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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/30168?offset=490</link>
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	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/44352/bioinformatics-tools-for-genome-assembly</guid>
	<pubDate>Mon, 24 Jul 2023 07:04:26 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/44352/bioinformatics-tools-for-genome-assembly</link>
	<title><![CDATA[Bioinformatics tools for genome assembly !]]></title>
	<description><![CDATA[<p>There are numerous genome assembly tools available, each with its strengths and weaknesses. Here is a list of some widely used genome assembly tools as of my last update in September 2021:</p><ol>
<li>
<p><span>SPAdes:</span> An assembler specifically designed for single-cell and multi-cell bacterial genomes, as well as small eukaryotic genomes.</p>
</li>
<li>
<p><span>ABySS:</span> A parallelized assembler for large genomes that uses de Bruijn graphs.</p>
</li>
<li>
<p><span>Velvet:</span> Another de Bruijn graph-based assembler optimized for short-read sequencing data.</p>
</li>
<li>
<p><span>SOAPdenovo:</span> A de Bruijn graph-based assembler designed for short reads, widely used for assembling large and complex genomes.</p>
</li>
<li>
<p><span>MaSuRCA:</span> A hybrid assembler that combines data from multiple sequencing technologies, such as Illumina and PacBio.</p>
</li>
<li>
<p><span>Canu:</span> A long-read assembler optimized for PacBio and Oxford Nanopore sequencing data.</p>
</li>
<li>
<p><span>Flye:</span> A long-read assembler suitable for bacterial and small eukaryotic genomes.</p>
</li>
<li>
<p><span>SMARTdenovo:</span> An assembler designed for long reads, particularly suited for PacBio data.</p>
</li>
<li>
<p><span>SPAdes Long Read (SPAdesLR):</span> An extension of SPAdes for long-read data, such as those from PacBio or Nanopore.</p>
</li>
<li>
<p><span>Minia:</span> An assembler optimized for low memory consumption, suitable for small and medium-sized genomes.</p>
</li>
<li>
<p><span>Unicycler:</span> A hybrid assembler that combines short and long reads for circular bacterial genome assembly.</p>
</li>
<li>
<p><span>wtdbg2:</span> A de Bruijn graph assembler for long reads, efficient for very large genomes.</p>
</li>
<li>
<p><span>Shasta:</span> A long-read assembler that uses the Overlap-Layout-Consensus approach, suitable for PacBio and Nanopore data.</p>
</li>
<li>
<p><span>Sparc:</span> An assembler designed to handle noisy long reads from Nanopore sequencing.</p>
</li>
<li>
<p><span>CANA:</span> An assembler for metagenomic data, particularly for complex and diverse microbial communities.</p>
</li>
<li>
<p><span>Ra</span> Assembler: A metagenome assembler for long reads, designed for highly complex metagenomic samples.</p>
</li>
</ol><p>Please note that the field of bioinformatics is constantly evolving, and new assembly tools may have emerged since my last update. Additionally, the performance of these tools can vary depending on the characteristics of the sequencing data and the genome being assembled. When selecting an assembly tool, consider the specific requirements of your project, the available data types, and the computational resources at your disposal. Always refer to the respective tool's documentation and publications for the most up-to-date information and recommendations.</p>]]></description>
	<dc:creator>BioStar</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/5209/anders-krogh-lab</guid>
  <pubDate>Mon, 30 Sep 2013 19:07:40 -0500</pubDate>
  <link></link>
  <title><![CDATA[Anders Krogh Lab]]></title>
  <description><![CDATA[
<p>In a lot of my work in bioinformatics, I have been using hidden Markov models (HMMs). As a postdoc with David Haussler at UCSC we developed the so-called profile HMMs (refs). Since then I have applied HMMs to membrane proteins (refs) and gene identification (refs) and have worked on methods for such things as discriminative estimation of HMMs (refs) and alternative decoding algorithms etc. (refs).</p>

<p>Now my main interests are in gene regulation, where we work on promoter analysis; non-coding RNA, where miRNAs and structure prediction are the main areas; and protein structure, where the group is working on methods for structure prediction from sequence. To read more about these topics, please see the research pages. </p>

