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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/30701?offset=1330</link>
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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/2457/rdataminingcom-r-and-data-mining</guid>
	<pubDate>Thu, 15 Aug 2013 18:37:23 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/2457/rdataminingcom-r-and-data-mining</link>
	<title><![CDATA[Rdatamining.com : R and Data Mining]]></title>
	<description><![CDATA[<p>This website presents examples, documents and resources on data mining with R. <br>Documents on using R for data mining are available to download for non-commercial personal use, including&nbsp;R Reference card for Data Mining, R and Data Mining: Examples and Case Studies and Time Series Analysis and Mining with R.</p><p>Address of the bookmark: <a href="http://www.rdatamining.com/" rel="nofollow">http://www.rdatamining.com/</a></p>]]></description>
	<dc:creator>Poonam Mahapatra</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/33960/mgra-breakpoint-graphs-and-ancestral-genome-reconstructions</guid>
	<pubDate>Tue, 25 Jul 2017 08:48:25 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/33960/mgra-breakpoint-graphs-and-ancestral-genome-reconstructions</link>
	<title><![CDATA[MGRA: Breakpoint graphs and ancestral genome reconstructions]]></title>
	<description><![CDATA[<p>MGRA (Multiple Genome Rearrangements and Ancestors) is a tool for reconstruction of ancestor genomes and evolutionary history of extant genomes.</p>
<p>It takes as an input a set of genomes represented as sequences of genes (or synteny blocks) and produces such sequences for ancestral genomes at the internal nodes of the phylogenetic tree.</p>
<p>The phylogenetic tree may be also specified completely or partially, in the latter case MGRA can reconstruct conserved ancestral regions (CARs) of the ancestral genome of interest.</p>
<p>Since version 2 MGRA supports gene insertion and deletions in addition to genome rearrangements and allows the input genomes to have different gene content.</p>
<p>It also can reconstruct most plausible phylogenetic tree based on the rearrangement characters.</p><p>Address of the bookmark: <a href="http://mgra.cblab.org/" rel="nofollow">http://mgra.cblab.org/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/2573/most-commonly-used-awk-by-bioinformatician</guid>
	<pubDate>Mon, 19 Aug 2013 01:12:38 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/2573/most-commonly-used-awk-by-bioinformatician</link>
	<title><![CDATA[Most Commonly used Awk by Bioinformatician]]></title>
	<description><![CDATA[<p style="text-align: center;">&nbsp;</p><p>Awk is a programming language that is specifically designed for quickly manipulating space delimited data. Although you can achieve all its functionality with Perl, awk is simpler in many practical cases.</p><p>Why awk? You can replace a pipeline of 'stuff | grep | sed | cut...' with a single call to awk. For a simple script, most of the timelag is in loading these apps into memory, and it's much faster to do it all with one. This is ideal for something like an openbox pipe menu where you want to generate something on the fly. You can use awk to make a neat one-liner for some quick job in the terminal, or build an awk section into a shell script. You can find a lot of online tutorials, but here I will only show a few examples which cover most of bioinformatician daily uses of awk.</p><p>choose rows where column 3 is larger than column 5:</p><p>awk '$3&gt;$5' input.txt &gt; output.txt</p><p>extract column 2,4,5:</p><p>awk '{print $2,$4,$5}' input.txt &gt; output.txt</p><p>awk 'BEGIN{OFS="\t"}{print $2,$4,$5}' input.txt</p><p>show rows between 20th and 80th:</p><p>awk 'NR&gt;=20&amp;&amp;NR&lt;=80' input.txt &gt; output.txt</p><p>calculate the average of column 2:</p><p>awk '{x+=$2}END{print x/NR}' input.txt</p><p>regex (egrep):</p><p>awk '/^test[0-9]+/' input.txt</p><p>calculate the sum of column 2 and 3 and put it at the end of a row or replace the first column:</p><p>awk '{print $0,$2+$3}' input.txt</p><p>awk '{$1=$2+$3;print}' input.txt</p><p>join two files on column 1:</p><p>awk 'BEGIN{while((getline&lt;"file1.txt")&gt;0)l[$1]=$0}$1 in l{print $0"\t"l[$1]}' file2.txt &gt; output.txt</p><p>count number of occurrence of column 2 (uniq -c):</p><p>awk '{l[$2]++}END{for (x in l) print x,l[x]}' input.txt</p><p>apply "uniq" on column 2, only printing the first occurrence (uniq):</p><p>awk '!($2 in l){print;l[$2]=1}' input.txt</p><p>count different words (wc):</p><p>awk '{for(i=1;i!=NF;++i)c[$i]++}END{for (x in c) print x,c[x]}' input.txt</p><p>deal with simple CSV:</p><p>awk -F, '{print $1,$2}'</p><p>substitution (sed is simpler in this case):</p><p>awk '{sub(/test/, "no", $0);print}' input.txt</p><p>&nbsp;</p><p>OK now here's where to read this stuff properly explained. roll</p><p>Two thorough tutorials:</p><p>http://www.gnu.org/software/gawk/manual/gawk.html</p><p>http://www.grymoire.com/Unix/Awk.html</p><p>A famous list of useful one-liners - though they're short, many are quite tricky:</p><p>http://www.pement.org/awk/awk1line.txt</p><p>And some nice explanations of those one-liners. After reading this you'll have a pretty good grasp!</p><p>http://www.catonmat.net/blog/awk-one-li &hellip; -part-one/</p><p>http://www.catonmat.net/blog/ten-awk-ti &hellip; -pitfalls/</p>]]></description>
	<dc:creator>Neel</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34377/genomicus-genome-browser-that-enables-users-to-navigate-in-genomes-in-several-dimensions</guid>
	<pubDate>Sat, 18 Nov 2017 16:10:16 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34377/genomicus-genome-browser-that-enables-users-to-navigate-in-genomes-in-several-dimensions</link>
	<title><![CDATA[Genomicus: genome browser that enables users to navigate in genomes in several dimensions]]></title>
	<description><![CDATA[<p>Genomicus is a genome browser that enables users to navigate in genomes in several dimensions: linearly along chromosome axes, transversaly across different species, and chronologicaly along evolutionary time.</p>
<p>Once a query gene has been entered, it is displayed in its genomic context in parallel to the genomic context of all its orthologous and paralogous copies in all the other sequenced metazoan genomes. Moreover, Genomicus stores and displays the predicted ancestral genome structure in all the ancestral species within the phylogenetic range of interest.</p>
<p>All the data on extant species displayed in this browser are from&nbsp;<a href="http://www.ensembl.org/">Ensembl</a>.</p><p>Address of the bookmark: <a href="http://genomicus.biologie.ens.fr/genomicus-90.01/cgi-bin/search.pl" rel="nofollow">http://genomicus.biologie.ens.fr/genomicus-90.01/cgi-bin/search.pl</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/4106/phd-at-national-institute-for-research-in-reproductive-health</guid>
  <pubDate>Fri, 30 Aug 2013 04:50:35 -0500</pubDate>
  <link></link>
  <title><![CDATA[PhD at National Institute for Research in Reproductive Health]]></title>
  <description><![CDATA[
<p>National Institute for Research in Reproductive Health</p>

