e1&amp;own=5ff684ea1a53c42123416f96&amp;l=https%3A%2F%2Fdocs.python.org%2F3%2Fhowto%2Fcurses.html" target="_blank">https://docs.python.org/3/howto/curses.html</a><span>&nbsp;</span><br /><span>05:09:43 | #12 - Alarm Clock (Easy)</span><br /><span>Python Project Idea Blog:&nbsp;</span><a href="https://morioh.com/redirect?id=65b0752318cf2dc4d28010e1&amp;own=5ff684ea1a53c42123416f96&amp;l=https%3A%2F%2Fhackr.io%2Fblog%2Fpython-projects" target="_blank">https://hackr.io/blog/python-projects</a><span>&nbsp;</span><br /><span>Sound Effects:&nbsp;</span><a href="https://morioh.com/redirect?id=65b0752318cf2dc4d28010e1&amp;own=5ff684ea1a53c42123416f96&amp;l=https%3A%2F%2Fwww.fesliyanstudios.com%2Froyalty-free-sound-effects-download%2Falarm-203" target="_blank">https://www.fesliyanstudios.com/royalty-free-sound-effects-download/alarm-203</a><span>&nbsp;</span><br /><span>---</span><br /><span>05:22:07 | #13 - Password Generator (Easy)</span><br /><span>Python Project Idea Blog:&nbsp;</span><a href="https://morioh.com/redirect?id=65b0752318cf2dc4d28010e1&amp;own=5ff684ea1a53c42123416f96&amp;l=https%3A%2F%2Fhackr.io%2Fblog%2Fpython-projects" target="_blank">https://hackr.io/blog/python-projects</a><span>&nbsp;</span><br /><span>---</span><br /><span>05:39:16 | #14 - Shortest Path Finder (Advanced)</span><br /><span>Code:&nbsp;</span><a href="https://morioh.com/redirect?id=65b0752318cf2dc4d28010e1&amp;own=5ff684ea1a53c42123416f96&amp;l=https%3A%2F%2Fgithub.com%2Ftechwithtim%2F3-Mini-Python-Projects-For-Intermediates%2Fblob%2Fmain%2Fpath-finder.py" target="_blank">https://github.com/techwithtim/3-Mini-Python-Projects-For-Intermediates/blob/main/path-finder.py</a><span>&nbsp;</span><br /><span>---</span><br /><span>06:14:53 | #15 - NBA Stats &amp; Current Scores (Medium)</span><br /><span>Code:&nbsp;</span><a href="https://morioh.com/redirect?id=65b0752318cf2dc4d28010e1&amp;own=5ff684ea1a53c42123416f96&amp;l=https%3A%2F%2Fgithub.com%2Ftechwithtim%2F3-Mini-Python-Projects-For-Intermediates%2Fblob%2Fmain%2Fnba-scores.py" target="_blank">https://github.com/techwithtim/3-Mini-Python-Projects-For-Intermediates/blob/main/nba-scores.py</a><span>&nbsp;</span><br /><span>---</span><br /><span>06:38:22 | #16 - Currency Converter (Medium)</span><br /><span>Code:&nbsp;</span><a href="https://morioh.com/redirect?id=65b0752318cf2dc4d28010e1&amp;own=5ff684ea1a53c42123416f96&amp;l=https%3A%2F%2Fgithub.com%2Ftechwithtim%2F3-Mini-Python-Projects-For-Intermediates%2Fblob%2Fmain%2Fcurrency-converter.py" target="_blank">https://github.com/techwithtim/3-Mini-Python-Projects-For-Intermediates/blob/main/currency-converter.py</a><span>&nbsp;</span><br /><span>API: https://free.currencyconverterapi.com/</span><br /><span>---</span><br /><span>06:58:51 | #17 - YouTube Video Downloader (Medium)</span><br /><span>Code: &nbsp;</span><a href="https://morioh.com/redirect?id=65b0752318cf2dc4d28010e1&amp;own=5ff684ea1a53c42123416f96&amp;l=https%3A%2F%2Fgithub.com%2Ftechwithtim%2FPython-Beginner-Automation-Projects%2Fblob%2Fmain%2Fyoutube.py" target="_blank">https://github.com/techwithtim/Python-Beginner-Automation-Projects/blob/main/youtube.py</a><span>&nbsp;</span><br /><span>---</span><br /><span>07:09:50 | #18 - Automated File Backup (Medium)</span><br /><span>Code:&nbsp;</span><a href="https://morioh.com/redirect?id=65b0752318cf2dc4d28010e1&amp;own=5ff684ea1a53c42123416f96&amp;l=https%3A%2F%2Fgithub.com%2Ftechwithtim%2FPython-Beginner-Automation-Projects%2Fblob%2Fmain%2Fbackup.py" target="_blank">https://github.com/techwithtim/Python-Beginner-Automation-Projects/blob/main/backup.py</a><span>&nbsp;</span><br /><span>---</span><br /><span>07:21:18 | #19 - Mastermind/4 Color Match (Advanced)</span><br /><span>---</span><br /><span>07:48:20 | #20 - Aim Trainer (Advanced)</span><br /><span>Code:&nbsp;</span><a href="https://morioh.com/redirect?id=65b0752318cf2dc4d28010e1&amp;own=5ff684ea1a53c42123416f96&amp;l=https%3A%2F%2Fgithub.com%2Ftechwithtim%2FPython-Aim-Trainer" target="_blank">https://github.com/techwithtim/Python-Aim-Trainer</a><span>&nbsp;</span><br /><span>---</span><br /><span>08:39:20 | #21 - Advanced Python Scripting (Advanced)</span><br /><span>Code:&nbsp;</span><a href="https://morioh.com/redirect?id=65b0752318cf2dc4d28010e1&amp;own=5ff684ea1a53c42123416f96&amp;l=https%3A%2F%2Fgithub.com%2Ftechwithtim%2FPython-Scripting-Project" target="_blank">https://github.com/techwithtim/Python-Scripting-Project</a><span>&nbsp;</span></p></div></div></div>]]></description>
