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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/39307?</link>
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	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/10925/a-brief-bioinformatics-tutorial</guid>
	<pubDate>Wed, 21 May 2014 12:50:09 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/10925/a-brief-bioinformatics-tutorial</link>
	<title><![CDATA[A Brief Bioinformatics Tutorial]]></title>
	<description><![CDATA[<p>This is about how to use a computer to find what is known about a gene of interest and also how to get new insights about it.</p>
<p>The tutorial is divided in three main parts:</p>
<ul>
<li>In the <strong>Sequence </strong>part, you will see how to look efficiently for a particular protein sequence, how to blast it against the database of your choice to find homologues, how to perform a multiple alignment of the homologues you've selected and how to edit this alignment.</li>
<li>The <strong>Structure </strong>part is about molecular visualization, homology modeling and structural domain prediction.</li>
<li>In the <strong>Function </strong>part, you will be introduced to you 3 useful servers to investigate the function of a protein. i.e. finding interactors, co-expressed genes, see a phylogenetic profile, easily access papers citing your gene etc ...</li>
</ul>
<p>During all the three parts, we will use the <em>S. cerevisiae </em>VPS36 protein as an example.</p><p>Address of the bookmark: <a href="http://www.mrc-lmb.cam.ac.uk/rlw/text/bioinfo_tuto/introduction.html" rel="nofollow">http://www.mrc-lmb.cam.ac.uk/rlw/text/bioinfo_tuto/introduction.html</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<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>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/videolist/watch/14218/pimp-your-brain-bioinformatics</guid>
	<pubDate>Wed, 20 Aug 2014 22:09:21 -0500</pubDate>
	<link>https://bioinformaticsonline.com/videolist/watch/14218/pimp-your-brain-bioinformatics</link>
	<title><![CDATA[Pimp your brain: Bioinformatics]]></title>
	<description><![CDATA[<iframe width="" height="" src="https://www.youtube-nocookie.com/embed/KqelGy6Q8nE" frameborder="0" allowfullscreen></iframe>Jan Lisec from the Max Planck Institute of Molecular Plant Physiology explains, in this "pimp your brain" episode, what bioinformatics is and why bioinformatics is so important and indispensable for biological research.

In the video serial "Pimp your brain" scientists from the Max Planck Institute of Molecular Plant Physiology describe their research. More videos from the 'Pimp your brain' serial are available on www.youtube.com/playlist?list=PL-l9VItC9Gn2Ur2Xj6PTOAkjLUlVPbIOO

More videos are available on www.mpimp-golm.mpg.de]]></description>
	
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43863/snakemake-tutorials</guid>
	<pubDate>Mon, 09 May 2022 05:20:41 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43863/snakemake-tutorials</link>
	<title><![CDATA[Snakemake Tutorials !]]></title>
	<description><![CDATA[<p>A lesson introducing the Snakemake workflow system for bioinformatics analysis.</p>
<blockquote>
<h2 id="prerequisites">Prerequisites<a href="https://carpentries-incubator.github.io/snakemake-novice-bioinformatics/index.html#prerequisites"></a></h2>
<p>This is an intermediate lesson and assumes learners have already done some bioinformatics:</p>
<ul>
<li>Familiarity with the BASH command shell, including concepts like pipes, variables and loops.</li>
<li>Knowledge of bioinformatics fundamentals like the FASTQ file format and transcriptome sequencing, in order to understand the example workflow.</li>
</ul>
<p>No previous knowledge of Snakemake or workflow systems is required.</p>
<p>https://carpentries-incubator.github.io/snakemake-novice-bioinformatics/index.html</p>
</blockquote><p>Address of the bookmark: <a href="https://carpentries-incubator.github.io/snakemake-novice-bioinformatics/aio/index.html" rel="nofollow">https://carpentries-incubator.github.io/snakemake-novice-bioinformatics/aio/index.html</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/33398/tiny-python36-notebook</guid>
	<pubDate>Sat, 03 Jun 2017 03:16:28 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/33398/tiny-python36-notebook</link>
	<title><![CDATA[Tiny Python3.6 Notebook]]></title>