<p>Lab page @ http://wiki.binf.ku.dk/User:Krogh</p>
]]></description>
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<item>
	<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/opportunity/view/4946/crcri-bioinfomatics-walk-in-on-08102013</guid>
  <pubDate>Fri, 27 Sep 2013 10:59:53 -0500</pubDate>
  <link></link>
  <title><![CDATA[CRCRI Bioinfomatics Walk In on 08.10.2013]]></title>
  <description><![CDATA[
<p>Walk-in-Interview for recruitment of one Project Fellow for a period of 10 months purely on temporary basis is proposed to be held at Central Tuber Crops Research Institute, Sreekariyam, Thiruvananthapuram for a KSCSTE funded project entitled “PARTICIPATORY DEVELOPMENT OF A WEB BASED USER FRIENDLY CASSAVA EXPERT SYSTEM”</p>

<p>Salary: Rs. 10,000/- per month.</p>

<p>Age limit: 35 for men and 40 for women &amp; SC/ST.</p>

<p>Qualification: First class in M. Sc (Agriculture)/MCA/M.Sc (IT)/ M. Sc (Computer Application)/M.Sc (Bioinformatics)/M.Sc (Geoinformatics).</p>

<p>Desirable: Two years experience in web design and web programming.</p>

<p>Date &amp; time of interview: 08.10.2013, 10 am</p>

<p>Interested candidates may appear for an interview at this institute along with their application in plain paper containing the following particulars viz. (1) Name (2) Father/Husband/Guardian’s Name (3) date of birth &amp; age as on 01.10.2013 (4) Permanent address (5) Address for communication (6) Email address and Telephone No. with code (7) Qualification (8) National fellowship like ICAR/CSIR/UGC etc. if any (9) Whether SC/ST/OBC (10) Details of experience (Attested copies of degree certificate, proof of age, mark sheets). Original certificates should be produced for verification.</p>

<p>No TA/DA will be admissible to the candidates attending the test. The selected candidate will have to join immediately.</p>

<p>Advertisement: http://www.ctcri.org/careers/mithra_SRF.doc</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/40589/new-layout-for-blast-ftp-database-site</guid>
	<pubDate>Tue, 21 Jan 2020 11:57:11 -0600</pubDate>
	<link>https://bioinformaticsonline.com/news/view/40589/new-layout-for-blast-ftp-database-site</link>
	<title><![CDATA[New Layout for BLAST ftp Database Site]]></title>
	<description><![CDATA[<p>As announced previously, the new default database version for&nbsp;<a href="https://ncbiinsights.ncbi.nlm.nih.gov/2019/12/18/blast-2-10-0/" target="_blank" title="Follow link">BLAST+</a>&nbsp;is&nbsp;<a href="https://ncbiinsights.ncbi.nlm.nih.gov/2019/09/30/protein-blastdbs-accession-based/" target="_blank" title="Follow link">dbV5</a>.&nbsp; To complete this transition, the&nbsp;<a href="ftp://ftp.ncbi.nlm.nih.gov/blast/db/" target="_blank" title="Follow link">ftp database site</a>&nbsp;will be updated to support this change.&nbsp; We expect this change to happen around February 4<sup>th</sup>, please adjust your scripts or procedures accordingly.</p><p>Here is a list of what is changing:</p><ol>
<li>All databases at the root level will be dbV5.</li>
<li>The dbV5 file naming, &nbsp;&ldquo;_v5&rdquo; will be removed. Databases with &nbsp;no &ldquo;_vX&rdquo; descriptor will be dbV5.</li>
<li>dbV4 tarballs will be renamed with "_v4", files included in tarball will not be renamed.</li>
<li>dbV4 databases will be moved to a v4 subdirectory.</li>
<li>As of 1/13/20 the Cloud directory will be frozen with no more new entries.</li>
<li>The will be no more updates to dbV4 databases.</li>
<li>The FASTA directory will contain nr, nt, swissprot, and pdbaa files.</li>
</ol><p>If you have any questions or concerns, please contact&nbsp;<a href="mailto:blast-help@ncbi.nlm.nih.gov" target="_blank" title="Follow link">blast-help@ncbi.nlm.nih.gov</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/videolist/watch/5187/bioinformatics-algorithms-part-1-with-pavel-pevzner-phillip-e-c-compeau</guid>
	<pubDate>Mon, 30 Sep 2013 11:34:09 -0500</pubDate>
	<link>https://bioinformaticsonline.com/videolist/watch/5187/bioinformatics-algorithms-part-1-with-pavel-pevzner-phillip-e-c-compeau</link>
	<title><![CDATA[Bioinformatics Algorithms (Part 1)  with Pavel  Pevzner, Phillip E. C. Compeau,]]></title>
	<description><![CDATA[<iframe width="" height="" src="https://www.youtube-nocookie.com/embed/t5t_nfzdzEg" frameborder="0" allowfullscreen></iframe><p>The course Bioinformatics Algorithms (Part 1) by Pavel Pevzner, Phillip E. C. Compeau, and Nikolay Vyahhi from University of California, San Diego will be offered free of charge to everyone on the Coursera platform. Sign up at http://www.coursera.org/course/bioinformatics.</p>]]></description>
	
