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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/30976?offset=600</link>
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	<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>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/videolist/watch/11354/genomics-and-personalized-medicine</guid>
	<pubDate>Sun, 01 Jun 2014 23:38:42 -0500</pubDate>
	<link>https://bioinformaticsonline.com/videolist/watch/11354/genomics-and-personalized-medicine</link>
	<title><![CDATA[Genomics and Personalized Medicine]]></title>
	<description><![CDATA[<iframe width="" height="" src="https://www.youtube-nocookie.com/embed/pgHAXCMMcro" frameborder="0" allowfullscreen></iframe>(October 20, 2009) Michael Snyder, Professor of Genetics and Chair of the Department of Genetics at Stanford, discusses advances in gene sequencing, the impact of genomics on medicine, the potential for personalized medicine. and efforts at Stanford to further study these issues.

Stanford Mini Med School is a series arranged and directed by Stanford's School of Medicine, and presented by the Stanford Continuing Studies program. Featuring more than thirty distinguished, faculty, scientists and physicians from Stanford's medical school, the series offers students a dynamic introduction to the world of human biology, health and disease, and the groundbreaking changes taking place in medical research and health care.

Stanford University
http://www.stanford.edu

Stanford University School of Medicine
http://med.stanford.edu

Stanford Continuing Studies
http://continuingstudies.stanford.edu

Stanford University Channel on YouTube:
http://www.youtube.com/stanford]]></description>
	
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36109/sankeynetwork-with-networkd3</guid>
	<pubDate>Fri, 06 Apr 2018 12:07:55 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36109/sankeynetwork-with-networkd3</link>
	<title><![CDATA[sankeyNetwork with networkD3]]></title>
	<description><![CDATA[<p><span>You can also create&nbsp;</span><a href="http://en.wikipedia.org/wiki/Sankey_diagram">Sankey diagrams</a><span>&nbsp;with&nbsp;</span><code>sankeyNetwork</code><span>. Here is an example using downloaded JSON data:</span></p>
<p><span>https://en.wikipedia.org/wiki/Sankey_diagram</span></p><p>Address of the bookmark: <a href="https://christophergandrud.github.io/networkD3/#sankey" rel="nofollow">https://christophergandrud.github.io/networkD3/#sankey</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/11434/adhoc-bioinformatics-faculty-position-nit</guid>
  <pubDate>Tue, 03 Jun 2014 16:19:52 -0500</pubDate>
  <link></link>
  <title><![CDATA[Adhoc Bioinformatics Faculty Position @ NIT]]></title>
  <description><![CDATA[
<p>NATIONAL INSTITUTE OF TECHNOLOGY, DEPARTMENT OF BIOTECHNOLOGY, WARANGAL – 506 021, Andhra Pradesh</p>

<p>No.NITW/BT/2014/adhoc</p>

<p>APPLICATIONS ARE INVITED FOR THE APPOINTMENT OF ADHOC FACULTY ON CONTRACT BASIS IN THE DEAPARTMENT OF BIOTECHNOLOGY</p>

<p>Period of Contract: Initially the appointment is for one semester i.e., from July 2014 up to December 2014 only.</p>

<p>Essential Qualifications:</p>

<p>i) B. Tech or equivalent in Biotechnology/ Industrial Biotechnology/ Biochemical Engineering / Chemical Engg. Or M. Sc in Microbiology/ Botany/ Zoology/ Biochemistry/Biotechnology and ii) M. Tech or equivalent in Biotechnology/Industrial Biotechnology/Bioinformatics</p>

<p>Or</p>

<p>Integrated M. Tech in Biotechnology/Industrial Biotechnology/ Bioinformatics</p>

<p>Candidates must possess First class (60% aggregate marks or 6.5 CGPA) at B. Tech/ M. Sc and M. Tech.</p>

<p>Desirable: Ph. D Pay Package: All selected candidates shall be eligible for a consolidated pay of Rs.30, 000/- per month. Candidates with Ph. D shall be eligible for an additional amount of Rs.5, 000/- per month.</p>

<p>How to apply : Applications on plain paper with attested photocopies of certificate and bio data along with justification for eligibility should reach to the Head, Department of Biotechnology, National Institute of Technology, Warangal AP 506004 in the form of soft or hard copy on or before 21st June 2014 email : biotech_hod@nitw.ac.in</p>

<p>Intimation: No separate call letters will be sent to the candidates. All the eligible candidates will be notified in the institute web site on 23rd June 2014. All the eligible candidates are requested to report for the interview to the Head, Department of Biotechnology at 9:00 AM on 27th June 2014</p>

<p>Joining: Selected candidates will be informed and they are expected to join immediately.</p>

<p>Advertisement:</p>

<p>http://www.nitw.ac.in/nitw/announcements/2014/Bio-Adhoc%20Advt.%20May-2014.pdf</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38004/vcfr-a-package-to-manipulate-and-visualize-vcf-data-in-r</guid>
	<pubDate>Thu, 25 Oct 2018 09:05:59 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38004/vcfr-a-package-to-manipulate-and-visualize-vcf-data-in-r</link>
	<title><![CDATA[vcfR:  a package to manipulate and visualize VCF data in R]]></title>
	<description><![CDATA[<p><span>VcfR is an R package intended to allow easy manipulation and visualization of variant call format (VCF) data. Functions are provided to rapidly read from and write to VCF files. Once VCF data is read into R a parser function extracts matrices from the VCF data for use with typical R functions. This information can then be used for quality control or other purposes. Additional functions provide visualization of genomic data. Once processing is complete data may be written to a VCF file or converted into other popular R objects (e.g., genlight, DNAbin). VcfR provides a link between VCF data and the R environment connecting familiar software with genomic data.</span></p><p>Address of the bookmark: <a href="https://github.com/knausb/vcfR" rel="nofollow">https://github.com/knausb/vcfR</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/11656/faculty-post-at-zhejiang-university</guid>
  <pubDate>Tue, 10 Jun 2014 03:40:40 -0500</pubDate>
  <link></link>
  <title><![CDATA[Faculty post at Zhejiang University]]></title>
  <description><![CDATA[
<p>Zhejiang University (ZJU) is seeking faculty candidates for its newly launched, highly competitive and well funded “Hundred Talents Program”. This search covers all colleges and departments at ZJU. Applicants, expected to be about 35 years old, should hold PhD degree, and postdoctoral experiences are preferred for applicants in most fields. Applicants should have demonstrated commitment to excellence in teaching and research at a level comparable to the academic achievement of assistant professor or associate professor in world-renowned universities. Successful candidates must work full-time and are expected to establish internationally competitive and independent research program in cutting-edge areas of the relevant field at ZJU.</p>

