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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/29992?offset=1310</link>
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	<description><![CDATA[]]></description>
	
	
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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/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/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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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34594/synima-synteny-imaging-tool</guid>
	<pubDate>Sun, 10 Dec 2017 17:03:48 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34594/synima-synteny-imaging-tool</link>
	<title><![CDATA[Synima: Synteny Imaging tool]]></title>
	<description><![CDATA[<p><span>Synteny Imaging tool (Synima) written in Perl, which uses the graphical features of R. Synima takes orthologues computed from reciprocal best BLAST hits or OrthoMCL, and DAGchainer, and outputs an overview of genome-wide synteny in PDF. Each of these programs are included with the Synima package, and a pipeline for their use. Synima has a range of graphical parameters including size, colours, order, and labels, which are specified in a config file generated by the first run of Synima &ndash; and can be subsequently edited. Synima runs quickly on a command line to generate informative and publication quality figures. Synima is open source and freely available from&nbsp;</span><span><a href="https://github.com/rhysf/Synima"><span>https://github.com/rhysf/Synima</span></a></span><span>&nbsp;under the MIT License.</span></p><p>Address of the bookmark: <a href="https://github.com/rhysf/Synima" rel="nofollow">https://github.com/rhysf/Synima</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/4653/human-genome-meeting-2014-geneva-switzerland</guid>
  <pubDate>Fri, 20 Sep 2013 12:36:44 -0500</pubDate>
  <link></link>
  <title><![CDATA[Human Genome Meeting 2014, Geneva, Switzerland]]></title>
  <description><![CDATA[
<p>The spectacular advances of the last few years resulted in the rapid analysis of the genome sequence of each individual. The biomedical world is now faced with the enormous challenges of assigning pathogenicity to each genomic variant, the functional analysis of the genome of each individual, and the accurate and detailed phenotypic characterization. Advances in these challenges are likely to fundamentally change the medical practice in a global scale.</p>

<p>This 2014 HUGO Meeting in Geneva will be a Forum for discussions on innovative approaches, and proposals to tackle the anticipated challenges.</p>

<p>Time : 27 April 2014 - 30 April 2014 </p>

<p>For enquiries, please email hugo2014@mci-group.com or visit www.hugo-international.org</p>

<p>More at http://www.hgm2014-geneva.org/</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41694/mercator-multiple-whole-genome-orthology-map-construction</guid>
	<pubDate>Tue, 19 May 2020 16:46:22 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41694/mercator-multiple-whole-genome-orthology-map-construction</link>
	<title><![CDATA[Mercator: Multiple Whole-Genome Orthology Map Construction]]></title>
	<description><![CDATA[<p><span>Whole-genome homology maps attempt to identify the evolutionary relationships between and within multiple genomes. The term "syntenic" is often used to describe regions of multiple genomes that are believed to have evolved from the same region in an ancestral genome. However, it has been pointed out that this use of the term is incorrect (</span><a href="https://www.biostat.wisc.edu/~cdewey/mercator/#refSynteny">Passarge et al. 1999</a><span>) and thus we will use the terms "homologous", "orthologous", and "paralogous" instead. Ideally, given K genomes, we would like to identify all orthologous genomic regions as well as paralogous regions within each genome and hypothetical ancestral genome. Maps listing these relationships are extremely valuable to researchers performing comparative analyses of genomic sequence. Here we present our initial work in the form a program called&nbsp;</span><em>Mercator</em><span>&nbsp;that constructs orthology maps between multiple whole genomes.</span></p><p>Address of the bookmark: <a href="https://www.biostat.wisc.edu/~cdewey/mercator/" rel="nofollow">https://www.biostat.wisc.edu/~cdewey/mercator/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/4636/molecular-and-computational-biology-research-school</guid>
  <pubDate>Fri, 20 Sep 2013 09:01:18 -0500</pubDate>
  <link></link>
  <title><![CDATA[Molecular and Computational Biology Research School]]></title>
  <description><![CDATA[
<p>The ambition of the Molecular and Computational Biology Research School (MCB) is to create an attractive and stimulating training environment for PhD students in molecular and computational biology, both to better serve the needs for relevant training in the field, and to stimulate crossdiscipline developments in the research of the parties.</p>