	<description><![CDATA[<p><span>This is not so much an instructional manual, but rather notes, tables, and examples for Python syntax. It was created by the author as an additional resource during training, meant to be distributed as a physical notebook. Participants (who favor the physical characteristics of dead tree material) could add their own notes, thoughts, and have a valuable reference of curated examples.</span></p><p>Address of the bookmark: <a href="https://github.com/mattharrison/Tiny-Python-3.6-Notebook/blob/master/python.rst" rel="nofollow">https://github.com/mattharrison/Tiny-Python-3.6-Notebook/blob/master/python.rst</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42552/bioinformatics-workbook</guid>
	<pubDate>Tue, 05 Jan 2021 22:42:32 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42552/bioinformatics-workbook</link>
	<title><![CDATA[bioinformatics workbook]]></title>
	<description><![CDATA[<p><span>This books assumes that the reader has some knowledge of biology and basic understanding of the Unix command line. However, for the beginner, the appendix contains introductory material and tips/tricks for common bioinformatic problems, that is referred to for more information throughout the book.</span></p>
<p>https://bioinformaticsworkbook.org/</p><p>Address of the bookmark: <a href="https://bioinformaticsworkbook.org/" rel="nofollow">https://bioinformaticsworkbook.org/</a></p>]]></description>
	<dc:creator>biogeek</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/35534/awk-for-bioinformatician-and-computational-biologist</guid>
	<pubDate>Tue, 06 Feb 2018 14:54:35 -0600</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/35534/awk-for-bioinformatician-and-computational-biologist</link>
	<title><![CDATA[Awk for Bioinformatician and computational biologist]]></title>
	<description><![CDATA[<p>Awk is a programming language which allows easy manipulation of structured data and is mostly used for pattern scanning and processing. It searches one or more files to see if they contain lines that match with the specified patterns and then perform associated actions. The basic syntax is:</p><blockquote><p><br />awk '/pattern1/ {Actions}<br /> /pattern2/ {Actions}' file</p></blockquote><p><br />The working of Awk is as follows<br />Awk reads the input files one line at a time.<br />For each line, it matches with given pattern in the given order, if matches performs the corresponding action.<br />If no pattern matches, no action will be performed.<br />In the above syntax, either search pattern or action are optional, But not both.<br />If the search pattern is not given, then Awk performs the given actions for each line of the input.<br />If the action is not given, print all that lines that matches with the given patterns which is the default action.<br />Empty braces with out any action does nothing. It wont perform default printing operation.<br />Each statement in Actions should be delimited by semicolon.<br />Say you have data.tsv with the following contents:</p><p><br />$ cat data/test.tsv<br />contig1 ACTGTCTGTCACTGTGTTGTGATGTTGTGTGTG<br />contig2 ACTTTATATATT<br />contig3 ACTTATATATATATA<br />contig4 ACTTATATATATATA<br />contig5 ACTTTATATATT <br />By default Awk prints every line from the file.</p><p><br />$ awk '{print;}' data/test.tsv<br />contig1 ACTGTCTGTCACTGTGTTGTGATGTTGTGTGTG<br />contig2 ACTTTATATATT<br />contig3 ACTTATATATATATA<br />contig4 ACTTATATATATATA<br />contig5 ACTTTATATATT <br />We print the line which matches the pattern contig3</p><p><br />$ awk '/contig3/' data/test.tsv<br />contig3 ACTTATATATATATA<br />Awk has number of builtin variables. For each record i.e line, it splits the record delimited by whitespace character by default and stores it in the $n variables. If the line has 5 words, it will be stored in $1, $2, $3, $4 and $5. $0 represents the whole line. NF is a builtin variable which represents the total number of fields in a record.</p><p><br />$ awk '{print $1","$2;}' data/test.tsv<br />contig1,ACTGTCTGTCACTGTGTTGTGATGTTGTGTGTG<br />contig2,ACTTTATATATT<br />contig3,ACTTATATATATATA<br />contig4,ACTTATATATATATA<br />contig5,ACTTTATATATT</p><p>$ awk '{print $1","$NF;}' data/test.tsv<br />contig1,ACTGTCTGTCACTGTGTTGTGATGTTGTGTGTG<br />contig2,ACTTTATATATT<br />contig3,ACTTATATATATATA<br />contig4,ACTTATATATATATA<br />contig5,ACTTTATATATT</p><p><br />Awk has two important patterns which are specified by the keyword called BEGIN and END. The syntax is as follows:</p><blockquote><p>BEGIN { Actions before reading the file}<br />{Actions for everyline in the file} <br />END { Actions after reading the file }</p></blockquote><p><br />For example,<br />$ awk 'BEGIN{print "Header,Sequence"}{print $1","$2;}END{print "-------"}' data/test.tsv<br />Header,Sequence<br />contig1,ACTGTCTGTCACTGTGTTGTGATGTTGTGTGTG<br />contig2,ACTTTATATATT<br />contig3,ACTTATATATATATA<br />contig4,ACTTATATATATATA<br />contig5,ACTTTATATATT<br />------- <br />We can also use the concept of a conditional operator in print statement of the form print CONDITION ? PRINT_IF_TRUE_TEXT : PRINT_IF_FALSE_TEXT. For example, in the code below, we identify sequences with lengths &gt; 14:</p><p>$ awk '{print (length($2)&gt;14) ? $0"&gt;14" : $0"&lt;=14";}' data/test.tsv<br />contig1 ACTGTCTGTCACTGTGTTGTGATGTTGTGTGTG&gt;14<br />contig2 ACTTTATATATT&lt;=14<br />contig3 ACTTATATATATATA&gt;14<br />contig4 ACTTATATATATATA&gt;14<br />contig5 ACTTTATATATT&lt;=14<br />We can also use 1 after the last block {} to print everything (1 is a shorthand notation for {print $0} which becomes {print} as without any argument print will print $0 by default), and within this block, we can change $0, for example to assign the first field to $0 for third line (NR==3), we can use:</p><p>$ awk 'NR==3{$0=$1}1' data/test.tsv<br />contig1 ACTGTCTGTCACTGTGTTGTGATGTTGTGTGTG<br />contig2 ACTTTATATATT<br />contig3<br />contig4 ACTTATATATATATA<br />contig5 ACTTTATATATT<br />You can have as many blocks as you want and they will be executed on each line in the order they appear, for example, if we want to print $1 three times (here we are using printf instead of print as the former doesn't put end-of-line character),</p><p>$ awk '{printf $1"\t"}{printf $1"\t"}{print $1}' data/test.tsv<br />contig1 contig1 contig1<br />contig2 contig2 contig2<br />contig3 contig3 contig3<br />contig4 contig4 contig4<br />contig5 contig5 contig5 <br />Although, we can also skip executing later blocks for a given line by using next keyword:</p><p>$ awk '{printf $1"\t"}NR==3{print "";next}{print $1}' data/test.tsv<br />contig1 contig1<br />contig2 contig2<br />contig3 <br />contig4 contig4<br />contig5 contig5</p><p>$ awk 'NR==3{print "";next}{printf $1"\t"}{print $1}' data/test.tsv<br />contig1 contig1<br />contig2 contig2</p><p>contig4 contig4<br />contig5 contig5<br />You can also use getline to load the contents of another file in addition to the one you are reading, for example, in the statement given below, the while loop will load each line from test.tsv into k until no more lines are to be read:</p><p>$ awk 'BEGIN{while((getline k &lt;"data/test.tsv")&gt;0) print "BEGIN:"k}{print}' data/test.tsv<br />BEGIN:contig1 ACTGTCTGTCACTGTGTTGTGATGTTGTGTGTG<br />BEGIN:contig2 ACTTTATATATT<br />BEGIN:contig3 ACTTATATATATATA<br />BEGIN:contig4 ACTTATATATATATA<br />BEGIN:contig5 ACTTTATATATT<br />contig1 ACTGTCTGTCACTGTGTTGTGATGTTGTGTGTG<br />contig2 ACTTTATATATT<br />contig3 ACTTATATATATATA<br />contig4 ACTTATATATATATA<br />contig5 ACTTTATATATT <br />You can also store data in the memory with the syntax VARIABLE_NAME[KEY]=VALUE which you can later use through for (INDEX in VARIABLE_NAME) command:</p><p>$ awk '{i[$1]=1}END{for (j in i) print j"&lt;="i[j]}' data/test.tsv<br />contig1&lt;=1<br />contig2&lt;=1<br />contig3&lt;=1<br />contig4&lt;=1<br />contig5&lt;=1</p>]]></description>
	<dc:creator>Poonam Mahapatra</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/35144/converting-fastq-to-fasta</guid>
	<pubDate>Fri, 12 Jan 2018 03:49:09 -0600</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/35144/converting-fastq-to-fasta</link>
	<title><![CDATA[Converting FASTQ to FASTA]]></title>
	<description><![CDATA[<div id="block-system-main"><div><div><div><div><div><div><p>There are several ways you can convert fastq to fasta sequences. Some methods are listed below.</p><h3>Using SED</h3><p><span><code><span>sed</span></code></span>&nbsp;can be used to selectively print the desired lines from a file, so if you print the first and 2rd line of every 4 lines, you get the sequence header and sequence needed for fasta format.</p><pre>sed -n '1~4s/^@/&gt;/p;2~4p' INFILE.fastq &gt; OUTFILE.fasta
</pre><h3>Using PASTE</h3><p>You can linerize every 4 lines in a tabular format and print first and second field using&nbsp;<span><code>paste</code></span></p><pre>cat INFILE.fastq | paste - - - - |cut -f 1, 2| sed 's/@/&gt;/'g | tr -s "/t" "/n" &gt; OUTFILE.fasta
</pre><h3>EMBOSS:seqret</h3><p>Standard script that can be used for many purposes. One such use is fastq-fasta conversion</p><pre>seqret -sequence reads.fastq -outseq reads.fasta
</pre><p><span><code><span>awk</span></code></span>&nbsp;can be used for conversion as follows:</p><h3>Using AWK</h3><pre>cat infile.fq | awk '{if(NR%4==1) {printf("&gt;%s\n",substr($0,2));} else if(NR%4==2) print;}' &gt; file.fa
</pre><h3>FASTX-toolkit</h3><p><span><code>fastq_to_fasta</code></span>&nbsp;is available in the FASTX-toolkit that scales really well with the huge datasets</p><pre>fastq_to_fasta -h
usage: fastq_to_fasta [-h] [-r] [-n] [-v] [-z] [-i INFILE] [-o OUTFILE]
