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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/28903?offset=920</link>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/19086/postdoctoral-fellowship-in-bioinformatics</guid>
  <pubDate>Sat, 08 Nov 2014 14:41:14 -0600</pubDate>
  <link></link>
  <title><![CDATA[Postdoctoral fellowship in Bioinformatics]]></title>
  <description><![CDATA[
<p>A two-year post-doctoral position is available in the Biocomputing group of the Sapienza University led by Anna Tramontano to work on either genomics research or structural bioinformatics, focusing on the study of relevant biomedical problems.<br />The ideal candidate should be motivated and talented, hold a PhD degree, have good programming skills, a grasp of statistical methods and an understanding of biology.<br />Experience in the development of computational biology methods would be an added value.</p>

<p>Good communication skills and fluency in spoken and written English are required.<br />Please apply sending a curriculum vitae, the names of at least two referees and a letter of motivation describing past experience and future goals to anna.tramontano@uniroma1.it with subject: “Application for post-doctoral position November 2014 YOUR LAST NAME”</p>

<p>Deadline: No later than November 28th, 2014.<br />Duration: 2 years</p>

<p>Salary on grant: Commeasured to the experience of the candidate<br />Contact Person (Referent): Anna Tramontano<br />Ref. E-Mail: anna.tramontano@uniroma1.it<br />Group Web Page: http:/www.biocomputing.it</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43799/kast</guid>
	<pubDate>Wed, 23 Feb 2022 08:28:36 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43799/kast</link>
	<title><![CDATA[KAST]]></title>
	<description><![CDATA[<p><span>Perform Alignment-free k-tuple frequency comparisons from sequences. This can be in the form of two input files (e.g. a reference and a query) or a single file for pairwise comparisons to be made.</span></p><p>Address of the bookmark: <a href="https://github.com/martinjvickers/KAST" rel="nofollow">https://github.com/martinjvickers/KAST</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
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<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/19137/centre-for-systems-biology-bioinformatics-panjab-university-vacancy-of-research-fellow</guid>
  <pubDate>Wed, 12 Nov 2014 06:18:54 -0600</pubDate>
  <link></link>
  <title><![CDATA[Centre for Systems Biology &amp; Bioinformatics, Panjab University vacancy of Research Fellow]]></title>
  <description><![CDATA[
<p>Applications are invited along with complete bio-data and attested copies of certificates of qualifications, experience etc. for the one post of <br />Research Fellow and one post of Program Assistant under PURSE Grant of the University in Centre for Systems Biology &amp; Bioinformatics, UIEAST, Panjab University, Chandigarh which is tenable till the period of the project</p>

<p>Essential Qualification<br />For Research Fellow:-<br />M.Sc. in Systems Biology and Bioinformatics / Life<br />Sciences with minimum 55% marks.<br />Preference will be given to NET/GATE/ICMR qualified candidates without fellowship however, candidates who have cleared the Panjab University Ph.D. entrance test in Systems Biology &amp; Bioinformatics will also be eligible. </p>

<p>Applications should be reach on or before 19-11-2014 in the office of the undersigned. Interview will be held on 21-11-2014 in the office of the Coordinator, Centre for Systems Biology &amp; Bioinformatics, South Campus, Block-3, Sector-25, Panjab University, Chandigarh. No TA/DA will be paid. </p>

<p>more at http://jobs.puchd.ac.in/includes/jobs/2014/20141110143634-Advertisement.pdf</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44223/ale-assembly-likelihood-estimator</guid>
	<pubDate>Wed, 08 Mar 2023 01:39:33 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44223/ale-assembly-likelihood-estimator</link>
	<title><![CDATA[ALE: Assembly Likelihood Estimator]]></title>
	<description><![CDATA[<p>Just import the assembly, bam and ALE scores. You can convert the .ale file to a set of .wig files with ale2wiggle.py and IGV can read those directly.&nbsp; Depending on your genome size you may want to convert the .wig files to the BigWig format.</p><p>Address of the bookmark: <a href="https://github.com/sc932/ALE" rel="nofollow">https://github.com/sc932/ALE</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
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<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/19248/bioinformatics-jrfrasrf-position-at-institute-of-cytology-and-preventive-oncology-icpo</guid>
  <pubDate>Wed, 19 Nov 2014 20:16:32 -0600</pubDate>
  <link></link>
  <title><![CDATA[Bioinformatics JRF/RA/SRF position at Institute of Cytology and Preventive Oncology (ICPO)]]></title>
  <description><![CDATA[
<p>Institute of Cytology and Preventive Oncology (ICPO) I-7, Sector-39, Noida-201301</p>

