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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/44279?offset=370</link>
	<atom:link href="https://bioinformaticsonline.com/related/44279?offset=370" rel="self" type="application/rss+xml" />
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<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/12593/visiting-scientist-computational-genomics-two-positions</guid>
  <pubDate>Mon, 07 Jul 2014 22:53:41 -0500</pubDate>
  <link></link>
  <title><![CDATA[Visiting Scientist - Computational Genomics (two positions)]]></title>
  <description><![CDATA[
<p>Scientific/Managerial &amp; International Recruitment</p>

<p>ICRISAT seeks applications from Indian nationals Visiting Scientist-Computational Genomics (2 positions), to be part of a team of Centre of Excellence in Genomics (CEG), (www.icrisat.org/ceg) to work on legume genomics projects.  The positions will be based at ICRISAT’s Headquarters in Patancheru, Hyderabad, India.</p>

<p>ICRISAT is a non-profit, non-political organization that conducts agricultural research for development in Asia and sub-Saharan Africa with a wide array of partners throughout the world. Covering 6.5 million square kilometers of land in 55 countries, the semi-arid tropics is home to over 2 billion people, with 650 million of these are the poorest of the poor. ICRISAT and its partners help empower those living in the semi-arid tropics, especially smallholder farmers, to overcome poverty, hunger, malnutrition and a degraded environment through more efficient and profitable agriculture. ICRISAT is headquartered in Greater Hyderabad, Andhra Pradesh, India and belongs to the Consortium of Centers supported by the Consultative Group on International Agricultural Research (CGIAR).</p>

<p>The Job: Responsibilities for these positions include:</p>

<p>    Analyzing and handling large-scale next generation sequencing DNA and RNA data<br />    Data mining and development of pipelines and troubleshooting<br />    Genome diversity analysis such as SNPs, Indels, Structural Variations, population structure<br />    Genome wide association study (GWAS) related analysis- LD analysis, hapmap and trait mapping<br />    Expression analysis based on RNA-Seq data, annotation, gene ontology and metabolic pathway analysis<br />    Epigenome analysis, small RNA identification<br />    Gene family analysis, sequence level protein analysis, orthology/paralogy and molecular modelling<br />    Compiling and analysis of results, writing reports and research papers</p>

<p>The Person:  Ph.D. or MSc/MTech/PGDCA with two years research experience in Biotechnology, Computational biology, Agricultural/ Plant Biotechnology, Genetics, Molecular Biology or related discipline. Good knowledge of programming/scripting in at least two of following languages: Perl, C, C++, R, Shell Scripting and Python is plus.</p>

<p>How to apply: Please apply latest by 20 July 2014.  The application should include the name of the position applied for, a letter of motivation, a full Curriculum Vita (CV), and the names and contact information of three references that are knowledgeable of the candidate’s professional qualifications and work experience. Technical details and more information about these positions can be obtained from R.K.VARSHNEY@CGIAR.ORG. All applications will be acknowledged, however only short listed candidates will be contacted.</p>

