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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/23892?offset=670</link>
	<atom:link href="https://bioinformaticsonline.com/related/23892?offset=670" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
	
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/10739/science-for-life-laboratory-scilifelab-sweden</guid>
  <pubDate>Sat, 10 May 2014 06:22:30 -0500</pubDate>
  <link></link>
  <title><![CDATA[Science for Life Laboratory (SciLifeLab)-Sweden]]></title>
  <description><![CDATA[
<p>Science for Life Laboratory (SciLifeLab) is a national center for molecular biosciences with focus on health and environmental research. The center combines frontline technical expertise with advanced knowledge of translational medicine and molecular bioscience. SciLifeLab is a national resource and a collaboration between four universities: Karolinska Institutet, KTH Royal Institute of Technology, Stockholm University and Uppsala University.</p>

<p>Webpage : https://www.scilifelab.se/about-us/<br />Opportunity: https://www.scilifelab.se/about-us/career/</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/44930/bioinformatics-the-bridge-between-curiosity-and-discovery</guid>
	<pubDate>Mon, 24 Nov 2025 05:16:49 -0600</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/44930/bioinformatics-the-bridge-between-curiosity-and-discovery</link>
	<title><![CDATA[Bioinformatics: The Bridge Between Curiosity and Discovery]]></title>
	<description><![CDATA[<p>In the sprawling universe of modern science, bioinformatics stands as one of the most transformative and empowering fields of our time. It is where biology meets computation, where data becomes meaning, and where curiosity becomes discovery. If you&rsquo;ve stepped into this world&mdash;or are considering it&mdash;here&rsquo;s your reminder: you&rsquo;re part of a revolution.</p><p><strong>Why Bioinformatics Matters More Than Ever</strong></p><p>Every day, our world generates massive amounts of biological data&mdash;from genome sequences to microbiome profiles to real-time pathogen surveillance. Hidden within these datasets are the answers to some of the greatest challenges humanity faces: emerging diseases, antimicrobial resistance, environmental stress, genetic disorders, sustainable agriculture, and more.</p><p>Bioinformatics isn&rsquo;t just a skill.<br />It&rsquo;s the language of the future of biology.</p><p>By mastering it, you give yourself the power to:</p><p>Decode genomes and understand life at its most fundamental level</p><p>Identify patterns no microscope could ever reveal</p><p>Predict disease outbreaks before they occur</p><p>Accelerate drug discovery with computational precision</p><p>Contribute to open-source tools that empower scientists worldwide</p><p>You don&rsquo;t just follow science&mdash;you drive it.</p><p><strong>Every Expert Was Once a Beginner</strong></p><p>Many newcomers feel intimidated. Command-line interfaces. R scripts. Python packages. Next-generation sequencing data. Complex machine learning models.</p><p>But here&rsquo;s the truth: every bioinformatician started exactly where you are now&mdash;curious, unsure, but excited.</p><p>No one writes perfect code on day one.</p><p>No one understands genomics pipelines immediately.</p><p>What makes you a bioinformatician is not perfection, but perseverance.</p><p>When your script throws a cryptic error&hellip;<br />When your data refuses to format&hellip;<br />When your pipeline runs for 6 hours only to crash&hellip;</p><p>Remember: this is part of the journey.<br />Every error teaches you. Every retry strengthens you. Every breakthrough energizes you.</p><p>Bioinformatics Is Not Just a Career&mdash;It&rsquo;s a Mindset</p><p>It&rsquo;s the mindset of:</p><p>Problem-solving.</p><p>Continuous learning.</p><p>Turning chaos into clarity.</p><p>Seeing what others can&rsquo;t.</p><p>Bioinformaticians are detectives of biological complexity. You sit at the intersection of innovation, using tools that can shape public health, medicine, agriculture, and ecology. Few fields give you such direct impact on the world.</p><p><strong>Your Contribution Matters</strong></p><p>As you work on your script, pipeline, genome, or model, remember:</p><p>Somewhere, your analysis might contribute to:</p><p>A new therapy</p><p>A faster diagnostic test</p><p>A better understanding of a pathogen</p><p>A more resilient crop</p><p>An open-source dataset that helps thousands</p><p>A discovery that rewrites textbooks</p><p>Your code may be small, but its ripple effect is powerful.