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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/30976?offset=1580</link>
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	<description><![CDATA[]]></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/4098/bioinformatics-algorithm-demonstrations-and-tutorials</guid>
	<pubDate>Thu, 29 Aug 2013 09:23:51 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/4098/bioinformatics-algorithm-demonstrations-and-tutorials</link>
	<title><![CDATA[Bioinformatics Algorithm Demonstrations and Tutorials]]></title>
	<description><![CDATA[<p>Abstract</p>
<p>This project presents demonstrations of selected computer science algorithms important in&nbsp;bioinformatics, implemented in the spreadsheet program Microsoft Excel. Spreadsheets provide an&nbsp;interesting platform for demonstration of algorithms, since various steps of the calculations can be&nbsp;exposed in a manner that is easily comprehensible to users with little programming experience. The&nbsp;algorithms demonstrated include two approaches to approximate string matching (dynamic programming&nbsp;and Shift-AND numeric approximate matching), Hierarchical Clustering (used in phylogenetic studies&nbsp;and microarray analysis of gene expression), a Naive Bayes Classifier for simulated microarray gene&nbsp;expression data, and a simple Neural Network. These demonstrations are designed to serve as&nbsp;instructional aids in bioinformatics courses.</p>
<p>Tutorial @&nbsp;http://www.cybertory.org/downloads/bae/BioinformaticsAlgorithmsInExcel.zip</p>
<p>One of the best resource for online bioinformatics learning is https://stepic.org/Bioinformatics-Algorithms-2 Enjoy the online learning.</p>
<p>Reference :&nbsp;cybertory</p>
<blockquote>
<p><span>" Please add your favourite bioinformatics algorithms and tutorial links below in the comment section, for the benefit of bioinformatics and computational biology community ".&nbsp;</span></p>
</blockquote><p>Address of the bookmark: <a href="http://www.cybertory.org/downloads/bae/BioinformaticsAlgorithmsExcelDoc.pdf" rel="nofollow">http://www.cybertory.org/downloads/bae/BioinformaticsAlgorithmsExcelDoc.pdf</a></p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/videolist/watch/4851/blast</guid>
	<pubDate>Wed, 25 Sep 2013 10:56:23 -0500</pubDate>
	<link>https://bioinformaticsonline.com/videolist/watch/4851/blast</link>
	<title><![CDATA[BLAST]]></title>
	<description><![CDATA[<iframe width="" height="" src="https://www.youtube-nocookie.com/embed/g0nSH17psDc" frameborder="0" allowfullscreen></iframe>Dr. Rob Edwards describes how BLAST works]]></description>
	