<p>http://www.uib.no/rs/mcb</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41459/jcvipython-utility-libraries-on-genome-assembly-annotation-and-comparative-genomics</guid>
	<pubDate>Tue, 17 Mar 2020 06:19:06 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41459/jcvipython-utility-libraries-on-genome-assembly-annotation-and-comparative-genomics</link>
	<title><![CDATA[JCVI:Python utility libraries on genome assembly, annotation and comparative genomics]]></title>
	<description><![CDATA[<p>Collection of Python libraries to parse bioinformatics files, or perform computation related to assembly, annotation, and comparative genomics.</p>
<p>https://github.com/tanghaibao/jcvi</p>
<p>More at https://github.com/tanghaibao/jcvi/wiki</p><p>Address of the bookmark: <a href="https://github.com/tanghaibao/jcvi" rel="nofollow">https://github.com/tanghaibao/jcvi</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/4888/murray-coxs-genomicus-lab</guid>
  <pubDate>Thu, 26 Sep 2013 16:42:42 -0500</pubDate>
  <link></link>
  <title><![CDATA[Murray Cox's Genomicus Lab]]></title>
  <description><![CDATA[
<p>This group interested in modeling genome dynamics in following topics:</p>

<p>---how genetic variation is distributed within and between individuals, <br />---determining how this diversity changes over evolutionary time.</p>

<p>Hence, Cox group work at the interface between biology, statistics and computer science to address questions of outstanding biological importance through intrepretation of large genetic datasets.</p>