</p><p>The Future Is Bioinformatics&mdash;And You Are Part of It</p><p>The world is shifting. Wet labs are integrating AI. Hospitals rely on genomic insights. Farmers use gene-level predictions. Governments monitor disease in real time. Students launch pipelines that become global tools.</p><p>This is a golden era&mdash;and you are not late.<br />You are exactly where you need to be.</p><p>Keep Pushing. Keep Learning. Keep Discovering.</p><p>Bioinformatics is a journey filled with challenges, but also with unmatched rewards.</p><p>So the next time you feel stuck, frustrated, or overwhelmed, remember:<br />You&rsquo;re building the science of tomorrow.</p><p>Be proud. Stay curious. Keep going.<br />Your work matters more than you think.</p>]]></description>
	<dc:creator>BioStar</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40786/google-colab-google-colab-is-a-free-cloud-service-and-now-it-supports-free-gpu</guid>
	<pubDate>Fri, 31 Jan 2020 01:31:23 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40786/google-colab-google-colab-is-a-free-cloud-service-and-now-it-supports-free-gpu</link>
	<title><![CDATA[Google Colab : Google Colab is a free cloud service and now it supports free GPU!]]></title>
	<description><![CDATA[<p><strong>You</strong>&nbsp;can: improve your Python programming language coding skills. develop deep learning applications using popular libraries such as Keras, TensorFlow, PyTorch, and OpenCV.&nbsp;</p>
<p><span><span>If you have just a single notebook to submit, use the website&nbsp;<a href="https://google-colab.com/">https://google-colab.com/</a>, it is really easy, on the top right corner click 'submit +'. The earlier you post the more visibility you will get over time</span></span></p><p>Address of the bookmark: <a href="http://colab.research.google.com" rel="nofollow">http://colab.research.google.com</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/videolist/watch/4094/manufacturing-life-with-j-craig-venter</guid>
	<pubDate>Thu, 29 Aug 2013 08:52:26 -0500</pubDate>
	<link>https://bioinformaticsonline.com/videolist/watch/4094/manufacturing-life-with-j-craig-venter</link>
	<title><![CDATA[Manufacturing Life with J. Craig Venter]]></title>
	<description><![CDATA[<iframe width="" height="" src="https://www.youtube-nocookie.com/embed/PKtozMvSsBk" frameborder="0" allowfullscreen></iframe>J. Craig Venter, CEO of Synthetic Genomics, talks about finding genomic-driven solutions to address global needs such as new sources of energy, food and vaccines in an interview with James Bennet, Editor-in-Chief of The Atlantic. This program is introduced by Pradeep Khosla, the new chancellor of the University of California, San Diego.  Series: "The Atlantic Meets The Pacific" [11/2012] [Public Affairs] [Show ID: 24359]
The Atlantic Meets the Pacific playlist: http://goo.gl/5V8Yb
The Atlantic Meets the Pacific on UCTV: http://www.uctv.tv/atlanticpacific
UCTV: http://www.uctv.tv]]></description>
	
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/11107/the-minerva-research-group-for-bioinformatics</guid>
  <pubDate>Tue, 27 May 2014 15:48:14 -0500</pubDate>
  <link></link>
  <title><![CDATA[The Minerva Research Group for Bioinformatics]]></title>
  <description><![CDATA[
<p>The focus of the bioinformatics group is to use computational approaches to gain an insight into genome evolution in primates.</p>

<p>http://www.eva.mpg.de/genetics/bioinformatics/overview.html?Fsize=0%2C%20%40%2F%27</p>

<p>Kelso Group<br />Department of Evolutionary Genetics<br />Max Planck Institute for Evolutionary Anthropology<br />Deutscher Platz 6<br />04103 Leipzig<br />Germany<br />Phone: +49 341 3550 500</p>

<p>Job: <br />http://www.eva.mpg.de/genetics/bioinformatics/jobs.html?Fsize=0%2C%2B%40</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/19272/translate2r</guid>
	<pubDate>Fri, 21 Nov 2014 01:16:06 -0600</pubDate>
	<link>https://bioinformaticsonline.com/news/view/19272/translate2r</link>
	<title><![CDATA[translate2R]]></title>
	<description><![CDATA[<p>After their presentation at the international &ldquo;user!&rdquo; conference, data analysis specialist <a href="http://www.eoda.de/en/" target="_blank">eoda</a> starts the public alpha testing of <a href="http://www.eoda.de/en/translate2R.html" target="_blank">translate2R</a>. With the start of alpha testing the innovative migration solution by the company hailing from Kassel discards the working title &ldquo;translateR&rdquo; and takes on the final product brand name &ldquo;translate2R&rdquo;. translate2R is a service for the automated translation of SPSS&reg; syntax to R code, therefore supporting data analysts with a quick and low-risk migration to R.</p><p>The manual translation of many, frequently rather complex SPSS scripts often presents itself as a tedious and error-prone task, and represents a rather large obstacle for many analysts and companies to migrate to a modern, open source data management and analysis tool like R. With translate2R this hurdle will be diminished substantially.</p><p>Find at https://service.eoda.de/translater/?lang=en</p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/36191/bioinformatics-workshops-no-coding-required</guid>