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	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/4162/4273%CF%80-bioinformatics-education-on-low-cost-arm-hardware</guid>
	<pubDate>Mon, 02 Sep 2013 07:02:43 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/4162/4273%CF%80-bioinformatics-education-on-low-cost-arm-hardware</link>
	<title><![CDATA[4273π: Bioinformatics education on low cost ARM hardware]]></title>
	<description><![CDATA[<p>Are you teaching bioinformatics at universities and found it complicated by typical computer classroom settings. As well as running software locally and online, students should gain experience of systems administration. Hmm don't worry there is one new OS for the rescue. 4273<em>&pi;</em>, an operating system image for Raspberry Pi based on Raspbian Linux. It provides an attractive, general-purpose computing environment, within which the course 4273&pi; Bioinformatics for Biologists is embedded.<br /><br />Though far slower than current desktop and laptop computers, the Raspberry Pi is notably faster than the Cray 1 supercomputer, a marvel of computer speed in its day. The Raspberry Pi approach includes all the benefits of the laptop approach, above, but at lower cost. In addition, the Raspberry Pi is a new and exciting computer system, which in itself can add interest to the course.<br /><br />As the Raspbian operating system, Raspberry Pi firmware and hardware and 4273&pi; Bioinformatics for Biologists teaching material develop, further releases of 4273&pi; will be made available. It is anticipated that there will be a minimum of two releases per year during the next four years.</p><p>4273<em>&pi;</em> is a means to teach bioinformatics, including systems administration tasks, to undergraduates at low cost.</p><p>Descriptive paper @ http://www.biomedcentral.com/1471-2105/14/243</p><p>Image source: BMC Bioinformatics</p><p><img src="http://www.biomedcentral.com/content/download/figures/1471-2105-14-243-1.png" alt="image" style="border: 0px; border: 0px;"></p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37545/ncbi-magic-blast</guid>
	<pubDate>Tue, 14 Aug 2018 18:11:11 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37545/ncbi-magic-blast</link>
	<title><![CDATA[NCBI Magic-BLAST]]></title>
	<description><![CDATA[<p>Magic-BLAST is a tool for mapping large next-generation RNA or DNA sequencing runs against a whole genome or transcriptome. Each alignment optimizes a composite score, taking into account simultaneously the two reads of a pair, and in case of RNA-seq, locating the candidate introns and adding up the score of all exons. This is very different from other versions of BLAST, where each exon is scored as a separate hit and read-pairing is ignored.</p>
<p>Magic-BLAST incorporates within the NCBI BLAST code framework ideas developed in the NCBI Magic pipeline, in particular hit extensions by local walk and jump&nbsp;<a href="http://www.ncbi.nlm.nih.gov/pubmed/26109056">(http://www.ncbi.nlm.nih.gov/pubmed/26109056)</a>, and recursive clipping of mismatches near the edges of the reads, which avoids accumulating artefactual mismatches near splice sites and is needed to distinguish short indels from substitutions near the edges.</p>
<p>&nbsp;</p><p>Address of the bookmark: <a href="https://ncbi.github.io/magicblast/" rel="nofollow">https://ncbi.github.io/magicblast/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/4409/huber-lab</guid>
  <pubDate>Mon, 09 Sep 2013 21:57:03 -0500</pubDate>
  <link></link>
  <title><![CDATA[Huber Lab]]></title>
  <description><![CDATA[
<p>The Huber group develops computational and statistical methods to design and analyse novel experimental approaches in genetics and cell biology. </p>

<p>Future projects and goals</p>

<p>Large-scale systematic maps of gene-gene and gene-environment interactions by automated phenotyping, using image analysis, machine learning, sparse model building and causal inference.<br />DNA-, RNA- and ChIP-Seq and their applications to gene expression regulation: statistical and computational foundations.<br />Cancer genomics, genomes as biomarkers, cancer phylogeny.<br />Image analysis for systems biology: measuring the dynamics of cell cycle and of cell migration of individual cells under normal conditions and many different perturbations (RNAi, drugs).</p>

<p>More @ http://www.embl.de/research/units/genome_biology/huber/index.html</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41482/magic-blast</guid>
	<pubDate>Fri, 20 Mar 2020 15:18:36 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41482/magic-blast</link>
	<title><![CDATA[Magic-BLAST]]></title>
	<description><![CDATA[<p>Magic-BLAST is a tool for mapping large next-generation RNA or DNA sequencing runs against a whole genome or transcriptome. Each alignment optimizes a composite score, taking into account simultaneously the two reads of a pair, and in case of RNA-seq, locating the candidate introns and adding up the score of all exons. This is very different from other versions of BLAST, where each exon is scored as a separate hit and read-pairing is ignored.</p><p>Address of the bookmark: <a href="https://ncbi.github.io/magicblast/" rel="nofollow">https://ncbi.github.io/magicblast/</a></p>]]></description>
	<dc:creator>Shruti Paniwala</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/4456/asst-prof-in-bioinformatics-at-jaipur-national-university</guid>
  <pubDate>Thu, 12 Sep 2013 07:18:02 -0500</pubDate>
  <link></link>
  <title><![CDATA[Asst. PROF IN BIOINFORMATICS at JAIPUR NATIONAL UNIVERSITY]]></title>
  <description><![CDATA[
<p>JAIPUR NATIONAL UNIVERSITY, SCHOOL OF LIFE SCIENCES (SIILAS CAMPUS) URGENTLY REQUIRES</p>

