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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/29008?offset=390</link>
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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/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/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/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/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/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/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/19085/jrf-in-bioinformatics-pondicherry-university</guid>
  <pubDate>Sat, 08 Nov 2014 14:34:48 -0600</pubDate>
  <link></link>
  <title><![CDATA[JRF in Bioinformatics @ Pondicherry University]]></title>
  <description><![CDATA[
<p>Eager to get JRF job in Puducherry? Pondicherry University, School of Life Sciences, Centre for Bioinformatics has issued notification to fill the vacancy of JRF for DST sponsored research project entitled "Design and discovery of aurora kinase inhibitors as anti cancer drugs; application of computer aided drug design". It is good chance to get job with Pondicherry University and secure your future. Learn eligibility criteria and apply on or before 21.11.2014.</p>

<p>Required Skills:	no special skills required for this job post<br />Required Experience:	<br />Experience in computer aided drug design and or biochemical testing of natural or synthetic compounds is desired<br />Required Education:	<br />M.Sc. / M.Tech.</p>

<p>Required Job Profile:<br />Candidate must possess M.Sc. in bioinformatics or computational biology or biotechnology or any branch of life sciences or pharmacology or chemical sciences or M.Tech. in any branch of life sciences with at least fifty five percent marks with NET or GATE.</p>

<p>Desired Job Profile:<br />Candidate having experience in computer aided drug design and or biochemical testing of natural or synthetic compounds.</p>

<p>How to apply:<br />Eligible and interested candidates should need to appear for walk-in interview on 21.11.2014 at 1700 hrs at the above mentioned address.</p>

<p>Contact<br />Pondicherry University<br />Dr. S. Mohane Coumar, Assistant Professor &amp; Project Investigator, Centre for Bioinformatics, Pondicherry University, Puducherry 605 014<br />Email:registrar@pondiuni.edu.in<br />Phone:	0413-2655175</p>

<p>More at http://www.pondiuni.edu.in/sites/default/files/JRF-bioinfor-041114.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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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/19091/phd-opportunity-aicadd-fellowship-mhrd-govt-of-india-of-university-of-kerala</guid>
  <pubDate>Sat, 08 Nov 2014 15:16:24 -0600</pubDate>
  <link></link>
  <title><![CDATA[PhD opportunity / AiCADD fellowship (MHRD, Govt. of India) of University of Kerala.]]></title>
  <description><![CDATA[
<p>No. DCB/DBT-BIF/229 /14-15                                                                                     07-11-2014</p>

<p>Applications are invited for the AiCADD fellowship (MHRD, Govt. of India) of University of Kerala.</p>

<p>The terms and conditions of the fellowship is given below:</p>

<p>Ø The AiCADD PhD Fellowship scheme will be available for the students registered for full-time research      or   intending to register and pursue full time research at SIUCEB in frontier areas of bioinformatics,    computational biology, systems biology and closely allied areas with focus on Ayur-Informatics. </p>

<p>  Ø  The fellowships will be widely announced and open to students irrespective of geographical consideration.</p>

<p>  Ø  Candidates availing of this fellowship shall not be in receipt of any other fellowships concurrently.</p>

<p>  Ø  Researchers will be selected on the basis of research aptitude test and personal interview.</p>

<p>  Ø  Each selected student will be eligible for a monthly fellowship of Rs. 10,000/- for the 1st and 2nd year and Rs. 12,000/- for the 3rd year.</p>

<p>  Ø  Candidates must register for PhD within one year of joining, failing which the fellowship will have to be    remitted back.</p>

<p>  Ø  Candidates receiving the fellowship shall submit bi-annual reports of progress and the continuation of the fellowship will be based on the evaluation of the same.</p>

<p>  Ø  Candidates are also required to take up academic duties including teaching upto a maximum of 6 hours     per week, as directed by AiCADD Principal Investigator.</p>

<p> Interested candidates may please forward their application along with resume on or before 15th November 2014 in the following address. Principal Investigator, AiCADD Centre, Dept. of Computational Biology and Bioinformatics, University of Kerala, Thiruvananthapuram - 695581.</p>

<p>More at https://sites.google.com/site/centreforbioinformatics/announcements</p>
]]></description>
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