	<pubDate>Mon, 09 Apr 2018 13:06:01 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/36191/bioinformatics-workshops-no-coding-required</link>
	<title><![CDATA[Bioinformatics Workshops - NO CODING REQUIRED]]></title>
	<description><![CDATA[<p><img src="https://edu.t-bio.info/wp-content/uploads/2018/03/t-bioinfo-bioinformatics-workshops.jpg" alt="Bioinformatics Workshops T-BioInfo" width="568" height="319" style="vertical-align: middle; border: 0px;"></p><p>Pine Biotech, Inc., a US-based startup working with the Tauber Bioinformatics Research Center is offering a full curriculum online preparing students without any technical background for real-life challenges with large scale biomedical data. Workshops on processing, analysis and biomedical interpretation of Next Generation Sequencing data cover important up-to-date algorithms and machine learning approaches. The most important thing is that there are virtually no pre-requisites such as coding, biostatistics or advanced medical skills. If you know what gene is and how the genes are expressed, you are ready to take the courses or join our workshops. Learn more:&nbsp;https://edu.t-bio.info/workshops/</p>]]></description>
	<dc:creator>eliabrodsky</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/37592/benchmarking-perl-module</guid>
	<pubDate>Sat, 25 Aug 2018 11:40:42 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/37592/benchmarking-perl-module</link>
	<title><![CDATA[Benchmarking Perl Module !]]></title>
	<description><![CDATA[<p>The benchmark module is a great tool to know the time the code takes to run. The output is usually in terms of CPU time. This module provides us with a way to optimize our code. With the advent of petascale computing and other multicore processor it is becoming a neccesity to know about the CPU time taken by our perl program.</p><p>This is the simple way to use the module</p><blockquote><p>Example1:</p><p>use Benchmark;</p><p>$first_time = Benchmark-&gt;new;</p><p>our code&hellip;&hellip;</p><p>$second_time = Benchmark-&gt;new;</p><p>$final_difference = timediff($first_time,$second_time);</p><p>print &ldquo;the code took, timestr($final_difference),&rdquo;\n&rdquo;;</p></blockquote><p>that was a very simple way to know the time diff , we can use it to know the time taken by some part of the code in the program.</p><blockquote><p>More sophisticated way:</p><p>use Benchmark;<br />sub first {</p><p>my(arguments) = @_;</p><p>}</p><p>timethese(100, { first =&gt; &lsquo;first_sub(arguments)&rsquo;});</p><p>The first argument to timethese is 100 (evaluate 100 times).</p></blockquote><p>Hope this very small tutorial with Benchmark will help people get started.</p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/42003/perl-one-liner-for-beginners</guid>
	<pubDate>Fri, 24 Jul 2020 05:58:28 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/42003/perl-one-liner-for-beginners</link>
	<title><![CDATA[Perl one-liner for beginners !]]></title>
	<description><![CDATA[<p>I often use the following arguments to perl:</p><ul>
<li>-e Makes the line of code be executed instead of a script</li>
<li>-n Forces your line to be called in a loop. Allows you to take lines from the diamond operator (or stdin)</li>
<li>-p Forces your line to be called in a loop. Prints $_ at the end</li>
</ul><p>&nbsp;</p><ul>
<li>This counts the number of quotation marks in each line and prints it
<div>
<blockquote>
<div>perl -ne&nbsp;'$cnt = tr/"//;print "$cnt\n"'&nbsp;inputFileName.txt</div>
</blockquote>
</div>
</li>
</ul><ul>
<li>Adds string to each line, followed by tab
<div>
<blockquote>
<div>perl -pe&nbsp;'s/(.*)/string\t$1/'&nbsp;inFile &gt; outFile</div>
</blockquote>
</div>
</li>
</ul><ul>
<li>Append a new line to each line
<div>
<blockquote>
<div>perl -pe&nbsp;'s//\n/'&nbsp;all.sent.classOnly &gt; all.sent.classOnly.sep</div>
</blockquote>
</div>
</li>
</ul><ul>
<li>Replace all occurrences of pattern1 (e.g. [0-9]) with pattern2
<div>
<blockquote>
<div>perl -p -i.bak -w -e&nbsp;'s/pattern1/pattern2/g'&nbsp;inputFile</div>
</blockquote>
</div>
</li>
</ul><ul>
<li>Go through file and only print words that do not have any uppercase letters.