<p>As one of the leading research-intensive universities in China, ZJU is located in the beautiful city of Hangzhou. Successful candidates will be employed as Principal Investigators and are qualified to supervise doctoral students. ZJU will offer an internationally competitive salary and the opportunity to purchase university's apartment at a price much lower than the market price, and will provide office and laboratory spaces as well as internationally competitive research startup packages.</p>

<p>Qualified applicants are strongly encouraged to submit their applications electronically to tr@zju.edu.cn. Applicants should include the following materials in pdf format: a comprehensive CV, a statement of research and teaching plan, and a list of 3 to 5 references with detailed contact information.</p>

<p>Contact：Talents Office, ZJU</p>

<p>Tel：+86-571-88981345, +86-571-88981390</p>

<p>Fax：+86-571-88981976</p>

<p>E-mail:tr@zju.edu.cn</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41487/tinycov-standalone-command-line-utility-written-in-python-to-plot-coverage-from-a-bam-file</guid>
	<pubDate>Mon, 23 Mar 2020 06:22:08 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41487/tinycov-standalone-command-line-utility-written-in-python-to-plot-coverage-from-a-bam-file</link>
	<title><![CDATA[tinycov: standalone command line utility written in python to plot coverage from a BAM file]]></title>
	<description><![CDATA[<p>Tinycov is a small standalone command line utility written in python to plot the coverage of a BAM file quickly. This software was inspired by&nbsp;<a href="https://github.com/matted/genome_coverage_plotter">Matt Edwards' genome coverage plotter</a>.</p>
<p>To install the stable version:&nbsp;<code>pip3 install --user tinycov</code></p>
<p>To install the development version:</p>
<pre><code>git clone https://github.com/cmdoret/tinycov.git
cd tinycov
pip install .</code></pre><p>Address of the bookmark: <a href="https://github.com/cmdoret/tinycov" rel="nofollow">https://github.com/cmdoret/tinycov</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/11592/xampp-starting-apache-fail-ubuntu</guid>
	<pubDate>Sat, 07 Jun 2014 05:52:35 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/11592/xampp-starting-apache-fail-ubuntu</link>
	<title><![CDATA[XAMPP: Starting Apache fail Ubuntu]]></title>
	<description><![CDATA[<p>Once you install XAMMP on linux, the most common problem you face is Apache failure. To fix the issues please use following command to first stop and then again start it.</p><p>sudo /etc/init.d/apache2 stop</p><p>sudo /etc/init.d/mysql stop</p><p>sudo /etc/init.d/proftpd stop</p><p>sudo /opt/lampp/lampp start</p><p>&nbsp;</p><p><strong>PhpMyAdmin &ldquo;Wrong permissions on configuration file, should not be world writable!&rdquo;</strong></p><p>Once the Xammp is installed, it might be possible to set up the configuration file in writable mode. Try the following steps:</p><p>Just chmod 0755 the file</p><pre>sudo chmod 0755 config.inc.php</pre>]]></description>
	<dc:creator>Ram Yash Pal</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/videolist/watch/12288/genomic-medicine-bruce-korf-2014</guid>
	<pubDate>Tue, 24 Jun 2014 07:58:44 -0500</pubDate>
	<link>https://bioinformaticsonline.com/videolist/watch/12288/genomic-medicine-bruce-korf-2014</link>
	<title><![CDATA[Genomic Medicine - Bruce Korf (2014)]]></title>
	<description><![CDATA[<iframe width="" height="" src="https://www.youtube-nocookie.com/embed/FYldIrsXHKw" frameborder="0" allowfullscreen></iframe>May 21, 2014 - Current Topics in Genome Analysis 2014
A lecture series covering contemporary areas in genomics and bioinformatics. More: http://www.genome.gov/COURSE2014]]></description>
	
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42713/gggenomes-a-grammar-of-graphics-for-comparative-genomics</guid>
	<pubDate>Mon, 01 Feb 2021 14:47:32 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42713/gggenomes-a-grammar-of-graphics-for-comparative-genomics</link>
	<title><![CDATA[gggenomes: A grammar of graphics for comparative genomics]]></title>
	<description><![CDATA[<p><span>gggenomes is a versatile graphics package for comparative genomics. It extends the popular R visualization package</span><a href="https://ggplot2.tidyverse.org/">ggplot2</a><span>&nbsp;by adding dedicated plot functions for genes, syntenic regions, etc. and verbs to manipulate the plot to, for example, quickly zoom in into gene neighborhoods.</span></p><p>Address of the bookmark: <a href="https://github.com/thackl/gggenomes" rel="nofollow">https://github.com/thackl/gggenomes</a></p>]]></description>
	<dc:creator>Surabhi Chaudhary</dc:creator>
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