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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/28844?offset=410</link>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/17751/jrf-in-bioinformatics-inmas-drdodelhi</guid>
  <pubDate>Wed, 01 Oct 2014 07:01:07 -0500</pubDate>
  <link></link>
  <title><![CDATA[JRF in Bioinformatics @ INMAS, DRDO,Delhi]]></title>
  <description><![CDATA[
<p>Institute of Nuclear Medicine and Allied Sciences (INMAS), Delhi under the aegis of Defence Research and Development Organisation (DRDO), is engaged in research and developmental work in radiation sciences, Neuro-Computing and Medical Image Processing. INMAS is looking for meritorious young researchers for pursuing research in the frontier areas at INMAS. The Institute invites applications from young and meritorious Indian nationals who are creative, have passion and desire to pursue R&amp;D in frontier areas. INMAS possesses ambience of a research cum academic institute coupled with an advanced R&amp;D infrastructure in a mission mode. It provides the best infrastructure, motivation and personality development prospects for talented students, dreaming of unparalleled success in their professional endeavors. INMAS provides state of the art research facilities for undertaking pioneering research with defence applications. </p>

<p>JRF (Maximum Tenure‐ Five Years: 2yrs as JRF and 3yrs  as SRF) 	<br />A first class Master’s Degree in Bioinformatics (likely 2 posts) 	<br />Around Rs 16,000/ Plus 30% HRA (as per rules of funding agency)</p>

<p>Applications are invited from candidates possessing the above qualifications. The upper age limit is as on the last date for receipt of application. (5 years relaxation to SC/ST candidates, 3 years to OBC candidates, and other entitled categories as per Govt rules). Actual No. of vacancies may vary.</p>

<p>Application form can be download from the website www.drdo.gov.in and E Mailed to inmashrd@gmail.com.<br />Last date to apply by email is 1700 hrs on 15 Oct 2014<br />Incomplete applications are liable to be rejected.<br />Confirmation will be sent to short-listed candidates through email only<br />Antecedents of selected candidates will be verified.<br />Written Test will be conducted from 0930-1030 hrs. Latecomers will not be considered.<br />Candidates will be required to produce certificates/testimonials in original at the time of interview.<br />It may please be noted that offer of Fellowship does not confer on fellows any right for absorption in DRDO.<br />Candidates should carry photocopy of Application form sent by email with them.<br />No TA/DA will be paid for attending interview &amp; on joining.<br />Last date to apply by email is 1700 hrs on 15 Oct 2014</p>

