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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/35798?offset=510</link>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/10773/bioinformatics-jrfsrf-position-at-national-research-centre-on-plant-biotechnology</guid>
  <pubDate>Sun, 11 May 2014 22:29:12 -0500</pubDate>
  <link></link>
  <title><![CDATA[Bioinformatics JRF/SRF position at NATIONAL RESEARCH CENTRE ON PLANT BIOTECHNOLOGY]]></title>
  <description><![CDATA[
<p>NATIONAL RESEARCH CENTRE ON PLANT BIOTECHNOLOGY<br />LBS, CENTRE, PUSA CAMPUS, IARI NEW DELHI<br />NEW DELHI – 110 012</p>

<p>WALK- IN –INTERVIEWS</p>

<p>Eligible candidates may appear in Walk-in-Interview on May 23, 2014 at 10 AM for the posts of Research Associates &amp; Senior Research Fellows (SRF) in the following DST/DBT/ICAR funded projects.</p>

<p>1 NPTC Project on Bioinformatics and Comparative Genomics</p>

<p>Research Associate (One)</p>

<p>Rs. 24000/- + 30% HRA for masters degree holder with more than 4 years experience</p>

<p>Essential: Ph D in Plant Molecular Biology &amp; Biotechnology/Genetics 0r Candidates who have already submitted their Ph D thesis in above subjects</p>

<p>Desirable: Research experience in Genomics, Molecular biology, Microarrays analysis, Gene cloning, transgenic Techniques , and computational analysis.</p>

<p>Senior Research Fellow ( UGCCSIR/ DBT/ ICAR Net qualified only): (One)</p>

<p>Rs. 16000/- + 30% HRA and Rs. 18000+30 HRA from 3rd year onwards</p>

<p>Essential:</p>

<p>1. ICAR/ UGCCSIR/DBT Net qualified only</p>

<p>2. M. Sc. (with thesis) in Biotechnology, Life Sciences, Biosciences/ Bioinformatics, Genetics/ Plant Pathology with experience in molecular biology.</p>

<p>Or M.Sc with more than 3 years research experiences</p>

<p>3. B.Sc. Agriculture or Biology</p>

<p>Desirable:<br />1. M. Sc. with thesis<br />2. Experience in molecular biology, plant tissue culture<br />3. Bioinformatics knowledge is important</p>

<p>2 DST JC Bose National Fellowship</p>

<p>Research Associate (Bioinformatics) : One</p>

<p>Rs.22000/- + 30% HRA for 1 &amp; 2nd Yr., Rs. 23000+ 30% HRA for 3rd year and Rs. 24000+30% HRA for 4th &amp;5th yr</p>

<p>Essential: M Ph D in Plant Molecular Biology &amp; Biotechnology/Genetics</p>

<p>Desirable: Research experience in Genomics, Molecular biology, Microarrays analysis, Gene cloning, transgenic Techniques , and computational analysis.</p>

<p>Age limit: Max.35 years (Age relaxation of 5 years for SC/ST &amp; women and 3 years for OBC)</p>

<p>The posts are purely temporary in nature and are co-terminus with the project. Initially the offer will be made for one year only and may be further extendable based on performance of the candidate. The interview will be held on May 23 , 2014 at 10:00 AM at NRCPB, LBS Building, Pusa Campus, IARI, New Delhi- 110012. The candidates must bring four copies of biodata (in the prescribed proforma), original certificates, attested photocopies of each of the certificates and an attested copy of recent passport size photograph. No. TA/DA would be given for the appearance in interview. Only the candidates having essential qualification would be entertained for the interviews. Short-listing of candidates based on academic merit and experience will be done in case of large number of applicants.</p>