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/4209/enzyme-portal</guid>
	<pubDate>Tue, 03 Sep 2013 18:06:06 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/4209/enzyme-portal</link>
	<title><![CDATA[Enzyme Portal]]></title>
	<description><![CDATA[<p><span>Enzyme Portal-&nbsp;To look for information about the biology of a protein with enzymatic activity.</span></p>
<p><span>The enzyme portal integrates many resources, most of them hosted by EBI and also external ones such as BioPortal. Its main goal is to provide information about enzymes in a suitable format, with a usable interface designed for intended users. Instead of reinventing the wheel, it makes use of available and reliable resources to that end.</span></p>
<p><span><strong>Related Literature</strong>:</span></p>
<p><span><a href="http://nar.oxfordjournals.org/content/41/D1/D773.full">http://nar.oxfordjournals.org/content/41/D1/D773.full</a></span></p>
<p><span><a href="http://www.biomedcentral.com/1471-2105/14/103">http://www.biomedcentral.com/1471-2105/14/103</a></span></p><p>Address of the bookmark: <a href="http://www.ebi.ac.uk/enzymeportal/" rel="nofollow">http://www.ebi.ac.uk/enzymeportal/</a></p>]]></description>
	<dc:creator>Rahul Agarwal</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/5255/walk-in-interview-indian-agricultural-statistics-research-institute</guid>
  <pubDate>Wed, 02 Oct 2013 15:40:17 -0500</pubDate>
  <link></link>
  <title><![CDATA[Walk-in-Interview @ Indian Agricultural Statistics Research Institute]]></title>
  <description><![CDATA[
<p>Indian Agricultural Statistics Research Institute<br />Library Avenue, Pusa, New Delhi – 110012</p>

<p>Walk-in-Interview</p>

<p>Walk-in-interview will be held on October 5, 2013 at 10:00 A.M. at IASRI, New Delhi for a project “A New Distributed Computing Framework for Data Mining” funded by Department of Electronics and Information Technology, Government of India for the following posts. The appointment will be on contractual basis upto 14th October, 2015 or till the termination of the project whichever is earlier and the incumbent shall not have any claim for regular appointment under ICAR.</p>

<p>Research Associate</p>

<p>    Ph.D. in Bioinformatics/ Agricultural Statistics/ Statistics/ Computer Science/ Computer Application or equivalent or</p>

<p>    Post-Graduation in Bioinformatics/ Agricultural Statistics/ Statistics/ Computer Science/ Computer Application or equivalent with 1st Division and at least two years of research experience</p>

<p>     Knowledge of Statistical Analysis /Bioinformatics tools for computational genomics.</p>

<p>     Knowledge of R/Perl programming language</p>

<p>Research Associate</p>

<p>    Ph.D. in Computer Science/ Computer Application / Bioinformatics/ Agricultural<br />    Statistics/ Statistics or equivalent or</p>