<p>More at http://drdo.gov.in/drdo/English/jrf29092014.pdf<br />http://drdo.gov.in/drdo/English/index.jsp?pg=inmas29092014.jsp</p>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/44766/genome-simulation-with-slim-and-msprime</guid>
	<pubDate>Fri, 31 Jan 2025 12:47:43 -0600</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/44766/genome-simulation-with-slim-and-msprime</link>
	<title><![CDATA[Genome Simulation with SLiM and msprime]]></title>
	<description><![CDATA[<p>Genome simulation is an essential tool in population genetics, enabling researchers to model evolutionary processes and study genetic variation. Two widely used simulation tools in this field are <strong style="font-size: 12.8px;">SLiM</strong><span style="font-size: 12.8px; font-weight: normal;"> and </span><strong style="font-size: 12.8px;">msprime</strong><span style="font-size: 12.8px; font-weight: normal;">. While both serve different purposes, they can be used together with the </span><strong style="font-size: 12.8px;">slendr</strong><span style="font-size: 12.8px; font-weight: normal;"> framework to compare simulation outputs effectively.</span></p><h2>Overview of SLiM and msprime</h2><h3>SLiM: Forward Genetic Simulator</h3><p>SLiM is a <strong>free, open-source</strong> tool designed for forward genetic simulations. It allows researchers to model complex evolutionary scenarios, including selection, recombination, and demographic events, making it particularly useful for studying adaptation and selection in populations.</p><p><strong>Key Features of SLiM:</strong></p><ul>
<li>
<p>Simulates population evolution forward in time</p>
</li>
<li>
<p>Supports custom evolutionary models using an embedded scripting language</p>
</li>
<li>
<p>Allows modeling of spatial and ecological dynamics</p>
</li>
<li>
<p>Provides high flexibility and extensibility for user-defined scenarios</p>
</li>
<li>
<p>Available on GitHub as an open-source project</p>
</li>
</ul><h3>msprime: Ancestry and Mutation Simulator</h3><p>msprime is an efficient, <strong>open-source</strong> tool that simulates ancestry and mutations using a coalescent framework. It is known for its high-speed performance and low memory requirements, making it a popular choice for large-scale genomic simulations.</p><p><strong>Key Features of msprime:</strong></p><ul>
<li>
<p>Implements coalescent simulations for ancestry modeling</p>
</li>
<li>
<p>Efficiently simulates large population histories</p>
</li>
<li>
<p>Supports the addition of mutations to genealogies</p>
</li>
<li>
<p>Developed using an open-source community model</p>
</li>
<li>
<p>Often faster and more memory-efficient than alternative simulators</p>
</li>
</ul><h2>Using SLiM and msprime with slendr</h2><p>Both SLiM and msprime can be integrated with <strong>slendr</strong>, a framework that facilitates structured population genetic simulations. This integration allows for seamless comparison of simulation outputs.</p><h3>How They Work Together:</h3><ul>
<li>
<p>SLiM and msprime simulations can be analyzed within slendr.</p>
</li>
<li>
<p>The <strong>ts_read()</strong> function in slendr enables loading and comparing tree sequence outputs from both simulators.</p>
</li>
<li>
<p>This integration allows researchers to validate simulation results and gain deeper insights into evolutionary processes.</p>
</li>
</ul><h2>Performance Considerations</h2><p>While SLiM offers powerful forward simulations with extensive customization, msprime is often preferred for its <strong>speed and memory efficiency</strong> when simulating ancestry and mutations. The choice between the two depends on the research goals:</p><ul>
<li>
<p><strong>For detailed evolutionary modeling with selection and recombination:</strong> Use SLiM.</p>
</li>
<li>
<p><strong>For large-scale coalescent simulations with mutations:</strong> Use msprime.</p>
</li>
<li>
<p><strong>For comparing different simulation models and their outputs:</strong> Use slendr to integrate SLiM and msprime results.</p>
</li>
</ul><h2>Conclusion</h2><p>SLiM and msprime are valuable tools for genome simulation, each serving distinct but complementary purposes in population genetics research. By leveraging the strengths of both simulators with slendr, researchers can conduct robust and efficient evolutionary simulations, enhancing our understanding of genetic diversity and adaptation.</p><p>For more information, check out the official GitHub repositories for <strong>SLiM</strong> and <strong>msprime</strong>, and explore the <strong>slendr</strong> framework for streamlined simulation workflow</p>]]></description>
	<dc:creator>BioStar</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/17966/internship-program-for-bioinformatics-biotechnology-professionals-no-of-vacancy-2</guid>
  <pubDate>Wed, 08 Oct 2014 01:10:08 -0500</pubDate>
  <link></link>
  <title><![CDATA[Internship Program for Bioinformatics / Biotechnology Professionals (No. Of Vacancy: 2)]]></title>
  <description><![CDATA[
<p>ArrayGen is offering an Internship Program for Post graduate Bioinformatics / Biotechnology students and professionals. ArrayGen Technologies provide an excellent opportunity to gain research experience and explore if a scientific career is right for you. Currently we offer positions to outstanding students interested in Next Generation Sequencing (NGS) data analysis. Applications are accepted throughout the year. Accepted students will be listed on web with their schedules. Accepted students can attend our future workshops and trainings freely at the specified venue.</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/view/2044</guid>
	<pubDate>Mon, 12 Aug 2013 12:19:29 -0500</pubDate>
	<link>https://bioinformaticsonline.com/view/2044</link>
	<title><![CDATA[Does anyone have Nanopore latest updates?]]></title>
	<description><![CDATA[<p>There was a lot of buzz about&nbsp;<span>Oxford Nanopore Technologies&reg; is developing the GridION&trade; system and miniaturised MinION&trade; device. These are a new generation of electronic molecular analysis system for use in scientific research, personalised medicine, crop science, security/defence and more. The platform technology uses nanopores to analyse single molecules including DNA/RNA and proteins. With a broad patent portfolio, the Oxford Nanopore pipeline includes biological nanopores and solid-state nanopores.</span></p><p>Is this available, or still under trial mode?&nbsp;</p><p><a href="https://www.nanoporetech.com/">https://www.nanoporetech.com/</a></p><p><a href="https://www.nanoporetech.com/technology/the-minion-device-a-miniaturised-sensing-system/the-minion-device-a-miniaturised-sensing-system">https://www.nanoporetech.com/technology/the-minion-device-a-miniaturised-sensing-system/the-minion-device-a-miniaturised-sensing-system</a></p>]]></description>
	<dc:creator>Poonam Mahapatra</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/videolist/watch/18381/how-far-can-bioinformatics-go-creating-organisms-used-for-testing</guid>
	<pubDate>Fri, 17 Oct 2014 02:08:16 -0500</pubDate>
	<link>https://bioinformaticsonline.com/videolist/watch/18381/how-far-can-bioinformatics-go-creating-organisms-used-for-testing</link>
	<title><![CDATA[How far can bioinformatics go creating organisms used for testing?]]></title>
	<description><![CDATA[<iframe width="" height="" src="https://www.youtube-nocookie.com/embed/FojhDef2NW4" frameborder="0" allowfullscreen></iframe>"I think you can get very far on a technical level. The problem is that a human body is more complex than just one cell." ... "At some point we still need clinical tests on animals and humans before we use it for real treatment. But we will likely be able to remove 99 % of animal tests in the future."

