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<channel>
	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/27696?offset=550</link>
	<atom:link href="https://bioinformaticsonline.com/related/27696?offset=550" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
	
<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/19597/assistant-professor-at-gauhati-university-guwahati</guid>
  <pubDate>Tue, 16 Dec 2014 01:15:30 -0600</pubDate>
  <link></link>
  <title><![CDATA[Assistant Professor at GAUHATI UNIVERSITY, GUWAHATI]]></title>
  <description><![CDATA[
<p>Advt. No.T/2014/4</p>

<p>Ref. No. GU/Estt/T/308(VI)/2014/6451-61</p>

<p>Applications are invited from the Indian citizens for five (5) teaching posts of Assistant Professor (Contractual) under various departments of Gauhati University. Details of the advertisement, other terms and conditions and the application forms are available in the University website www.gauhati.ac.in</p>

<p>Asstt. Professor (Contractual)</p>

<p>    2. M.Sc. Microbiology Course in Botany</p>

<p>    3 1.M.Sc. Microbiology/M.Sc. Botany (Specialization in Microbiology)/M.Sc. Biochemistry (1 post). (Preference will be given to candidates having experience in Biochemistry).</p>

<p>    2.M.Sc. Microbiology/M.Sc. Botany (Specialization in Microbiology)/M.Sc. Biotechnology(1 post). (Preference will be given to candidates having experience in Bioinformatics).</p>

<p>    3.M.Sc. Microbiology/M.Sc. Botany (Specialization in Microbiology)/M.Sc.  Biotechnology(1 post). (Preference will be given to candidates having experience in Microbial Genetics).</p>

<p>As per UGC norms</p>

<p>Pay Band &amp; Academic Grade Pay : (Consolidated pay) : Rs. 21,600/- per month</p>

<p>Application Form : Prescribe application form may download from the G.U. website www.gauhati.ac.in</p>

<p>Last date of receipt of filled-in application is 08.01.2015.</p>

<p>Advertisement: www.gauhati.ac.in/openfile.php?file=Notice1258.pdf</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44322/genome-context-viewer-gcv</guid>
	<pubDate>Sun, 21 May 2023 19:33:43 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44322/genome-context-viewer-gcv</link>
	<title><![CDATA[Genome Context Viewer (GCV)]]></title>
	<description><![CDATA[<p><span>The Genome Context Viewer (GCV) is a web-app that visualizes genomic context data provided by third party services. Specifically, it uses functional annotations as a unit of search and comparison. By adopting a common set of annotations, data-store operators can deploy federated instances of GCV, allowing users to compare genomes from different providers in a single interface.</span></p><p>Address of the bookmark: <a href="https://github.com/legumeinfo/gcv" rel="nofollow">https://github.com/legumeinfo/gcv</a></p>]]></description>
	<dc:creator>LEGE</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/19695/china-university-of-macau-phd-position-2015-in-bioinformatics-computer-science</guid>
  <pubDate>Mon, 22 Dec 2014 00:12:49 -0600</pubDate>
  <link></link>
  <title><![CDATA[China University of Macau PhD Position 2015 in Bioinformatics, Computer Science]]></title>
  <description><![CDATA[
<p>The Computational Biology and Bioinformatics Group at the University of Macau is inviting applications for PhD Position. Applicants will work on a research project focusing on the flexible receptor protein-ligand docking algorithms for computer-aided drug design.  The candidate will be working as part of a team in developing novel metaheuristic algorithms and scoring functions for large-scale, highly flexible protein-ligand docking problems. The duration of this PhD position is 2-3 years, starting in August 2015. Remuneration paid to candidate is MOP 11000-14000/month (~USD 1375-1750/month). The applications should be submitted before March 2015.</p>

<p>Study Subject(s): PhD position is award in the field of Bioinformatics/Computer Science.<br />Course Level: Position is available for pursuing PhD degree level at the University of Macau.<br />Scholarship Provider: University of Macau<br />Scholarship can be taken at: China</p>