<p>(Indian Council of Medical Research )<br />Jehangir Merwanji Street, Parel, Mumbai 400 012</p>

<p>Advertisement No. 1/NIRRH/Ph.D. 2013<br />Admission to Ph.D. Programme – 2013</p>

<p>National Institute for Research in Reproductive Health, Mumbai, a premier institute of the Indian Council of Medical Research, conducts basic, clinical and operational research in different areas of reproductive health. The thrust areas of research include: Fertility Regulation, Infertility and Reproductive Disorders, Reproductive Tract Infections, Maternal and Child Health, Osteoporosis, Genetic Disorders, Stem Cell Biology, Structural Biology, Bioinformatics and Reproductive Toxicology. Institute is affiliated to the University of Mumbai for the award of Ph.D. degree in Applied Biology, Biochemistry, Life Sciences and Biotechnology. The institute invites applications from young and bright students for enrollment in Ph.D. programme.</p>

<p>More at http://www.nirrh.res.in/announcements/phd_program_2013.htm</p>
]]></description>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/4081/csir-institute-of-genomics-integrative-biology</guid>
  <pubDate>Thu, 29 Aug 2013 05:22:03 -0500</pubDate>
  <link></link>
  <title><![CDATA[CSIR-INSTITUTE OF GENOMICS &amp; INTEGRATIVE BIOLOGY]]></title>
  <description><![CDATA[
<p>CSIR-INSTITUTE OF GENOMICS &amp; INTEGRATIVE BIOLOGY, Mall Road, Delhi 110007</p>

<p>POSITIONS OPEN FOR TEMPORARY RESEARCH PROJECT POSTS</p>

<p>(Date of interview 23rd September 2013 at 10:30 AM)</p>

<p>CSIR-Institute of Genomics &amp; Integrative Biology (IGIB), desires to engage qualified incumbents on purely temporary basis as detailed below:</p>

<p>Project Code/Title (Project Code BSC0123)</p>

<p>Genome dynamics in Cellular Organization, Differentiation and Enantiostasis (GENCODE)</p>

<p>Project Fellow<br />	<br />First Class M.Sc./M.Tech in bioinformatics/Human Genetics/Genomics</p>