<p>Apply here https://recruit.zoho.com/ats/Portal.na?digest=T642sgLYWZOStExJ77cPrcM*sIMGZETWw4yPxngbmHA-</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/bookmarks/view/11030/r-programming-and-jobs-website</guid>
	<pubDate>Sun, 25 May 2014 14:43:57 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/11030/r-programming-and-jobs-website</link>
	<title><![CDATA[R programming and Jobs website]]></title>
	<description><![CDATA[<p>Welcome to the R Jobs section of ProgrammingR.com. If your organization has an R employment opportunity that you would like to have posted here, submit it via the <a href="http://www.programmingr.com/contact" title="contact page">contact page</a>. Prospective employees: use the contact information provided in the position listing to apply or contact the hiring organization.</p><p>Address of the bookmark: <a href="http://www.programmingr.com/category/stype/r-job-listings/" rel="nofollow">http://www.programmingr.com/category/stype/r-job-listings/</a></p>]]></description>
	<dc:creator>Pragati Singh</dc:creator>
</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/pages/view/11181/perl-one-liner-for-bioinformatician</guid>
	<pubDate>Fri, 30 May 2014 05:49:07 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/11181/perl-one-liner-for-bioinformatician</link>
	<title><![CDATA[Perl one-liner for bioinformatician !!!]]></title>
	<description><![CDATA[<p>With the emergence of NGS technologies, and sequencing data most of the bioinformaticians mung and wrangle around massive amounts of genomics text. There are several "standardized" file formats (FASTQ, SAM, VCF, etc.) and some tools for manipulating them (fastx toolkit, samtools, vcftools, etc.), there are still times where knowing a little bit of Perl onliner is extremely helpful.</p><p>Perl one-liners are small and awesome Perl programs that fit in a single line of code and they do one thing really well. These things include changing line spacing, numbering lines, doing calculations, converting and substituting text, deleting and printing certain lines, parsing logs, editing files in-place, doing statistics, carrying out system administration tasks, updating a bunch of files at once, and many more. Perl one-liners will make you the shell warrior. Anything that took you minutes to solve, will now take you seconds!<br /><br />perl -pe '$\="\n"'&nbsp; &nbsp;<br />#double space a file<br /><br />perl -pe '$_ .= "\n" unless /^$/' <br />#double space a file except blank lines<br /><br />perl -pe '$_.="\n"x7' <br />#7 space in a line.<br /><br />perl -ne 'print unless /^$/' <br />#remove all blank lines<br /><br />perl -lne 'print if length($_) &lt; 20' <br />#print all lines with length less than 20.<br /><br />perl -00 -pe '' <br />#If there are multiple spaces, delete all leaving one(make the file a single spaced file).<br /><br />perl -00 -pe '$_.="\n"x4' <br />#Expand single blank lines into 4 consecutive blank lines<br /><br />perl -pe '$_ = "$. $_"'<br />#Number all lines in a file<br /><br />perl -pe '$_ = ++$a." $_" if /./' <br />#Number only non-empty lines in a file<br /><br />perl -ne 'print ++$a." $_" if /./' <br />#Number and print only non-empty lines in a file<br /><br />perl -pe '$_ = ++$a." $_" if /regex/' <br />#Number only lines that match a pattern<br /><br />perl -ne 'print ++$a." $_" if /regex/' <br />#Number and print only lines that match a pattern<br /><br />perl -ne 'printf "%-5d %s", $., $_ if /regex/' <br />#Left align lines with 5 white spaces if matches a pattern (perl -ne 'printf "%-5d %s", $., $_' : for all the lines)<br /><br />perl -le 'print scalar(grep{/./}&lt;&gt;)' <br />#prints the total number of non-empty lines in a file<br /><br />perl -lne '$a++ if /regex/; END {print $a+0}' <br />#print the total number of lines that matches the pattern<br /><br />perl -alne 'print scalar @F' <br />#print the total number fields(words) in each line.<br /><br />perl -alne '$t += @F; END { print $t}' <br />#Find total number of words in the file<br /><br />perl -alne 'map { /regex/ &amp;&amp; $t++ } @F; END { print $t }' <br />#find total number of fields that match the pattern<br /><br />perl -lne '/regex/ &amp;&amp; $t++; END { print $t }' <br />#Find total number of lines that match a pattern<br /><br />perl -le '$n = 20; $m = 35; ($m,$n) = ($n,$m%$n) while $n; print $m' <br />#will calculate the GCD of two numbers.<br /><br />perl -le '$a = $n = 20; $b = $m = 35; ($m,$n) = ($n,$m%$n) while $n; print $a*$b/$m' <br />#will calculate lcd of 20 and 35.<br /><br />perl -le '$n=10; $min=5; $max=15; $, = " "; print map { int(rand($max-$min))+$min } 1..$n' <br />#Generates 10 random numbers between 5 and 15.<br /><br />perl -le 'print map { ("a".."z",&rdquo;0&rdquo;..&rdquo;9&rdquo;)[rand 36] } 1..8'<br />#Generates a 8 character password from a to z and number 0 &ndash; 9.<br /><br />perl -le 'print map { ("a",&rdquo;t&rdquo;,&rdquo;g&rdquo;,&rdquo;c&rdquo;)[rand 4] } 1..20'<br />#Generates a 20 nucleotide long random residue.<br /><br />perl -le 'print "a"x50'<br />#generate a string of &lsquo;x&rsquo; 50 character long<br /><br />perl -le 'print join ", ", map { ord } split //, "hello world"'<br />#Will print the ascii value of the string hello world.<br /><br />perl -le '@ascii = (99, 111, 100, 105, 110, 103); print pack("C*", @ascii)'<br />#converts ascii values into character strings.<br /><br />perl -le '@odd = grep {$_ % 2 == 1} 1..100; print "@odd"'<br />#Generates an array of odd numbers.<br /><br />perl -le '@even = grep {$_ % 2 == 0} 1..100; print "@even"'<br />#Generate an array of even numbers<br /><br />perl -lpe 'y/A-Za-z/N-ZA-Mn-za-m/' file <br />#Convert the entire file into 13 characters offset(ROT13)<br /><br />perl -nle 'print uc' <br />#Convert all text to uppercase:<br /><br />perl -nle 'print lc' <br />#Convert text to lowercase:<br /><br />perl -nle 'print ucfirst lc' <br />#Convert only first letter of first word to uppercas<br /><br />perl -ple 'y/A-Za-z/a-zA-Z/' <br />#Convert upper case to lower case and vice versa<br /><br />perl -ple 's/(\w+)/\u$1/g' <br />#Camel Casing<br /><br />perl -pe 's|\n|\r\n|' <br />#Convert unix new lines into DOS new lines:<br /><br />perl -pe 's|\r\n|\n|' <br />#Convert DOS newlines into unix new line<br /><br />perl -pe 's|\n|\r|' <br />#Convert unix newlines into MAC newlines:<br /><br />perl -pe '/regexp/ &amp;&amp; s/foo/bar/' <br />#Substitute a foo with a bar in a line with a regexp.</p><p>Reference/Sources:</p><p>http://genomics-array.blogspot.in/2010/11/some-unixperl-oneliners-for.html</p><p><a href="http://genomespot.blogspot.com/2013/08/a-selection-of-useful-bash-one-liners.html">http://genomespot.blogspot.com/2013/08/a-selection-of-useful-bash-one-liners.html</a></p><p><a href="http://biowize.wordpress.com/2012/06/15/command-line-magic-for-your-gene-annotations/">http://biowize.wordpress.com/2012/06/15/command-line-magic-for-your-gene-annotations/</a></p><p><a href="http://genomics-array.blogspot.com/2010/11/some-unixperl-oneliners-for.html">http://genomics-array.blogspot.com/2010/11/some-unixperl-oneliners-for.html</a></p><p><a href="http://bioexpressblog.wordpress.com/2013/04/05/split-multi-fasta-sequence-file/">http://bioexpressblog.wordpress.com/2013/04/05/split-multi-fasta-sequence-file/</a></p>]]></description>
	<dc:creator>Abhimanyu Singh</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/11311/stephen-friend-the-hunt-for-unexpected-genetic-heroes</guid>
	<pubDate>Sat, 31 May 2014 14:31:47 -0500</pubDate>
	<link>https://bioinformaticsonline.com/videolist/watch/11311/stephen-friend-the-hunt-for-unexpected-genetic-heroes</link>
	<title><![CDATA[Stephen Friend: The hunt for "unexpected genetic heroes"]]></title>
	<description><![CDATA[<iframe width="" height="" src="https://www.youtube-nocookie.com/embed/Yagdvqn2YMU" frameborder="0" allowfullscreen></iframe>What can we learn from people with the genetics to get sick — who don't? With most inherited diseases, only some family members will develop the disease, while others who carry the same genetic risks dodge it. Stephen Friend suggests we start studying those family members who stay healthy. Hear about the Resilience Project, a massive effort to collect genetic materials that may help decode inherited disorders.