# Remember to use -Q33 for illumina reads!
version 0.0.6
       [-h]         = This helpful help screen.
       [-r]         = Rename sequence identifiers to numbers.
       [-n]         = keep sequences with unknown (N) nucleotides.
                   Default is to discard such sequences.
       [-v]         = Verbose - report number of sequences.
                   If [-o] is specified,  report will be printed to STDOUT.
                   If [-o] is not specified (and output goes to STDOUT),
                   report will be printed to STDERR.
       [-z]         = Compress output with GZIP.
       [-i INFILE]  = FASTA/Q input file. default is STDIN.
       [-o OUTFILE] = FASTA output file. default is STDOUT.
</pre><h3>Bioawk</h3><p>Another option to convert fastq to fasta format using&nbsp;<span><code>bioawk</code></span></p><pre>bioawk -c fastx '{print "&gt;"$name"\n"$seq}' input.fastq &gt; output.fasta
</pre><h3>Seqtk</h3><p>From the same developer, there is another option using a tool called&nbsp;<span><code>seqtk</code></span></p><pre>seqtk seq -a input.fastq &gt; output.fasta
</pre><p>Note that you can use either compressed or uncompressed files for this tool</p></div></div></div></div></div></div></div>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/28200/machine-learning</guid>
	<pubDate>Fri, 01 Jul 2016 12:57:12 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/28200/machine-learning</link>
	<title><![CDATA[Machine Learning !!!]]></title>
	<description><![CDATA[<p>In machine learning, computers apply&nbsp;<strong>statistical learning</strong>&nbsp;techniques to automatically identify patterns in data. These techniques can be used to make highly accurate predictions.</p>
<p><em>Keep scrolling.</em>&nbsp;Using a data set about homes, we will create a machine learning model to distinguish homes in New York from homes in San Francisco.</p><p>Address of the bookmark: <a href="http://www.r2d3.us/visual-intro-to-machine-learning-part-1/" rel="nofollow">http://www.r2d3.us/visual-intro-to-machine-learning-part-1/</a></p>]]></description>
	<dc:creator>Gudiya Pal</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/35798/an-introduction-to-applied-bioinformatics</guid>
	<pubDate>Fri, 02 Mar 2018 04:26:38 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/35798/an-introduction-to-applied-bioinformatics</link>
	<title><![CDATA[An Introduction to Applied Bioinformatics]]></title>
	<description><![CDATA[<p>IAB is primarily being developed by&nbsp;<a href="http://caporasolab.us/people/greg-caporaso/">Greg Caporaso</a>(GitHub/Twitter:&nbsp;<a href="https://github.com/gregcaporaso">@gregcaporaso</a>) in the&nbsp;<a href="http://www.caporasolab.us/">Caporaso Lab</a>&nbsp;at&nbsp;<a href="http://www.nau.edu/">Northern Arizona University</a>. You can find information on the courses I teach on&nbsp;<a href="http://www.caporasolab.us/teaching">my teaching website</a>&nbsp;and information on my research and lab on&nbsp;<a href="http://www.caporasolab.us/">my lab website</a>.</p>
<p>&nbsp;</p><p>Address of the bookmark: <a href="http://readiab.org/" rel="nofollow">http://readiab.org/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

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