<div>
<blockquote>
<div>perl -ne&nbsp;'print unless m/[A-Z]/'&nbsp;allWords.txt &gt; allWordsOnlyLowercase.txt</div>
</blockquote>
</div>
</li>
</ul><ul>
<li>Go through file, split line at each space and print words one per line.
<div>
<blockquote>
<div>perl -ne&nbsp;'print join("\n", split(/ /,$_));print("\n")'&nbsp;someText.txt &gt; wordsPerLine.txt</div>
</blockquote>
</div>
</li>
</ul><ul>
<li>or in other words, delete every character that is not a letter, white space or line end (replace with nothing)
<div>
<blockquote>
<div>perl -pne&nbsp;'s/[^a-zA-Z\s]*//g'&nbsp;text_withSpecial.txt &gt; text_lettersOnly.txt</div>
</blockquote>
</div>
</li>
</ul><ul>
<li>
<div>
<div>perl -pne&nbsp;'tr/[A-Z]/[a-z]/'&nbsp;textWithUpperCase.txt &gt; textwithoutuppercase.txt;</div>
</div>
</li>
</ul><ul>
<li>Print only the second column of the data when using tabular as a separator
<div>
<blockquote>
<div>perl -ne&nbsp;'@F = split("\t", $_); print "$F[1]";'&nbsp;columnFileWithTabs.txt &gt; justSecondColumn.txt</div>
</blockquote>
</div>
</li>
</ul><ul>
<li>
<div>One-Liner: Sort lines by their length
<blockquote>
<div>perl -e&nbsp;'print sort {length $a &lt;=&gt; length $b} &lt;&gt;'&nbsp;textFile</div>
</blockquote>
</div>
</li>
</ul><ul>
<li>One-Liner: Print second column, unless it contains a number
<blockquote>
<div>perl"&gt;perl -lane&nbsp;'print $F[1] unless $F[1] =~ m/[0-9]/'&nbsp;wordCounts.txt</div>
</blockquote>
</li>
</ul>]]></description>
	<dc:creator>BioStar</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38378/gwaspro-a-high-performance-genome-wide-association-analysis-server</guid>
	<pubDate>Fri, 07 Dec 2018 08:04:57 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38378/gwaspro-a-high-performance-genome-wide-association-analysis-server</link>
	<title><![CDATA[GWASpro: A High-Performance Genome-Wide Association Analysis Server]]></title>
	<description><![CDATA[<p>GWASpro supports building complex design matrices, by which complex experimental designs that may include replications, treatments, locations and times, can be accounted for in the linear mixed model (LMM). GWASpro is optimized to handle GWAS data that may consist of up to 10 million markers and 10,000 samples from replicable lines or hybrids. GWASpro provides an interface that significantly reduces the learning curve for new GWAS investigators.</p>
<p>&nbsp;</p><p>Address of the bookmark: <a href="https://bioinfo.noble.org/GWASPRO/" rel="nofollow">https://bioinfo.noble.org/GWASPRO/</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
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