<p>Eligibility: The ideal candidate would be a master degree holder in Bioinformatics or related disciplines with knowledge in Medical sciences or Life sciences (with GPA of at least 3.0 on a 4-point scale or equivalent) . Knowledge in programming (C and C++) and Linux scripting are necessary; experience in molecular docking, molecular dynamics simulations or molecular modeling is an advantage. The candidate should be fluent in spoken and written English; preference will be given to applicants with good publication records in relevant areas.</p>

<p>Scholarship Open for International Students: Researchers from China can apply for this PhD position.</p>

<p>Scholarship Description:</p>

<p>The Computational Biology and Bioinformatics Group at the University of Macau is looking for a motivated PhD student in Bioinformatics or Computer Science to work on a research project focusing on the flexible receptor protein-ligand docking algorithms for computer-aided drug design.  The candidate will be working as part of a team in developing novel metaheuristic algorithms and scoring functions for large-scale, highly flexible protein-ligand docking problems.</p>

<p>Number of award(s): There is only one PhD position available.</p>

<p>Duration of award(s): The duration of this PhD position is 2-3 years.</p>

<p>What does it cover? Remuneration paid to candidate is  MOP 11000-14000/month (~USD 1375-1750/month).</p>

<p>Selection Criteria: Not Known</p>

<p>Notification: Not Known</p>

<p>How to Apply: Send your current CV, your academic transcripts, a letter of motivation and research interests, two letters of recommendations from academic faculty to Dr. Shirley Siu at shirleysiu[at]umac.mo before March 2015.</p>

<p>Scholarship Application Deadline: The applications should be submitted before March 2015.</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44491/cgviewjs-is-a-circular-genome-viewing-tool</guid>
	<pubDate>Wed, 27 Mar 2024 11:16:24 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44491/cgviewjs-is-a-circular-genome-viewing-tool</link>
	<title><![CDATA[CGView.js is a Circular Genome Viewing tool]]></title>
	<description><![CDATA[<p>CGView.js is a&nbsp;<span>C</span>ircular&nbsp;<span>G</span>enome&nbsp;<span>View</span>ing tool for visualizing and interacting with small genomes. This software is an adaptation of the Java program&nbsp;<a href="https://paulstothard.github.io/cgview/">CGView</a>.</p>
<div>
<p>CGView.js is the genome viewer of Proksee, an expert system for genome assembly, annotation and visualization.</p>
<a href="https://proksee.ca/"></a></div>
<h1 id="features">Features</h1>
<ul>
<li>
<p>Circular and linear views of genomes</p>
</li>
<li>
<p>Capable of drawing genomes up to 10 Mbp with 1000's of features and 100's contigs</p>
</li>
<li>
<p>Smooth zooming down to the sequence level</p>
</li>
<li>
<p>Easily generate features and plots directly form the sequence (e.g. ORFs, GC-content and GC-Skew)</p>
</li>
<li>
<p>Save high resolution PNG maps up to 8000x8000px</p>
</li>
<li>
<p>Fully documented API for interacting with CGView.js maps</p>
</li>
</ul><p>Address of the bookmark: <a href="https://js.cgview.ca/" rel="nofollow">https://js.cgview.ca/</a></p>]]></description>
	<dc:creator>LEGE</dc:creator>
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<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/19811/jnu-neurosciencesystems-biologymathematical-modeling-jrf-vacancies</guid>
  <pubDate>Fri, 26 Dec 2014 11:22:20 -0600</pubDate>
  <link></link>
  <title><![CDATA[JNU Neuroscience/Systems Biology/Mathematical modeling JRF Vacancies]]></title>
  <description><![CDATA[
<p>School of Computational and Integrative Sciences<br />Jawaharlal Nehru University<br />New Delhi 110067</p>

<p>Recruitment for Project</p>

<p>Applications were invited from the citizens of India for filling up the following temporary position for the CSIR sponsored Fellowship in the School of Computational and Integrative Sciences, Jawaharlal Nehru University, New Delhi 110067. This position is temporary for a period of two and half years or tenable only for the duration of the project. The requisite qualifications &amp; experience are given below.</p>

<p>Project Title : "Understanding Complex dynamics and Information processing in Brain Networks"<br />Funding Agency : CSIR</p>