<p>Advertisement: http://www.nrcpb.org/sites/default/files/Advertisement%20for%20RA%20and%20SRF%20Position.pdf</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/videolist/watch/12943/a-history-of-bioinformatics-in-the-year-2039</guid>
	<pubDate>Wed, 23 Jul 2014 06:37:51 -0500</pubDate>
	<link>https://bioinformaticsonline.com/videolist/watch/12943/a-history-of-bioinformatics-in-the-year-2039</link>
	<title><![CDATA[A History of Bioinformatics (in the Year 2039)]]></title>
	<description><![CDATA[<iframe width="" height="" src="https://www.youtube-nocookie.com/embed/uwsjwMO-TEA" frameborder="0" allowfullscreen></iframe><p>C. Titus Brown http://video.open-bio.org/video/1/a-history-of-bioinformatics-in-the-year-2039</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/news/view/11144/scientists-map-17294-proteins-produced-in-human-body</guid>
	<pubDate>Thu, 29 May 2014 01:57:55 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/11144/scientists-map-17294-proteins-produced-in-human-body</link>
	<title><![CDATA[Scientists map 17,294 proteins produced in human body]]></title>
	<description><![CDATA[<p>Indian scientists missed the genomic profiling bus, but they've more than made up for it by creating the first human proteome map which is an extension of the genomic study. Till now, here is no direct equivalent for the human proteome. But recently two groups present mass spectrometry-based analysis of human tissues, body fluids and cells mapping the large majority of the human proteome.</p><p>The Indian scientists working in Bangalore, along with their American counterparts, have mapped more than 17,000 proteins in 30 organs of the human body. Just like the human genome was sequenced around the turn of the millennium, this is an equivalent mapping of the human proteome.<br /><br />The researcher estimated there are around 20,500 proteins in the human body. These scientists have profiled around 17,294, which account for around 84% of the total proteins. Apart from this, the team also traced around 2,500 of 3,000 proteins that had been categorised as "missing proteins".</p><p>The work, done by group of Indian scientists, and Johns Hopkins University, published in the renowned journal Nature ( http://www.nature.com/nature/journal/v509/n7502/full/nature13302.html ). Of the 72 people who worked on the project, 46 are Indians.</p><p>Reference:</p><p>http://www.nature.com/nature/journal/v509/n7502/full/nature13302.html</p><p>http://www.proteinatlas.org/ -The antibody-based Human Protein Atlas programme</p><p>http://www.humanproteomemap.org/ -Proteogenomic analysis by identifying translated proteins from annotated pseudogenes, non-coding RNAs and untranslated regions.</p><p>https://www.proteomicsdb.org/ -Assembled protein evidence for 18,097 genes in ProteomicsDB</p><p>&nbsp;</p>]]></description>
	<dc:creator>Jit</dc:creator>
</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>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/videolist/watch/11249/how-to-sequence-the-human-genome-mark-j-kiel</guid>
	<pubDate>Fri, 30 May 2014 13:24:11 -0500</pubDate>
	<link>https://bioinformaticsonline.com/videolist/watch/11249/how-to-sequence-the-human-genome-mark-j-kiel</link>
	<title><![CDATA[How to sequence the human genome - Mark J. Kiel]]></title>
	<description><![CDATA[<iframe width="" height="" src="https://www.youtube-nocookie.com/embed/MvuYATh7Y74" frameborder="0" allowfullscreen></iframe>View full lesson: http://ed.ted.com/lessons/how-to-sequence-the-human-genome-mark-j-kiel

Your genome, every human's genome, consists of a unique DNA sequence of A's, T's, C's and G's that tell your cells how to operate. Thanks to technological advances, scientists are now able to know the sequence of letters that makes up an individual genome relatively quickly and inexpensively. Mark J. Kiel takes an in-depth look at the science behind the sequence.

Lesson by Mark J. Kiel, animation by Marc Christoforidis.]]></description>
	
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<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>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/videolist/watch/11354/genomics-and-personalized-medicine</guid>
	<pubDate>Sun, 01 Jun 2014 23:38:42 -0500</pubDate>
	<link>https://bioinformaticsonline.com/videolist/watch/11354/genomics-and-personalized-medicine</link>
	<title><![CDATA[Genomics and Personalized Medicine]]></title>
	<description><![CDATA[<iframe width="" height="" src="https://www.youtube-nocookie.com/embed/pgHAXCMMcro" frameborder="0" allowfullscreen></iframe>(October 20, 2009) Michael Snyder, Professor of Genetics and Chair of the Department of Genetics at Stanford, discusses advances in gene sequencing, the impact of genomics on medicine, the potential for personalized medicine. and efforts at Stanford to further study these issues.

Stanford Mini Med School is a series arranged and directed by Stanford's School of Medicine, and presented by the Stanford Continuing Studies program. Featuring more than thirty distinguished, faculty, scientists and physicians from Stanford's medical school, the series offers students a dynamic introduction to the world of human biology, health and disease, and the groundbreaking changes taking place in medical research and health care.

Stanford University
http://www.stanford.edu

Stanford University School of Medicine
http://med.stanford.edu

Stanford Continuing Studies
http://continuingstudies.stanford.edu

Stanford University Channel on YouTube:
http://www.youtube.com/stanford]]></description>
	
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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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