<p>Candidates having the below mentioned qualifications may appear for walk in interview at ICPO on 2nd December 2014 between 10.00 AM and 12:00 PM under the below time bound projects under Dr. Subhash M. Agarwal, Scientist C. The post is purely temporary and co-terminus with the project.</p>

<p>Research Assistant (One)<br />25650/- consolidated<br />Discovery of EGFR secondary mutant inhibitors using structure based screening approach (ICMR)<br />Duration: 7 months</p>

<p>Essential: M.Sc./ M.Tech in Bioinformatics or any other related subject with good academic record.</p>

<p>Desirable: Experience in scripting and molecular docking.<br />	<br />Below 30 years</p>

<p>Junior Research Fellow (One)</p>

<p>16,000 + 30% HRA = Rs. 20800/-</p>

<p>Identification of novel inhibitors targeting EGFR using an integrated ligand and structure based approach (DBT)</p>

<p>Duration: 9 months</p>

<p>Essential: M.Sc./ M.Tech in Bioinformatics or any other related subject with good academic record. Candidates with CSIR-UGC / ICMR, NET qualification will be preferred</p>

<p>Desirable: Experience in scripting, QSAR and molecular docking.<br />	<br />Below 28 years</p>

<p>Interested eligible candidates may send their applications with Bio-data by email at (smagarwal@gmail.com) or by post addressed to Dr. Subhash M Agarwal, Scientist C, Institute of Cytology and Preventive Oncology (ICPO) I-7, Sector-39, Noida-201301 so as to reach latest by 1st December, 2014. The candidates may appear for interview at ICPO along with 3 copies of CV, photo and relevant certificates of qualifications in original and reprints of publications at the time of interview. It should be noted that No TA/DA will be paid for the walk in Interview.</p>