<p>Asst. PROF IN BIOINFORMATICS.</p>

<p>QUALIFICATION: AS PER UGC</p>

<p>DESIRABLE: 1 YEAR EXPERIENCE IN ACADEMICS</p>

<p>CONTACT immediately</p>

<p>Prof D.S.Bhatia<br />Director<br />9351288070</p>

<p>Last date within 7 days of the publication.</p>

<p>Find more @ http://jnujaipur.ac.in/downloads/AdvtDec2012.jpg</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43952/elastic-blast</guid>
	<pubDate>Tue, 06 Sep 2022 18:14:57 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43952/elastic-blast</link>
	<title><![CDATA[Elastic BLAST !]]></title>
	<description><![CDATA[<p><a href="https://blast.ncbi.nlm.nih.gov/doc/elastic-blast/elasticblast.html?utm_source=ncbi_insights&amp;utm_medium=referral&amp;utm_campaign=elasticblast-top3-20220823">ElasticBLAST</a>&nbsp;is a new way to&nbsp;<a href="https://blast.ncbi.nlm.nih.gov/?utm_source=ncbi_insights&amp;utm_medium=referral&amp;utm_campaign=elasticblast-top3-20220823">BLAST</a>&nbsp;large numbers of queries, faster and on the cloud. Here are the top three reasons you should use ElasticBLAST:</p>
<h6><strong><img src="https://i0.wp.com/ncbiinsights.ncbi.nlm.nih.gov/wp-content/uploads/2022/08/ElasticBLAST_Larger-e1659978198941.png?resize=150%2C120&amp;ssl=1" alt="" width="150" height="120" style="border: 0px;">1. ElasticBLAST can handle much LARGER queries!&nbsp;</strong></h6>
<p>ElasticBLAST can search query sets that have&nbsp;<em>hundreds to millions of sequences</em>&nbsp;and against BLAST databases of all sizes.</p>
<h6><span><img src="https://i0.wp.com/ncbiinsights.ncbi.nlm.nih.gov/wp-content/uploads/2022/08/ElasticBLAST_Faster.png?resize=150%2C120&amp;ssl=1" alt="" width="150" height="120" style="border: 0px;">2. ElasticBLAST is FASTER</span></h6>
<p>ElasticBLAST distributes your searches across multiple cloud instances to process them simultaneously. The ability to scale resources in this way allows you to process large numbers of queries in a shorter time than you could with BLAST+.</p>
<h6><img src="https://i0.wp.com/ncbiinsights.ncbi.nlm.nih.gov/wp-content/uploads/2022/08/ElasticBLAST_Easy.png?resize=150%2C120&amp;ssl=1" alt="" width="150" height="120" style="border: 0px;">3. ElasticBLAST is EASY to run on the cloud<strong><br></strong></h6>
<p>ElasticBLAST is easy to set up using our step-by-step instructions&nbsp;<span>(</span><a href="https://blast.ncbi.nlm.nih.gov/doc/elastic-blast/quickstart-aws.html?utm_source=ncbi_insights&amp;utm_medium=referral&amp;utm_campaign=elasticblast-top3-20220823" target="_blank"><span><span>Amazon Web&nbsp;</span><span>Services (AWS)</span></span></a><span>,&nbsp;</span><a href="https://blast.ncbi.nlm.nih.gov/doc/elastic-blast/quickstart-gcp.html?utm_source=ncbi_insights&amp;utm_medium=referral&amp;utm_campaign=elasticblast-top3-20220823" target="_blank"><span>Google Cloud Platform (GCP)</span></a><span><span>)</span>&nbsp;<span>and</span>&nbsp;<span>allows&nbsp;</span><span>you&nbsp;</span><span>to leverage the power of</span><span>&nbsp;the&nbsp;</span><span>cloud. Once configured, i</span><span>t</span>&nbsp;<span>manages the software and database installation, handles partitioning of the BLAST workload among the various instances, and deallocates cloud resources when the searches are done.</span></span></p>
<p><span><span>ElasticBLAST</span>&nbsp;<span>also&nbsp;</span><span>selects the instance (</span><span>i.e.,</span><span>&nbsp;machine) type for you based on database size. Of course, you can also choose the instance type manually if you prefer</span><span>.&nbsp;</span></span></p><p>Address of the bookmark: <a href="https://blast.ncbi.nlm.nih.gov/doc/elastic-blast/" rel="nofollow">https://blast.ncbi.nlm.nih.gov/doc/elastic-blast/</a></p>]]></description>