	<dc:creator>BioStar</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/44648/modern-statistics-with-r</guid>
	<pubDate>Thu, 22 Aug 2024 04:44:06 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44648/modern-statistics-with-r</link>
	<title><![CDATA[Modern Statistics with R]]></title>
	<description><![CDATA[<p>This is the online version of the second edition of&nbsp;<em>Modern Statistics with R</em>. It is free to use, and always will be.&nbsp;<a href="https://www.routledge.com/Modern-Statistics-with-R-From-Wrangling-and-Exploring-Data-to-Inference-and-Predictive-Modelling/Thulin/p/book/9781032512440">Printed copies</a>&nbsp;are available from CRC Press.</p>
<p><span>Live&nbsp;<a href="https://statistikakademin.se/in-english-r/">online courses on statistics with R</a></span>&nbsp;based on this book, led by the author, are offered regularly; see&nbsp;<a href="https://statistikakademin.se/in-english-r/">this page</a>&nbsp;for more information and dates.</p>
<p>The past decades have transformed the world of statistical data analysis, with new methods, new types of data, and new computational tools. The aim of&nbsp;<em>Modern Statistics with R</em>&nbsp;is to introduce you to key parts of the modern statistical toolkit. It teaches you:</p>
<ul>
<li><span>Data wrangling</span>&nbsp;- importing, formatting, reshaping, merging, and filtering data in R.</li>
<li><span>Exploratory data analysis</span>&nbsp;- using visualisations and multivariate techniques to explore datasets.</li>
<li><span>Statistical inference</span>&nbsp;- modern methods for testing hypotheses and computing confidence intervals.</li>
<li><span>Predictive modelling</span>&nbsp;- regression models and machine learning methods for prediction, classification, and forecasting.</li>
<li><span>Simulation</span>&nbsp;- using simulation techniques for sample size computations and evaluations of statistical methods.</li>
<li><span>Ethics in statistics</span>&nbsp;- ethical issues and good statistical practice.</li>
<li><span>R programming</span>&nbsp;- writing code that is fast, readable, and (hopefully!) free from bugs.</li>
</ul>
<p>The book includes plenty of examples and more than 200 exercises with worked solutions.&nbsp;<a href="http://www.modernstatisticswithr.com/data.zip">The datasets used for the examples and the exercises can be downloaded here.</a></p><p>Address of the bookmark: <a href="https://www.modernstatisticswithr.com/" rel="nofollow">https://www.modernstatisticswithr.com/</a></p>]]></description>
	<dc:creator>LEGE</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/43631/pangolin-tutorial</guid>
	<pubDate>Fri, 10 Dec 2021 05:58:59 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43631/pangolin-tutorial</link>
	<title><![CDATA[Pangolin tutorial !]]></title>
	<description><![CDATA[<p><span>This is a tutorial for using the Pangolin Web Application. For information on using the command line tool, please visit the&nbsp;</span><a href="https://cov-lineages.org/resources/pangolin/usage.html">command line tool usage page</a><span>.</span></p>
<p>https://cov-lineages.org/resources/pangolin/tutorial.html</p><p>Address of the bookmark: <a href="https://cov-lineages.org/resources/pangolin/tutorial.html" rel="nofollow">https://cov-lineages.org/resources/pangolin/tutorial.html</a></p>]]></description>
	<dc:creator>Abhi</dc:creator>
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