<p>Principal Investigator : Dr. R.K. Brojen Singh</p>

<p>Position : Junior Research Fellow(One post)</p>

<p>Salary : As per CSIR rules and guidelines for JRF.</p>

<p>Qualifications &amp; Experience : M.Sc. in Physics/Mathematics/Biology/B.Tech. In Eng. Physics/Comp. Sc. and desirable CSIR-UGC NET Qualified. Candidates should also have at least one years research experience after M. Sc./B.Tech. in works related to Neuroscience/Mathematical modeling.</p>

<p>Candidates possessing requisite qualifications may apply either on plain paper stating the project title along with CV and send to the following address or send as email attachment (pdf or word format) so as to reach on or before 8 January, 2014.</p>

<p>Dr. R.K. Brojen Singh<br />School of Computational and Integrative Sciences<br />Jawharlal Nehru University<br />New Delhi 110067<br />Email: brojen@jnu.ac.in, brojen@mail.jnu.ac.in</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/44722/step-by-step-guide-to-running-genome-assembly</guid>
	<pubDate>Fri, 13 Dec 2024 11:35:55 -0600</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/44722/step-by-step-guide-to-running-genome-assembly</link>
	<title><![CDATA[Step-by-Step Guide to Running Genome Assembly]]></title>
	<description><![CDATA[<p>Genome assembly is a critical process in bioinformatics, enabling the reconstruction of an organism's genome from short DNA sequence reads. Whether you&rsquo;re working on a new microbial genome or a complex eukaryotic organism, this guide will walk you through the steps of genome assembly using state-of-the-art tools and best practices.</p><h4><strong>What is Genome Assembly?</strong></h4><p>Genome assembly involves piecing together short DNA sequence reads generated by sequencing platforms (e.g., Illumina, PacBio, Oxford Nanopore) into longer, contiguous sequences called contigs. This can be performed as:</p><ul>
<li><strong>De Novo Assembly</strong>: Without a reference genome.</li>
<li><strong>Reference-Guided Assembly</strong>: Using a reference genome to guide the assembly process.</li>
</ul><h4><strong>Step 1: Preparing Your Data</strong></h4><p>Before starting the assembly, ensure that your raw sequencing data is high quality.</p><ol>
<li>
<p><strong>Input Data</strong></p>
<ul>
<li><strong>Short Reads</strong>: Illumina sequencing generates short, accurate reads ideal for scaffolding.</li>
<li><strong>Long Reads</strong>: PacBio and Nanopore sequencing provide long reads for resolving repetitive regions.</li>
</ul>
</li>
<li>
<p><strong>Quality Control (QC)</strong><br />Use tools like <strong>FastQC</strong> or <strong>MultiQC</strong> to assess the quality of your reads:</p>
<div>
<div dir="ltr"><code>fastqc reads.fastq multiqc . </code></div>
</div>
<p>Look for issues like low-quality bases, adapter contamination, or overrepresented sequences.</p>
</li>
<li>
<p><strong>Read Trimming and Filtering</strong><br />Trim low-quality bases and adapters using <strong>Trimmomatic</strong> or <strong>Cutadapt</strong>:</p>
<div>
<div dir="ltr"><code>trimmomatic PE reads_R1.fastq reads_R2.fastq trimmed_R1.fastq trimmed_R2.fastq \ ILLUMINACLIP:adapters.fa:2:30:10 LEADING:3 TRAILING:3 SLIDINGWINDOW:4:20 MINLEN:36 </code></div>
</div>
</li>
</ol><h4><strong>Step 2: Choosing an Assembly Strategy</strong></h4><p>Select an assembly strategy based on your data type:</p><ul>
<li>
<p><strong>Short-Read Assemblers</strong>:</p>
<ul>
<li>SPAdes: Popular for microbial genomes.</li>
<li>Velvet: Fast for smaller genomes.</li>
</ul>
</li>
<li>
<p><strong>Long-Read Assemblers</strong>:</p>
<ul>
<li>Canu: Ideal for long-read datasets.</li>
<li>Flye: Versatile for small and large genomes.</li>
</ul>
</li>
<li>
<p><strong>Hybrid Assemblers</strong>:</p>
<ul>
<li>MaSuRCA: Combines short and long reads.</li>
<li>Unicycler: Optimized for bacterial genomes.</li>
</ul>
</li>
</ul><h4><strong>Step 3: Running the Assembly</strong></h4><h5><strong>3.1. SPAdes (Short-Read Assembly)</strong></h5><p>SPAdes is an excellent choice for small genomes, such as bacteria.</p><div><div dir="ltr"><code>spades.py -1 trimmed_R1.fastq -2 trimmed_R2.fastq -o spades_output </code></div></div><p>The output includes assembled contigs (<code>contigs.fasta</code>) and scaffolds (<code>scaffolds.fasta</code>).</p><h5><strong>3.2. Canu (Long-Read Assembly)</strong></h5><p>Canu is designed for high-error long reads from PacBio or Nanopore.</p><div><div dir="ltr"><code>canu -p genome -d canu_output genomeSize=4.7m -nanopore-raw reads.fastq </code></div></div><p>The output will be in <code>canu_output/genome.contigs.fasta</code>.</p><h5><strong>3.3. Hybrid Assembly with Unicycler</strong></h5><p>Unicycler combines short and long reads for improved assemblies.</p><div><div dir="ltr"><code>unicycler -1 trimmed_R1.fastq -2 trimmed_R2.fastq -l long_reads.fastq -o unicycler_output </code></div></div><h4><strong>Step 4: Assessing Assembly Quality</strong></h4><p>After assembly, evaluate its quality using the following tools:</p><ol>