	<dc:creator>Abhi</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/6715/research-associate-school-of-computational-and-integrative-sciences-under-jawaharlal-nehru-university</guid>
  <pubDate>Fri, 22 Nov 2013 19:06:44 -0600</pubDate>
  <link></link>
  <title><![CDATA[Research Associate@ School of Computational and Integrative Sciences under Jawaharlal Nehru University]]></title>
  <description><![CDATA[
<p>School of Computational and Integrative Sciences under Jawaharlal Nehru University, New Delhi invited applications for filling up 4 posts of Research Associates (RA) and Junior Research Fellow (JRF) (2 posts each)  purely on temporary basis, liable to be terminated at any time without prior notice or ceased/withdrawn by the funding agency. The vacancies are for a Department of Biotechnology, Government of India funded project entitled "Computational Core for Plant Metabolomics" (Project ID: 632) being administered by Prof Indira Ghosh. Interested candidates should send their applications till 13 December 2013.<br />Important Dates<br />Last Date for receipt of applications: 13 December 2013<br />Vacancy Details<br />Total Vacancies: 4 posts<br />Type of recruitment: Temporary<br />Sl. No.: 01<br />Name of the Post: Research Associate<br />No of Posts: 1 post<br />Remuneration: Rs.  23000 + 30%<br />Qualifications: PhD in Bioinformatics / computational biology / Biophysics / Physical Chemistry / Computer Science. Computational experience, proven by paper published, is a necessary qualification.<br /> Sl. No.: 02<br />Name of the Post: Research Associate<br />No of Posts: 1 post<br />Remuneration: Rs. 23000 + 30%<br />Qualifications: PhD in Computational Biology / Bioinformatics &amp; related subjects. Computational experience, proven by paper published, is a necessary qualification.<br />Sl. No.: 03<br />Name of the Post: Junior Research Fellow<br />No of Posts: 1 post<br />Remuneration: Rs. 12000 + 30%<br />Qualifications: M. Sc. / B. Tech. preferably in Computational Biology /Bioinformatics and related fields with experience in Website designing &amp; maintenance of Database.<br />Sl. No.: 04<br />Name of the Post: Junior Research Fellow<br />No of Posts: 1 post<br />Remuneration: Rs.  12000 + 30%<br />Qualifications: M. Sc. / MCA / B. Tech. preferably in Computational Biology / Computer science with experience in Programming in Java / Python, C++ etc &amp; designing of Database.<br />Selection Procedure: Selection will be done on the basis of candidates’ performance in the Interview.  <br />Candidates short-listed / selected for Interview will be informed through email only.<br />How to Apply: Interested eligible candidates should send their applications, in the prescribed format, along with their current CV by post to “Prof Indira Ghosh, Project Investigator,  Hall#6, School of Computational and Integrative Sciences,  Jawaharlal Nehru University,  New Delhi-110 067” so as to reach the concerned authority by 13 December 2013.<br />Name of the post applied for’ must be superscripted on the envelope containing the application.<br />NOTE: For the post of Research Associates, only those candidates who have submitted thesis are eligible to apply. However, salary will be provided as per DBT / DST guidelines (i.e. candidates who have qualified NET /BET / BINC will have higher pay scale).<br />Candidates interested to register for PhD may not apply for JRF.<br />More @ http://www.jnu.ac.in/Career/currentjobs.htm</p>
]]></description>
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