<p>Rs. 16,000/- + 30 % HRA per month</p>

<p>Sr. Project Fellow	</p>

<p>First Class M.Sc./M.Tech in bioinformatics/Human Genetics/Genomics</p>

<p>With two years of experience in NGS data analysis.</p>

<p>Rs. 18,000/- + 30 % HRA per month</p>

<p>Age relaxation as per Govt. of India instructions.</p>

<p>Engagement is for the project and on behalf of the funding agency and the tenure shall be as mentioned above. The duration of the post is initially for One year or till the closing date of the project, whichever is earlier. Tenure may be extendable up to project duration. Contract may be terminated at any time by giving one-month notice by either side. The applicants will have no claim implicit or explicit for consideration against any CSIR/IGIB post.</p>

<p>How to Apply:</p>

<p>It is mandatory for eligible applicants to apply by both the processes as given below:</p>

<p>1.    Sending the resume in MS Word format directly to hrd@igib.res.in (Mentioning the Project Code-Post Code in the Subject Line of the email example:GAP0059-1)</p>

<p>2.    They also need to fill up proforma by clicking on the following link HR Online Form.</p>

<p>3.    Candidate cannot apply for more than two posts.</p>

<p>Last date of receiving application is 02-09-2013.</p>

<p>No application would be entertained with result awaited status or after due date.</p>

<p>The email will be sent to the short listed candidates.</p>

<p>No TA/DA will be paid to the candidates to attend the interview. The engagement shall be as per guidelines of CSIR/Funding agency. Candidates will have an option to give reply in Hindi.</p>

<p>Note: The shortlisted candidates, who will receive the email for interview, have to report at 09:00 AM on the day of interview along with any Photo ID card and original certificates for entry purpose. Entry will be closed by 10:00 AM.</p>

<p>More @ http://www.igib.res.in/sites/default/files/23092013.htm</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/3013/python-and-biopython-tutorial</guid>
	<pubDate>Fri, 23 Aug 2013 06:47:40 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/3013/python-and-biopython-tutorial</link>
	<title><![CDATA[Python and BioPython Tutorial]]></title>
	<description><![CDATA[<p>A quickstart tutorial that allows to become familiar with the Python language. The exercises expect knowledge of basic concepts of programming. A group of 2nd year computer science students with no previous Python knowledge required 60'-90' to complete the exercises. With about 3 hours time, the exercise is suitable for non-programmers as well.</p><p>Address of the bookmark: <a href="http://www.biotnet.org/training-materials/python-programmers" rel="nofollow">http://www.biotnet.org/training-materials/python-programmers</a></p>]]></description>
	<dc:creator>Manshi Raghubanshi</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/3967/research-project-posts-for-csir-project-delhi</guid>
  <pubDate>Tue, 27 Aug 2013 04:31:41 -0500</pubDate>
  <link></link>
  <title><![CDATA[Research Project Posts for CSIR Project, Delhi]]></title>
  <description><![CDATA[
<p>Positions Open For Temporary Research Project Posts for CSIR Project, Delhi<br />CSIR is looking for bright young candidates to get involved in building algorithms and platforms for large biological data analyses in the areas of comparative genomics, computational workflows, disease association studies, simulating virtual organelles, etc. Anyone who fulfills the eligibility criteria mentioned below may appear for a walk-in interview on 3rd September 2013 at CSIR Headquarters, Anusandhan Bhawan, 2 Rafi Marg, Delhi – 110001.<br />you can go to link for details or download PDF</p>

<p>http://www.csir.res.in/External/Heads/aboutcsir/announcements/ProjectPost_130813.pdf</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36890/price-paired-read-iterative-contig-extension-a-de-novo-genome-assembler-implemented-in-c</guid>
	<pubDate>Mon, 11 Jun 2018 03:08:26 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36890/price-paired-read-iterative-contig-extension-a-de-novo-genome-assembler-implemented-in-c</link>
	<title><![CDATA[PRICE (Paired-Read Iterative Contig Extension), a de novo genome assembler implemented in C++.]]></title>
	<description><![CDATA[We are pleased to release PRICE (Paired-Read Iterative Contig Extension), a de novo genome assembler implemented in C++. Its name describes the strategy that it implements for genome assembly: PRICE uses paired-read information to iteratively increase the size of existing contigs. Initially, those contigs can be individual reads from a subset of the paired-read dataset, non-paired reads from sequencing technologies that provide non-paired data, or contigs that were output from a prior run of PRICE or any other assembler.

http://derisilab.ucsf.edu/software/price/<p>Address of the bookmark: <a href="http://derisilab.ucsf.edu/software/price/" rel="nofollow">http://derisilab.ucsf.edu/software/price/</a></p>]]></description>
	<dc:creator>Surabhi Chaudhary</dc:creator>
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