<li>
<p><strong>QUAST</strong><br />QUAST generates assembly statistics, such as N50, genome size, and GC content:</p>
<div>
<div dir="ltr"><code>quast contigs.fasta -o quast_output </code></div>
</div>
</li>
<li>
<p><strong>BUSCO</strong><br />BUSCO checks genome completeness by identifying conserved genes:</p>
<div>
<div dir="ltr"><code>busco -i contigs.fasta -o busco_output -l fungi_odb10 -m genome </code></div>
</div>
</li>
<li>
<p><strong>Assembly Graph Visualization</strong><br />Visualize assembly graphs with <strong>Bandage</strong>:</p>
<div>
<div dir="ltr"><code>Bandage load assembly_graph.gfa </code></div>
</div>
</li>
</ol><hr><h4><strong>Step 5: Post-Assembly Steps</strong></h4><ol>
<li>
<p><strong>Polishing</strong><br />Improve assembly accuracy using tools like <strong>Pilon</strong> (for short reads) or <strong>Racon</strong> (for long reads).</p>
<div>
<div dir="ltr"><code>racon long_reads.fasta mapped_reads.sam contigs.fasta &gt; polished_contigs.fasta </code></div>
</div>
</li>
<li>
<p><strong>Scaffolding</strong><br />Link contigs into scaffolds using tools like <strong>SSPACE</strong> or <strong>Opera-LG</strong> if required.</p>
</li>
<li>
<p><strong>Annotation</strong><br />Annotate the assembled genome using <strong>Prokka</strong> for prokaryotes or <strong>Maker</strong> for eukaryotes.</p>
<div>
<div dir="ltr"><code>prokka --outdir annotation_output --prefix genome contigs.fasta </code></div>
</div>
</li>
</ol><h4><strong>Step 6: Sharing and Archiving</strong></h4><ol>
<li>
<p><strong>Submit to Public Repositories</strong><br />Share your assembly in databases like <strong>NCBI GenBank</strong>, <strong>ENA</strong>, or <strong>DDBJ</strong>.</p>
</li>
<li>
<p><strong>Metadata Preparation</strong><br />Include detailed metadata for your submission, such as organism name, sequencing platform, and coverage.</p>
</li>
</ol><h4><strong>Best Practices</strong></h4><ul>
<li>Always perform quality checks at each stage to ensure data integrity.</li>
<li>Use multiple tools to cross-validate results when working with complex genomes.</li>
<li>Document parameters and software versions for reproducibility.</li>
</ul><h4><strong>Conclusion</strong></h4><p>Genome assembly is a powerful process that transforms raw sequencing data into a coherent representation of an organism&rsquo;s genome. By following this step-by-step guide, you can successfully assemble genomes and uncover valuable biological insights. Whether you&rsquo;re assembling a microbial genome or tackling the complexities of a eukaryotic genome, these tools and strategies will set you on the path to success.</p>]]></description>
	<dc:creator>Abhi</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/44775/genomic-architecture-surrounding-the-fusion-site-of-human-chromosome-2</guid>
	<pubDate>Tue, 04 Mar 2025 12:26:29 -0600</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/44775/genomic-architecture-surrounding-the-fusion-site-of-human-chromosome-2</link>
	<title><![CDATA[Genomic architecture surrounding the fusion site of human chromosome 2]]></title>
	<description><![CDATA[<p>The article <strong>"Genomic Structure and Evolution of the Ancestral Chromosome Fusion Site in 2q13&ndash;2q14.1 and Paralogous Regions on Other Human Chromosomes (https://pmc.ncbi.nlm.nih.gov/articles/PMC187548/)"</strong> explores the genomic architecture surrounding the fusion site of human chromosome 2. This fusion event is a key evolutionary marker distinguishing humans from other great apes, as humans have 46 chromosomes while chimpanzees, gorillas, and orangutans possess 48. The fusion occurred through an end-to-end joining of two ancestral chromosomes, which remain separate in nonhuman primates.</p><h3><strong>Key Findings:</strong></h3><ol>
<li>
<p><strong>Chromosomal Fusion and Its Molecular Signature:</strong></p>
<ul>
<li>The fusion site is located at <strong>2q13&ndash;2q14.1</strong> and is characterized by <strong>degenerate telomeric sequences</strong> appearing interstitially, indicating the historical head-to-head joining of ancestral chromosomes.</li>
<li>Despite being a signature of a past fusion event, these telomeric repeats are no longer functional and have undergone sequence degradation over time.</li>
</ul>
</li>
<li>
<p><strong>Extensive Duplications in the Surrounding Genomic Region:</strong></p>