Erik Lindahl, Professor of Theoretical and Computational Biophysics at KTH Royal Institute of Technology is telling us about his work.

From the episode "Science for life – mapping the building blocks of the human body". Watch the rest of the talk, and other talks at www.crosstalks.tv

Crosstalks is an academic talkshow produced by KTH Royal Institute of Technology and Stockholm University.]]></description>
	
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	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/18741/a-powerful-yet-simple-gene-set-analysis-tool-for-interpreting-rna-seq-and-ngs-results</guid>
	<pubDate>Thu, 30 Oct 2014 09:19:29 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/18741/a-powerful-yet-simple-gene-set-analysis-tool-for-interpreting-rna-seq-and-ngs-results</link>
	<title><![CDATA[A powerful, yet simple, gene set analysis tool for interpreting RNA-seq and NGS results.]]></title>
	<description><![CDATA[<p>LifeMap Sciences is introducing&nbsp;<a href="http://geneanalytics.genecards.org/">GeneAnalytics</a>, our new gene set analysis tool, which is applicable for NGS results and differentially expressed gene lists from variable sources. GeneAnalytics provides&nbsp;gene associations with tissues &amp; cells, diseases, pathways, GO terms and compounds.</p><p>Our main advantages over other similar tools are:</p><ul>
<li>GeneAnalytics is very simple and intuitive to use.</li>
<li>GeneAnalytics is based on our proprietary databases &ndash;&nbsp;<strong>GeneCards</strong>, MalaCards, PathCards and LifeMap Discovery, each of them integrates information from a very large number of resources.</li>
<li>GeneAnalytics supplies links for extensive background information on each of the matched results.</li>
</ul><p>&nbsp;</p><p>I invite you to try it out for free at&nbsp;geneanalytics.genecards.org, and would be happy to hear your comments and thoughts on how we can improve.</p><p>&nbsp;</p><p>Yours,</p><p>Shani Ben-Ari Fuchs</p><p>LifeMap Sciences Team</p>]]></description>
	<dc:creator>Shani</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/18576/graduate-research-assistantships-university-of-nebraska-lincoln-unl</guid>
  <pubDate>Wed, 22 Oct 2014 10:05:31 -0500</pubDate>
  <link></link>
  <title><![CDATA[Graduate research assistantships @ University of Nebraska-Lincoln (UNL)]]></title>
  <description><![CDATA[
<p>Graduate research assistantships in quantitative genetics are available with Gota Morota in the Department of Animal Science at the University of Nebraska-Lincoln (UNL).</p>

<p>Current projects in the Morota lab include developing kernel-based whole-genome prediction and kernel-based genome-wide association models, polygenic modeling of binary traits, reexamining the results from quantitative genetics analysis in light of functional annotation, and extending kernel methods (such as GBLUP and RKHS) specifically tailored for diverse types of emerging omics data.</p>

<p>In addition, candidates will be expected to leverage opportunities to interact with faculty in animal genetics and biometrics at the UNL in the areas of bioinformatics, breeding, functional genomics, quantitative genetics, and molecular genetics.</p>

<p>Candidates should have a B.S. or M.S. degree in quantitative disciplines with strong background and interest in statistical computing. <br />The starting date is Fall 2015. <br />For more information about research in the Morota lab at the UNL, visit: http://www.morotalab.org</p>