<p>    Post-Graduation in Computer Science/ Computer Application /Bioinformatics/ Agricultural Statistics/ Statistics or equivalent with 1st Division and at least two years of research experience</p>

<p>     Expertise in Java programming.<br />     Knowledge of system administration and networking under Linux environment.<br />     Knowledge of parallel programming and cluster computing.</p>

<p>Emoluments for Research Associate: Consolidated Rs:24000/- per month + HRA (for Ph.D. Degree holders) and Rs:23000/- per month + HRA (for Master’s Degree holders)</p>

<p>Age Limit: Age should be not more than 40 years (5 years relaxation for  SC/ST/women candidates and 3 years for OBC candidates as on date of interview).</p>

<p>Interested candidates are requested to appear for Walk-in-Interview on the date and time as specified above in Room No. 106, Training Cum Administrative Block of the Institute along with their application giving bio-data with attested copies of certificates, degrees, testimonials, etc. and one passport size photograph.</p>

<p>Original certificates/ Degrees are needed to be produced at the time of interview.</p>

<p>No T.A. /D.A. will be paid for appearing in the interview.</p>

<p>Advertisement: http://www.iasri.res.in/employment/employment.htm</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/39281/humcfs-a-database-of-fragile-sites-in-human-chromosomes</guid>
	<pubDate>Sun, 21 Apr 2019 20:17:29 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/39281/humcfs-a-database-of-fragile-sites-in-human-chromosomes</link>
	<title><![CDATA[HumCFS: a database of fragile sites in human chromosomes]]></title>
	<description><![CDATA[<p>Fragile sites are specific chromosomal region that exhibit an increased frequency of chromosdomal breakge when cells are exposed to replicative stress. Since from the discovery of chromosomal fragile sites/regions (CFS), several line of evidence suggests their involvement in human pathologies and they have been recognized as a preferential site for integration of exogenous oncogenic DNA viruses and hotspots for chromosomal re-arrangement. There is large gap in our knowledge of human CFS region as knowledge about CFS are unequally distributed in literature, which impose a problem in studying these region. In order to address these issues, we develop this platform HumCFS, which provides comprehensive information about experimentally identified CFS at a single source.</p>
<p>https://link.springer.com/epdf/10.1186/s12864-018-5330-5?author_access_token=ICASEpyMAQaxLlKw--fyCG_BpE1tBhCbnbw3BuzI2RMA57KLmXk5bZabRUiDQzRFHXd6hjm4kWSiLV3mU5XVMitqXUwFMSo4x5vbfty0EDQ9PW1sd1h923_TYXkvJ5niSwAyZ7BklJ0ujFAFhcKtjw%3D%3D</p><p>Address of the bookmark: <a href="https://webs.iiitd.edu.in/raghava/humcfs/" rel="nofollow">https://webs.iiitd.edu.in/raghava/humcfs/</a></p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
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<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/5422/shendure-lab</guid>
  <pubDate>Wed, 09 Oct 2013 14:21:58 -0500</pubDate>
  <link></link>
  <title><![CDATA[Shendure Lab]]></title>
  <description><![CDATA[
<p>The Shendure Lab is part of the Department of Genome Sciences at the University of Washington (Seattle, WA). The mission of the lab is to develop and apply new technologies in genomics and molecular biology. Most projects in the lab exploit new DNA sequencing technologies (Shendure et al., Nature Reviews Genetics 2004; Shendure &amp; Ji, Nature Biotechnology 2008; Shendure &amp; Lieberman Aiden, Nature Biotechnology 2012), and generally fall into one of six areas: 1) next-generation human genetics; 2) genome contiguity &amp; completeness; 3) massively parallel functional analysis; 4) molecular tagging; 5) synthetic biology; 6) translational genomics. Our interests in each of these areas are outlined briefly below, and a full list of publications is available via PubMed. http://www.ncbi.nlm.nih.gov/pubmed?cmd=search&amp;term=shendure<br />More http://krishna.gs.washington.edu/research.html</p>

<p>Lab page @ http://krishna.gs.washington.edu/index.html</p>
]]></description>
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