<ul>
<li>The study identifies <strong>large-scale segmental duplications</strong> flanking the fusion site, with several of these regions duplicated and scattered across multiple chromosomes.</li>
<li>These duplications are predominantly located in <strong>subtelomeric and pericentromeric regions</strong>, suggesting their role in genomic instability and chromosomal evolution.</li>
</ul>
</li>
<li>
<p><strong>Paralogous Regions and Their Evolutionary Relationships:</strong></p>
<ul>
<li>A <strong>168-kilobase (kb) segment</strong> near the fusion site has <strong>98%&ndash;99% sequence identity</strong> with three regions on <strong>chromosome 9 (9pter, 9p11.2, and 9q13)</strong>.</li>
<li>Another <strong>67-kb region distal to the fusion site</strong> shows a high degree of homology to sequences in <strong>chromosome 22qter</strong>.</li>
<li>Additionally, a <strong>100-kb segment</strong> exhibits <strong>96% sequence identity</strong> with a region in <strong>chromosome 2q11.2</strong>.</li>
</ul>
</li>
<li>
<p><strong>Comparative Genomics and Evolutionary Implications:</strong></p>
<ul>
<li>By comparing the duplicated sequences and their arrangement in primates, the researchers traced the order of duplication events leading to their present distribution.</li>
<li>The presence of specific repetitive elements within these duplicated segments serves as <strong>evolutionary markers</strong> that help infer their historical rearrangements.</li>
<li>Some of these <strong>duplicated regions are associated with chromosomal inversion breakpoints</strong>, potentially contributing to evolutionary changes in primates.</li>
<li>Recurrent <strong>structural rearrangements</strong> in these regions have been linked to human chromosomal disorders.</li>
</ul>
</li>
</ol><h3><strong>Conclusions and Implications:</strong></h3><ul>
<li>The findings provide valuable insights into <strong>the structural evolution of human chromosome 2</strong>, which played a crucial role in human speciation.</li>
<li>Understanding these <strong>segmental duplications</strong> and their evolutionary trajectories sheds light on <strong>genomic instability</strong>, which may contribute to <strong>human genetic diseases</strong>.</li>
<li>The study highlights how large-scale chromosomal rearrangements, such as fusion and duplication, have influenced the <strong>evolutionary divergence of humans</strong> from other primates.</li>
</ul><p>This research advances our understanding of <strong>human genome evolution</strong> and offers a foundation for studying the effects of <strong>structural variants in genetic disorders</strong>.</p>]]></description>
	<dc:creator>LEGE</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/20015/illumina-smartphone-chip</guid>
	<pubDate>Tue, 30 Dec 2014 23:19:54 -0600</pubDate>
	<link>https://bioinformaticsonline.com/news/view/20015/illumina-smartphone-chip</link>
	<title><![CDATA[Illumina Smartphone Chip !!!]]></title>
	<description><![CDATA[<p>Illumina, the company that claims it brought human genome sequencing down to $1000 prices, has now turned its attention to a consumer product - a chip that you can plug into your smartphone and have it read your genetic information.<br /><br />The biggest challenge ahead of Illumina is simplifying the process of genetic sequencing. Currently, Illumina&rsquo;s DNA sequencers are gigantic machines that use techinques like colorimetry to work, but while the core technology is computational, it takes some 30 steps to extract genetic data and run it through. This process will likely have to be hugely simplified on mobile devices, given the fact that some studies require extracting 10 mililiters of blood. Illumina researchers are also working on finding the optimal technology for this on-chip DNA sequencing - be it electrical, optical, or other.<br /><br />Illumina is one of the most prominent names in genetics, often said to be the Intel of genetic sequencing, as just like Intel it provides the algorithms, the processing brain that runs a DNA reading task.<br /><br />In other recent smartphone-related biotech news, drug company Pfizer launched its REMOTE project, a new type of clinical trial that does not require going to a hospital for checks - targeted at patients with overactive bladder problems, the FDA-approved REMOTE project allowed to gather data from patients from over 10 states remotely, via mobile devices.<br /><br /></p><p>This is indeed the Illumina answer to Apple's Health app, HealthBook, Google HealthFit.</p>]]></description>
	<dc:creator>Robert M Willioms</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/45267/when-thousands-of-bacterial-genomes-become-one-giant-map</guid>