<p>Profile:<br />Associate Professor Murray Cox, <br />Inaugural Rutherford Fellow of the Royal Society of New Zealand,  Principal Investigator in the BioProtection Research Center and Associate Investigator in the Allan Wilson Center for Molecular Ecology and Evolution<br />Email : m.p.cox@massey.ac.nz<br />Webpage: http://massey.genomicus.com/index.html</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/42936/ancient-whole-genome-duplication-wgd-detection-tools</guid>
	<pubDate>Sun, 07 Mar 2021 00:32:44 -0600</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/42936/ancient-whole-genome-duplication-wgd-detection-tools</link>
	<title><![CDATA[Ancient whole genome duplication (WGD) detection tools !]]></title>
	<description><![CDATA[<p>There are two methods for ancient WGD detection, one is collinearity analysis, and the other is based on the Ks distribution map. Among them, Ks is defined as the average number of synonymous substitutions at each synonymous site, and there is also a Ka corresponding to it, which refers to the average number of non-synonymous substitutions at each non-synonymous site.</p><p>At present, some people have posted articles about the analysis process of WGD. I searched for the keyword "wgd pipeline" and found the following:</p><p><strong>GenoDup: https:// github.com/MaoYafei/GenoDup-Pipeline</strong><br /><strong>https://peerj.com/articles/6303/</strong><br /><strong>WGDdetector: https:// github.com/yongzhiyang2 012/WGDdetector</strong><br /><strong>https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-019-2670-3</strong><br /><strong>wgd: https:// github.com/arzwa/wgd</strong><br /><strong>https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-016-1142-2#Sec1</strong><br /><strong>https://bmcbiol.biomedcentral.com/articles/10.1186/s12915-017-0399-x</strong><br /><strong>GeNoGAP https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-016-1142-2</strong><br /><strong>https://bmcbiol.biomedcentral.com/articles/10.1186/s12915-017-0399-x</strong><br /><strong>https://github.com/dfguan/purge_dups</strong><br /><strong>https://www.biorxiv.org/content/10.1101/2020.01.24.917997v1</strong></p><p>This article introduces the usage of wgd.</p><p>Wgd cannot be installed directly with bioconda at present, so it is a little troublesome to install, because it depends on a lot of software. wgd depends on the following software</p><p><strong>BLAST</strong><br /><strong>MCL</strong><br /><strong>MUSCLE/MAFFT/PRANK</strong><br /><strong>PAML</strong><br /><strong>PhyML/FastTree</strong><br /><strong>i-ADHoRe</strong></p><p>But the good news is that most of the software it depends on can be installed with bioconda</p><blockquote><p>conda create -n wgd python=3.5 blast mcl muscle mafft prank paml fasttree cmake libpng mpi=1.0=mpich<br />conda activate wgd</p></blockquote><p>Here mpi=1.0=mpich is selected, because i-adhore depends on mpich. If openmpi is installed, an error will appear while loading shared libraries: libmpi_cxx.so.40: cannot open shared object file: No such file or directory</p><p>After that, the installation is much simpler</p><blockquote><p>git clone https://github.com/arzwa/wgd.git<br />cd wgd<br />pip install .<br />pip install git+https://github.com/arzwa/wgd.git<br />For i-ADHoRe, you need to register at http:// bioinformatics.psb.ugent.be /webtools/i-adhore/licensing/Agree to the license to download i-ADHoRe-3.0</p></blockquote><p>Since my miniconda3 installed ~/opt/, the installation path is so~/opt/miniconda3/envs/wgd/</p><blockquote><p>tar -zxvf i-adhore-3.0.01.tar.gz<br />cd i-adhore-3.0.01<br />mkdir -p build &amp;&amp; cd build<br />cmake .. -DCMAKE_INSTALL_PREFIX=~/opt/miniconda3/envs/wgd/<br />make -j 4 <br />make insatall</p></blockquote><p>Take the sugarcane genome Saccharum spontaneum L as an example. The genome is 8-ploid with 32 chromosomes (2n = 4x8 = 32)</p><p><strong>Download the tutorial for CDS and GFF annotation files</strong></p><blockquote><p><strong>mkdir -p wgd_tutorial &amp;&amp; cd wgd_tutorial</strong><br /><strong>wget http://www.life.illinois.edu/ming/downloads/Spontaneum_genome/Sspon.v20190103.cds.fasta.gz</strong><br /><strong>wget http://www.life.illinois.edu/ming/downloads/Spontaneum_genome/Sspon.v20190103.gff3.gz</strong><br /><strong>gunzip *.gz</strong></p></blockquote><p>First conda activate wgdstart our analysis environment, and then start the analysis</p><p>Step 1 : Use to wgd mclidentify homologous genes in the genome</p><blockquote><p>wgd mcl -n 20 --cds --mcl -s Sspon.v20190103.cds.fasta -o Sspon_cds.out</p></blockquote><p>Step 2 : Use to wgd ksdbuild Ks distribution</p><blockquote><p>wgd ksd --n_threads 80 Sspon_cds.out/Sspon.v20190103.cds.fasta.blast.tsv.mcl Sspon.v20190103.cds.fasta</p></blockquote><p>Step 3 : If the quality of the genome is good, then wgd syncollinearity analysis can be used . It can help us find the collinearity block in the genome and the corresponding anchor point</p><blockquote><p>wgd syn --feature gene --gene_attribute ID \<br /> -ks wgd_ksd/Sspon.v20190103.cds.fasta.ks.tsv \<br /> Sspon.v20190103.gff3 Sspon_cds.out/Sspon.v20190103.cds.fasta.blast.tsv.mcl</p></blockquote><p>&nbsp;For more reading - There are 9 sub-modules in WGD</p><ul>
<li><span>kde: KDE fitting to the Ks distribution</span></li>
<li><span>ksd: Ks distribution construction</span></li>
<li><span>mcl: BLASP comparison of All-vs-ALl + MCL classification analysis.</span></li>
<li><span><span>mix: Hybrid modeling of Ks distribution.</span></span></li>
<li><span>pre: preprocess the CDS file</span></li>
<li><span>syn: Call I-ADHoRe 3.0 to use GFF files for collinearity analysis</span></li>
<li><span>viz: draw histogram and density plot</span></li>
<li><span>wf1: Ks standard analysis procedure of the whole genome paranome (paranome), call mcl, ksd and syn</span></li>
<li><span>wf2: Ks standard analysis procedure of one-vs-one homologous gene (ortholog), call wcl and kSD</span></li>
</ul>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
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