<?xml version='1.0'?><rss version="2.0" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:georss="http://www.georss.org/georss" xmlns:atom="http://www.w3.org/2005/Atom" >
<channel>
	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/36880?offset=1280</link>
	<atom:link href="https://bioinformaticsonline.com/related/36880?offset=1280" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
	<item>
	<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>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/22235/project-fellow-bioinformatics-at-central-drug-research-institute</guid>
  <pubDate>Mon, 27 Apr 2015 20:15:45 -0500</pubDate>
  <link></link>
  <title><![CDATA[Project Fellow Bioinformatics at Central Drug Research Institute]]></title>
  <description><![CDATA[
<p>Project Fellow (Bioinformatics)<br />Central Drug Research Institute<br />Address: Chattar Manzil, M.G.Road, Kaisarbagh<br />Postal Code: 226001<br />City: Lucknow<br />State: Uttar Pradesh<br />Pay Scale: Rs.16,000/- (fixed) p.m.<br />Educational Requirements: M.Sc. in Bioinformatics with 55% marks for Gen. &amp; OBC and 50% marks for SC/ST candidates, Physically and Visually handicapped candidates<br />Experience Requirements: Experience in computer-assisted scientific research in the area of Drug Design including Bio- molecular modeling and simulation studies, Virtual screening, pharmacophore perception, QSAR etc. Familiarity with Linux/Unixbased computer systems and required to participate and contribute to the development and application of computational models for the design and discovery of novel molecules as inhibitors or chemical probes<br />Details will be available at: http://cdriindia.org/uploaded/advt_no01-2015.pdf</p>

<p>How To Apply: Eligible candidates required to report for the Interview at 9:00 A.M. sharp on 11-05-2015 (For Position Code No. 001 to 009) and 12-05-2015 (For Position Code No. 010 to 016). Candidates reporting after 10:00 A.M will not be allowed to attend the interview. Eligible candidates may appear before the Selection Committee for interview on the date and time mentioned above at CDRI, B.S. 10/1, Sector 10, Jankipuram Extension, Sitapur Road, Lucknow-226031. Eligible candidates must bring with them duly filled up application form (which can be downloaded from our website www.cdriindia.org), along with Original certificates as well as attested copies of certificates of examinations starting from matriculation, date of birth, caste certificate (in case of SC/ST/OBC) experience certificate, publication, if any and recent passport size photograph etc. Original documents are essential for verification of the particulars quoted by the candidate in the application form and candidate failed to produce original documents at the time of verification, shall not be allowed to attend the interview. Any request for relaxation in this regard shall not be entertained.<br />Detail of Interview: 11-05-2015<br />Age Limit: 28 Years</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/4038/java-and-biojava-tutorial-links</guid>
	<pubDate>Wed, 28 Aug 2013 06:33:39 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/4038/java-and-biojava-tutorial-links</link>
	<title><![CDATA[Java and BioJava Tutorial links]]></title>
	<description><![CDATA[<p>BioJava provides analytical and statistical routines, parsers for common file formats and allows the manipulation of sequences and 3D structures. The goal of this bookmark is to provide useful links for bioinformatician.</p>
<p>Please add more useful Java and BioJava links here ...</p><p>Address of the bookmark: <a href="http://biojava.org/wiki/BioJava:CookBook3.0" rel="nofollow">http://biojava.org/wiki/BioJava:CookBook3.0</a></p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/22269/school-of-life-sciences-jawaharlal-nehru-university-vacancy-of-jrf-srf-ra-in-csir-funded-project</guid>
  <pubDate>Wed, 29 Apr 2015 21:26:19 -0500</pubDate>
  <link></link>
  <title><![CDATA[School of Life Sciences, Jawaharlal Nehru University vacancy of JRF / SRF / RA in CSIR funded Project]]></title>
  <description><![CDATA[
<p>School of Life Sciences, Jawaharlal Nehru University has issued notification dated 27.04.2015 to fill the vacancy of JRF / SRF / RA in CSIR funded Projec entitled "Structural and functional characterization of serine biosynthetic pathway enzymes from entamoeba histolytica". It is good chance to get job with IITKGP and brighten your future. Learn eligibility criteria and apply on or before 08.05.2015.</p>