	<pubDate>Thu, 27 Aug 2026 10:56:47 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/45267/when-thousands-of-bacterial-genomes-become-one-giant-map</link>
	<title><![CDATA[When Thousands of Bacterial Genomes Become One Giant Map]]></title>
	<description><![CDATA[<p>Imagine trying to understand a city by studying just one house.</p><p>You might learn a lot about that house&mdash;the rooms, the doors, the furniture&mdash;but you would miss the bigger story: the streets, the neighborhoods, and all the ways the city changes from one place to another.</p><p>Something similar happens when scientists study bacterial genomes one at a time.</p><p>Over the past decade, researchers have collected thousands of bacterial genomes. These genomes contain an enormous amount of information about how bacteria survive, adapt, and evolve. But comparing thousands of individual genomes can quickly become a computational maze.</p><p>That is where PANORAMA enters the story.</p><p>Developed by J&eacute;r&ocirc;me Arnoux and colleagues, PANORAMA is a computational tool designed to explore bacterial pangenomes&mdash;the complete collection of genetic possibilities found across a species or group of related organisms. Instead of looking at every genome as an isolated object, the approach represents their shared and variable genetic features as a graph.</p><p>Think of this graph as a giant subway map.</p><p>Some stations appear on almost every route. These represent genes that are highly conserved. Other stations appear only on certain routes, representing genes that some bacteria possess while others do not. By looking at the entire network, scientists can begin to see not just *what genes exist*, but how they are organized and how biological systems are distributed across populations.</p><p>The researchers put PANORAMA to the test using 941 genomes of Pseudomonas aeruginosa, a bacterium important in human health. They used the tool to investigate biological systems, including bacterial defense mechanisms against viruses known as bacteriophages. They then expanded the analysis to more than 6,000 genomes from four Enterobacteriaceae species.</p><p>The result is more than a faster way to process data.</p><p>PANORAMA allows researchers to ask a bigger question: What can an entire microbial species do, genetically speaking?</p><p>By comparing pangenomes, the researchers could identify systems shared between species as well as distinctive features. They could also find recurring genomic locations where genetic material is inserted&mdash;clues that may reveal common evolutionary processes.</p><p>And this is perhaps the most exciting part of the story.</p><p>Every bacterial genome is like a page in a huge evolutionary book. Until recently, reading thousands of those pages together was difficult. PANORAMA provides a way to turn those pages into a map, allowing scientists to see patterns that might disappear when each genome is studied separately.</p><p>The study, published in PLOS Computational Biology in July 2026, presents PANORAMA as a foundation for large-scale comparative pangenomics. The software and accompanying analysis resources are openly available, giving other researchers the opportunity to explore microbial diversity themselves.</p><p>So the story is not really about one bacterium or one genome.</p><p>It is about changing the way we look at life.</p><p>Instead of asking, &ldquo;What is inside this genome?&rdquo;, scientists can increasingly ask, &ldquo;What is the full genetic landscape of this species&mdash;and how did it become this way?&rdquo;</p><p>And sometimes, when you stop looking at one house and finally see the whole city, the most interesting discoveries are hiding in the streets between them.</p><p>Read more at&nbsp;https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1013856</p>]]></description>
	<dc:creator>LEGE</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/20449/walk-in-interview-for-the-post-of-jrf-and-project-assistant-cift</guid>
  <pubDate>Tue, 20 Jan 2015 23:03:20 -0600</pubDate>
  <link></link>
  <title><![CDATA[WALK-IN-INTERVIEW for the post of JRF and Project Assistant @ CIFT]]></title>
  <description><![CDATA[
<p>Eligible candidates are invited to attend a walk-in-Interview with all relevant documents for the following positions of Project Fellows (on contractual basis) to work in the Project “ Genetic Diversity of Clostridium botulinum in seafood and Development of Lateral Flow Immuno Assay (LFIA) for toxinotyping  funded by Department of Biotechnology.   The duration of the project is 3 years / co-terminus with the scheme.</p>