<p>A letter of interest in the position, C.V., and contact information for <br />three references should be emailed to Gota Morota at . <br />Review of applications will begin immediately, and continue until the <br />positions are filled. Informal inquiries are also welcome.</p>

<p>Also, please see: http://animalscience.unl.edu/anscprospectivegraduatestudents</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/35418/karyoploter-plot-whole-genomes-with-arbitrary-data</guid>
	<pubDate>Fri, 02 Feb 2018 03:24:28 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/35418/karyoploter-plot-whole-genomes-with-arbitrary-data</link>
	<title><![CDATA[karyoploteR: plot whole genomes with arbitrary data]]></title>
	<description><![CDATA[<p><span><a href="http://bioconductor.org/packages/karyoploteR">karyoploteR</a></span><span>&nbsp;is an R package to create karyoplots, that is, representations of whole genomes with arbitrary data plotted on them. It is inspired by the R base graphics system and does not depend on other graphics packages. The aim of karyoploteR is to offer the user an easy way to plot data along the genome to get broad genome-wide view to facilitate the identification of genome wide relations and distributions.</span></p><p>Address of the bookmark: <a href="https://bernatgel.github.io/karyoploter_tutorial/" rel="nofollow">https://bernatgel.github.io/karyoploter_tutorial/</a></p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/18820/jrfsrf-at-university-of-calcutta</guid>
  <pubDate>Fri, 31 Oct 2014 08:53:10 -0500</pubDate>
  <link></link>
  <title><![CDATA[JRF/SRF at University of Calcutta]]></title>
  <description><![CDATA[
<p>Applications are invited to appear at a walk-in-interview for one post of Junior Research Fellow in the DBT(DBT Twinning NER) sponsored project entitled “Protein folding kinetics is a selection force on shaping codon usage bias in the high expression genes” in the room of the HOD, Department of Biotechnology and the Coordinator, DR. B. C. Guha Centre for Genetic Engineering and Biotechnology, University College of Science, 35 Ballygunge Circular Road, Kolkata 700019 on the 12th November, 2014 at 3:00 p.m.</p>

<p>Essential qualifications: First class M. Sc. in any branch of life sciences and qualified CSIR-UGC NET/GATE Examination.</p>

<p>Desirable qualifications: Practical experience in biochemical and biophysical studies of proteins</p>

<p>Emoluments: as per DBT norms</p>

<p>The project is tenable for two years, initially for one year.</p>

<p>Age: Below 28 years (relaxable in the case of SC/ST/OBC/women candidates)</p>

<p>Candidates are requested to bring two sets of complete applications on plain paper furnishing bio-data and copies of attested certificates along with originals (for verification) on the date of interview.</p>

<p>No TA/DA is admissible for candidates appearing at the interview.</p>

<p>Dr. Rajat Banerjee<br />Assistant Professor<br />Department of Biotechnology and<br />Dr. B. C. Guha Centre for Genetic Engineering and Biotechnology<br />University College of Science<br />35, Ballygunge Circular Road<br />Kolkata 700019</p>

<p>Advertisement: www.caluniv.ac.in/news/jrf_biotech_2.pdf</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/32946/grass-a-generic-algorithm-for-scaffolding-next-generation-sequencing-assemblies</guid>
	<pubDate>Tue, 23 May 2017 05:20:32 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/32946/grass-a-generic-algorithm-for-scaffolding-next-generation-sequencing-assemblies</link>
	<title><![CDATA[GRASS: a generic algorithm for scaffolding next-generation sequencing assemblies.]]></title>
	<description><![CDATA[<p><span>GRASS (GeneRic ASsembly Scaffolder)-a novel algorithm for scaffolding second-generation sequencing assemblies capable of using diverse information sources. GRASS offers a mixed-integer programming formulation of the contig scaffolding problem, which combines contig order, distance and orientation in a single optimization objective. The resulting optimization problem is solved using an expectation-maximization procedure and an unconstrained binary quadratic programming approximation of the original problem. We compared GRASS with existing HTS scaffolders using Illumina paired reads of three bacterial genomes. Our algorithm constructs a comparable number of scaffolds, but makes fewer errors. This result is further improved when additional data, in the form of related genome sequences, are used.</span></p><p>Address of the bookmark: <a href="https://github.com/AlexeyG/GRASS" rel="nofollow">https://github.com/AlexeyG/GRASS</a></p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
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