<p>Employer:	Jawaharlal Nehru University<br />Address:	Dr. S. Gourinath, Principal Investigator, School Of Life Sciences, Jawaharlal Nehru University, New Delhi-110067<br />Email:	not mentioned / provided for this job post<br />URL:	http://www.jnu.ac.in/Career/currentjobs.htm<br />Phone:	011 2674 2575<br />Skills:	not mentioned / required for this job post<br />Experience:	Experience in molecular biology, structural biology and bioinformatics is desired<br />Education:	M.Sc. in any field of life sciences.<br />Job Location:	New Delhi, Delhi, India   (View Jobs in New Delhi,   Jobs in Delhi,   Jobs in India)</p>

<p>Job Description: School of Life Sciences, Jawaharlal Nehru University vacancy of JRF / SRF / RA in CSIR funded Projec</p>

<p>Name of the Post: JRF / SRF / RA</p>

<p>Salary: As per rules</p>

<p>Required Job Profile:</p>

<p>Candidate must possess M.Sc. in any field of life sciences.</p>

<p>Desired Job Profile:</p>

<p>Candidate having NET - CSIR or UGC and experience in molecular biology, structural biology and bioinformatics is desired and experience with publication is preferred.</p>

<p>How to apply:</p>

<p>Eligible and interested candidates should need to apply with complete details to the above mentioned address on or before 08.05.2015.</p>

<p>Refer to http://www.jnu.ac.in/Career/currentjobs.htm</p>
]]></description>
</item>
<item>
	<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>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/22287/research-fellows-at-aimscs-hyderabad</guid>
  <pubDate>Wed, 06 May 2015 06:23:33 -0500</pubDate>
  <link></link>
  <title><![CDATA[Research Fellows at AIMSCS, Hyderabad]]></title>
  <description><![CDATA[
<p>C.R.Rao Advanced Institute of Mathematics, Statistics and Computer Science (AIMSCS) - Hyderabad, Andhra Pradesh<br />Advertisement No.: 5/2015</p>

<p>Research Fellows Systems Biology job vacancy in C.R.Rao Advanced Institute of Mathematics, Statistics and Computer Science (AIMSCS)</p>

<p>JRF : Qualification - M. Sc in Bioinformatics, Systems Biology, M. Sc statistics, or M. Tech in Bioinformatics,</p>

<p>Pay Scale : Rs. 25,000</p>

<p>SRF : Qualification- Qualification prescribed for JRF with 2 years of research experience.</p>

<p>Pay Scale : Rs. 28,000*</p>

<p>No.of Post: 2</p>

<p>Desirable: Candidates should have strong background in Computational biology, bioinformatics, statistics and algorithmic development. In addition to that previous experience of working on Linux, bio-informatics, NGS data analysis and Basic knowledge of biology is desirable. Programming on any one of the programming languages (C, C++, perl, python) and statistical framework (e.g. R, matlab, etc.) is highly desirable.</p>

<p>More at http://www.crraoaimscs.org/jrf_application_form_2015.pdf</p>
]]></description>
</item>
<item>
	<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>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/22388/perl-one-liner-basics</guid>
	<pubDate>Sun, 24 May 2015 09:28:33 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/22388/perl-one-liner-basics</link>
	<title><![CDATA[Perl One liner basics !!]]></title>
	<description><![CDATA[<p>Perl has a ton of command line switches (see perldoc perlrun), but I'm just going to cover the ones you'll commonly need to debug code. The most important switch is -e, for execute (or maybe "engage" :) ). The -e switch takes a quoted string of Perl code and executes it. For example:<br /><br />$ perl -e 'print "Hello, World!\n"'<br />Hello, World!<br /><br />It's important that you use single-quotes to quote the code for -e. This usually means you can't use single-quotes within the one liner code. If you're using Windows cmd.exe or PowerShell, you must use double-quotes instead.<br /><br />I'm always forgetting what Perl's predefined special variables do, and often test them at the command line with a one liner to see what they contain. For instance do you remember what $^O is?<br /><br />$ perl -e 'print "$^O\n"'<br />linux<br /><br />It's the operating system name. With that cleared up, let's see what else we can do. If you're using a relatively new Perl (5.10.0 or higher) you can use the -E switch instead of -e. This turns on some of Perl's newer features, like say, which prints a string and appends a newline to it. This saves typing and makes the code cleaner:<br /><br />$ perl -E 'say "$^O"'<br />linux<br /><br />Pretty handy! say is a nifty feature that you'll use again and again.</p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
</item>
<item>
	<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>
</item>
<item>
	<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>
</item>

</channel>
</rss>