<p>Jr. Research Fellow – 2 posts</p>

<p>    Fellowship    :   Rs. 25000/- + 20% HRA pm  for Ist &amp; 2nd year and Rs.28000/- + HRA on 3rd year</p>

<p>    Qualification :    Ist class Masters Degree in Microbiology/Fishery Microbiology/Bio-technology.</p>

<p>    Desirable        :  </p>

<p>    1. CSIR/UGC NET/JRF qualified</p>

<p>    2. Excellent analytical skills and computer documentation</p>

<p>    3. Prior experience in handling microbial cultures and molecular techniques</p>

<p>Project Assistant – 1 post</p>

<p>Fellowship    :    Rs.8000/- p.m (consolidated)</p>

<p>Qualification:   Masters degree in Microbiology/Biotechnology with skill in Bioinformatics</p>

<p>Desirable:   Excellent analytical skills in Bioinformatics and computer documentation</p>

<p>Terms &amp; Conditions:</p>

<p>Registration will begin at 8.30 a.m and will close at 11.00 am<br />Age limit (as on 29.1.2015):  Below 35 years for men and 40 years for women.<br />Age relaxation of 3 year for OBC candidates and 5 years for SC/ST candidates is permissible.<br />Candidates are required to submit self-attested copies of all the Certificates in support of their claims    regarding age, educational qualifications, scheduled caste/scheduled tribe/OBC etc.  The original certificates shall be produced for verification before the interview.<br />Candidates should bring detailed bio-data (in the enclosed format)  affixing a recent passport size photograph.<br />The selected candidate will be recruited on contract basis under ICAR norms.  The post is purely temporary and is co-terminus with the project.<br />The candidates attending the interview should ensure that they fulfil all the eligibility conditions.  No correspondence will be entertained from the candidates for selection/test/appointment.<br />No TA/DA will be paid to attend the interview.<br />Canvassing in any form will render the candidate disqualified for the post.<br />The Director’s decision will be final and binding in all aspects regarding the selection to the post.</p>

<p>Venue: CIFT, Matsyapuri.P.O, Cochin                  Date of interview:  29.01.2015          Time:  10.00 am</p>

<p>http://www.cift.res.in/uploads/userfiles/file/file/srf%20appn.doc</p>
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