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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/27477?offset=470</link>
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	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41571/wego-simple-but-useful-tool-for-visualizing-comparing-and-plotting-go-gene-ontology-annotation-results</guid>
	<pubDate>Sun, 12 Apr 2020 10:02:22 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41571/wego-simple-but-useful-tool-for-visualizing-comparing-and-plotting-go-gene-ontology-annotation-results</link>
	<title><![CDATA[WEGO : simple but useful tool for visualizing, comparing and plotting GO (Gene Ontology) annotation results]]></title>
	<description><![CDATA[<p><span>WEGO (Web Gene Ontology Annotation Plot) is a simple but useful tool for visualizing, comparing and plotting GO (Gene Ontology) annotation results. As the GO vocabulary became more and more popular, WEGO was widely adopted and used in many researches. Therefore we have updated WEGO 2.0 in 2018. Here are some changes we&rsquo;ve made:</span><br><span>1. The limit of input file numbers was cancelled. Now the users could upload as many files as they want with one operation.</span><br><span>2. We have added the reference data of 9 species for users selection.</span><br><span>3. Besides the traditional WEGO histogram, WEGO 2.0 outputs an additional type of bar graph showing GO terms with significant gene number differences.</span></p><p>Address of the bookmark: <a href="http://wego.genomics.org.cn/" rel="nofollow">http://wego.genomics.org.cn/</a></p>]]></description>
	<dc:creator>BioStar</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/44188/understanding-go-analysis</guid>
	<pubDate>Wed, 08 Feb 2023 04:22:01 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44188/understanding-go-analysis</link>
	<title><![CDATA[Understanding GO analysis]]></title>
	<description><![CDATA[<p>The confusion about gene ontology and gene ontology analysis can start right from the term itself. There are actually two different entities that are commonly referred to as gene ontology or &ldquo;GO&rdquo;:</p>
<ol>
<li>the&nbsp;<span>ontology itself</span>, which is a set of terms with their precise definitions and defined relationships between them, and</li>
<li>the&nbsp;<span>associations between gene products and GO terms</span>, which are used to capture the existing knowledge about what each gene is known to do.</li>
</ol>
<p>But the term gene ontology, or GO, is commonly used to refer to both, which is sometimes a source of potential confusion. In order to avoid this, here we will use the term &ldquo;GO ontology&rdquo; to describe the set of terms and their hierarchical structure and &ldquo;GO annotations&rdquo; to describe the set of associations between genes and GO terms.</p>
<p>There are 3 types of terms, or domains if you wish, in the gene ontology:</p>
<ul>
<li>Biological Processes (BP)</li>
<li>Molecular Functions (MF)</li>
<li>Cellular Components (CC)</li>
</ul><p>Address of the bookmark: <a href="https://advaitabio.com/faq-items/understanding-gene-ontology/" rel="nofollow">https://advaitabio.com/faq-items/understanding-gene-ontology/</a></p>]]></description>
	<dc:creator>Neel</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/bookmarks/view/32868/pollux-platform-independent-error-correction-of-single-and-mixed-genomes</guid>
	<pubDate>Fri, 19 May 2017 09:41:27 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/32868/pollux-platform-independent-error-correction-of-single-and-mixed-genomes</link>
	<title><![CDATA[Pollux: platform independent error correction of single and mixed genomes]]></title>
	<description><![CDATA[<p><span>Pollux: General-purpose error corrector that corrects errors introduced by Illumina, Ion Torrent, and Roche 454 sequencing technologies and can be applied to single- or mixed-genome data. In addition to correcting substitution errors, we locate and correct insertion, deletion, and homopolymer errors while remaining sensitive to low coverage areas of sequencing projects. Using published data sets, we correct 94% of Illumina MiSeq errors, 88% of Ion Torrent PGM errors, 85% of Roche 454 GS Junior errors. Introduced errors are 20 to 70 times more rare than successfully corrected errors. Furthermore, we show that the quality of assemblies improves when reads are corrected by our software.</span></p>
<p><span>https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-014-0435-6</span></p><p>Address of the bookmark: <a href="https://github.com/emarinier/pollux" rel="nofollow">https://github.com/emarinier/pollux</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<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.
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Subscribe to our channel: http://www.youtube.com/user/TEDtalksDirector]]></description>
	
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44313/orthovenn3-an-integrated-platform-for-exploring-and-visualizing-orthologous-data-across-genomes</guid>
	<pubDate>Tue, 02 May 2023 00:48:28 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44313/orthovenn3-an-integrated-platform-for-exploring-and-visualizing-orthologous-data-across-genomes</link>
	<title><![CDATA[OrthoVenn3: an integrated platform for exploring and visualizing orthologous data across genomes]]></title>
	<description><![CDATA[<p><span>OrthoVenn3 is a powerful tool for comparative genomics analysis, used as a web server for full genome comparisons, annotation, and evolutionary analysis of orthologous clusters across multiple species. It has already been used by thousands of users from over 60 countries.</span></p><p>Address of the bookmark: <a href="https://orthovenn3.bioinfotoolkits.net/" rel="nofollow">https://orthovenn3.bioinfotoolkits.net/</a></p>]]></description>
	<dc:creator>Abhi</dc:creator>
</item>

<item>
  <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>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34579/moss-a-system-for-detecting-software-similarity</guid>
	<pubDate>Sat, 09 Dec 2017 08:59:07 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34579/moss-a-system-for-detecting-software-similarity</link>
	<title><![CDATA[MOSS: A System for Detecting Software Similarity]]></title>
	<description><![CDATA[<p><span>Moss (for a Measure Of Software Similarity) is an automatic system for determining the similarity of programs. To date, the main application of Moss has been in detecting plagiarism in programming classes. Since its development in 1994, Moss has been very effective in this role. The algorithm behind moss is a significant improvement over other cheating detection algorithms (at least, over those known to us).</span></p>
<p><span><span>Moss can currently analyze code written in the following languages:</span></span></p>
<p>C, C++, Java, C#, Python, Visual Basic, Javascript, FORTRAN, ML, Haskell, Lisp, Scheme, Pascal, Modula2, Ada, Perl, TCL, Matlab, VHDL, Verilog, Spice, MIPS assembly, a8086 assembly, a8086 assembly, MIPS assembly, HCL2.</p><p>Address of the bookmark: <a href="https://theory.stanford.edu/~aiken/moss/" rel="nofollow">https://theory.stanford.edu/~aiken/moss/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37813/evidentialgene-tr2aacds-mrna-transcript-assembly-software</guid>
	<pubDate>Mon, 01 Oct 2018 13:13:24 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37813/evidentialgene-tr2aacds-mrna-transcript-assembly-software</link>
	<title><![CDATA[EvidentialGene: tr2aacds, mRNA Transcript Assembly Software]]></title>
	<description><![CDATA[<p><span>Quality assessment of this mRNA Transcript Assembly Software is described in&nbsp;</span><a href="http://arthropods.eugenes.org/EvidentialGene/about/EvidentialGene_quality.html">EvidentialGene_quality</a><span>.</span></p>
<p>Too many transcript assemblies is much better than too few. It allows one then to apply biological criteria to pick out the best ones. Don't be misled by the "right number" of transcripts that one or other transcript assembler may produce. It is the "right sequence" you want, and now the only way to get it is to produce way too many assemblies on a good RNA data set, with several methods and several parameter settings.</p><p>Address of the bookmark: <a href="https://sourceforge.net/p/evidentialgene/blog/" rel="nofollow">https://sourceforge.net/p/evidentialgene/blog/</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>

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