TEDTalks is a daily video podcast of the best talks and performances from the TED Conference, where the world's leading thinkers and doers give the talk of their lives in 18 minutes (or less). Look for talks on Technology, Entertainment and Design -- plus science, business, global issues, the arts and much more.
Find closed captions and translated subtitles in many languages at http://www.ted.com/translate

Follow TED news on Twitter: http://www.twitter.com/tednews
Like TED on Facebook: https://www.facebook.com/TED

Subscribe to our channel: http://www.youtube.com/user/TEDtalksDirector]]></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>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/12896/inspire-faculty-scheme-a-component-of-%E2%80%9Cassured-opportunity-for-research-career-aorc%E2%80%9D-under-inspire</guid>
  <pubDate>Sat, 19 Jul 2014 14:59:30 -0500</pubDate>
  <link></link>
  <title><![CDATA[INSPIRE Faculty Scheme: a component of “Assured Opportunity for Research Career (AORC)” under INSPIRE.]]></title>
  <description><![CDATA[
<p>Ministry of Science and Technology, Department of Science and Technology</p>

<p>7th ADVERTISEMENT – 2014 (2)</p>

<p>INSPIRE Faculty Scheme: a component of “Assured Opportunity for Research Career (AORC)” under INSPIRE.</p>

<p>The Department of Science and Technology, Government of India, has launched the “Innovation in Science Pursuit for Inspired Research (INSPIRE)” [http://www.inspire-dst.gov.in] program in 2008.</p>

<p>The program aims to attract talent for study of science and careers with research. INSPIRE includes many components. The importance of Assured Career Opportunity in R&amp;D sector has been recognized.</p>

<p>INSPIRE Faculty Scheme opens up an “Assured Opportunity for Research Career (AORC)” for young researchers in the age group of 27-32 years. It offers a contractual research awards to young achievers and opportunity for independent research in the near term and emerge as a future leader in the long term.</p>

<p>Eligibility</p>

<p>Essential Indian citizens and people of Indian origin including NRI/PIO status with PhD (in science, mathematics, engineering, pharmacy, medicine, and agriculture related subjects) from any recognized university in the world,</p>

<p>Those who have submitted their PhD Theses and are awaiting award of the degree are also<br />eligible. However, the award will be conveyed only after confirmation of the awarding the<br />PhD degree.</p>

<p>The upper age limit as on 1st July 2014 should be 32 years for considering support for a<br />period of 5 years. However, for SC and ST candidates, upper age limit will be 35 years.</p>

<p>Publication(s) in highly reputed Journals demonstrating research potential of the candidate.</p>

<p>Desirable</p>

<p>Candidates who are within top 1% at the School Leaving Examination, IIT-JEE rank, 1st Rank Holder either in graduation or post-graduation level university examination (which are used presently for identifying INSPIRE Scholars at under-graduate level and INSPIRE Fellows for doctoral degree)</p>

<p>More at http://www.inspire-dst.gov.in/faculty_scheme.html</p>
]]></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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