<p>Advertisement: www.icpo.org.in/advt-walk-in-interview.docx</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/44371/steps-to-find-all-the-repeats-in-the-genome</guid>
	<pubDate>Thu, 31 Aug 2023 02:43:28 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/44371/steps-to-find-all-the-repeats-in-the-genome</link>
	<title><![CDATA[Steps to find all the repeats in the genome !]]></title>
	<description><![CDATA[<div><p>To find repeats in a genome from 2 to 9 length using a Perl script, you can use the RepeatMasker tool with the "--length" option<a href="https://mobilednajournal.biomedcentral.com/articles/10.1186/1759-8753-5-13" target="_blank">[0]</a>. Here's a step-by-step guide:</p></div><div><ol>
<li>Install RepeatMasker: First, you need to install RepeatMasker on your system. You can download it from the RepeatMasker website<a href="https://mobilednajournal.biomedcentral.com/articles/10.1186/1759-8753-5-13" target="_blank">[0]</a>.</li>
</ol></div><div><ol>
<li>Prepare the genome sequence: Make sure you have the genome sequence in a FASTA file format. Let's assume the file is named "genome.fasta".</li>
</ol><blockquote><p>./RepeatMasker -pa &lt;number_of_processors&gt; -nolow -norna -no_is -div &lt;divergence_value&gt; -lib RepeatMaskerLib.embl -gff -xsmall -small -poly -species &lt;species_name&gt; -dir &lt;output_directory&gt; -length &lt;min_length&gt;-&lt;max_length&gt; genome.fasta</p></blockquote><div><p>Replace the following placeholders with appropriate values:</p><ul>
<li><code>&lt;number_of_processors&gt;</code>: The number of processors/threads you want to use for parallel processing.</li>
<li><code>&lt;divergence_value&gt;</code>: The divergence value for the species you are analyzing. You can find divergence values for different species in the RepeatMasker documentation<a href="https://mobilednajournal.biomedcentral.com/articles/10.1186/1759-8753-5-13" target="_blank">[0]</a>.</li>
<li><code>&lt;species_name&gt;</code>: The name of the species you are analyzing.</li>
<li><code>&lt;output_directory&gt;</code>: The directory where you want the output files to be saved.</li>
<li><code>&lt;min_length&gt;</code>&nbsp;and&nbsp;<code>&lt;max_length&gt;</code>: The minimum and maximum lengths of the repeats you want to find (in this case, 2 and 9).</li>
</ul></div><div><ol>
<li>Analyze the output: RepeatMasker will generate several output files, including a .out file. You can parse this file to extract the information you need. There is a Perl tool called "one_code_to_find_them_all.pl" that can help you parse RepeatMasker output files<a href="https://mobilednajournal.biomedcentral.com/articles/10.1186/1759-8753-5-13" target="_blank">[0]</a>. You can download it from the source provided.</li>
</ol></div><div><ol>
<li>Use the provided Perl script: Once you have the "one_code_to_find_them_all.pl" script, you can run it to conveniently parse the RepeatMasker output files. Here's an example of how to use it:</li>
</ol><blockquote><p>perl one_code_to_find_them_all.pl --rm &lt;RepeatMasker_out_file&gt; --length &lt;length_file&gt;</p></blockquote></div><p>&nbsp;</p></div><div><div><p>Replace&nbsp;<code>&lt;RepeatMasker_out_file&gt;</code>&nbsp;with the path to your RepeatMasker .out file, and&nbsp;<code>&lt;length_file&gt;</code>&nbsp;with the path to a file containing the lengths of the reference elements.</p></div><div><p>This script will generate several output files, including .log.txt and .copynumber.csv, which contain quantitative information about the identified repeat elements.</p></div><div><p>Remember to adjust the parameters and options according to your specific needs and the characteristics of your genome.</p></div></div>]]></description>
	<dc:creator>Neel</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/19556/genome-origami</guid>
	<pubDate>Fri, 12 Dec 2014 22:48:17 -0600</pubDate>
	<link>https://bioinformaticsonline.com/news/view/19556/genome-origami</link>
	<title><![CDATA[Genome Origami]]></title>
	<description><![CDATA[<p>There are several interesting factoid about our genomes, one of them is their folding. If we stretched out the DNA in a single cell, which is only a few millionths of an inch wide, it would span more than six feet. In other word, the size of six feet DNA fold themself to fit in a few millionths of an inch wide space. These DNA folding is a dynamic process that changes over time (!!). Researchers around the world have been trying to understand how DNA folds itself up so efficiently, and a recent post on the NIH Director&rsquo;s Blog highlights new research illustrating how the human genome folds inside the cell&rsquo;s nucleus, as well as how DNA folding affects gene regulation. The research team created this delightful video that demonstrates the principles involved using origami art.</p><p>http://bioinformaticsonline.com/videolist/watch/19555/a-3d-map-of-the-human-genome<br /><br />Researchers have been working to determine how cells regulate gene expression for nearly as long as we&rsquo;ve known about DNA. How, for example, do nerve cells know to turn off only nerve cell genes and turn off bone cell genes? DNA folding loops are part of the answer. This research team, which published their findings in a paper in Cell http://www.cell.com/cell/abstract/S0092-8674%2814%2901497-4 , found that the number of loops is much lower than expected. There are only 10,000 loops instead of the predicted millions, and they form on/off switches in DNA.<br /><br /></p><p>More at http://www.eurekalert.org/pub_releases/2014-12/ru-3mr121114.php</p><p>Reference http://www.cell.com/cell/abstract/S0092-8674%2814%2901497-4</p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/44637/tools-to-access-the-quality-of-your-assembled-genome</guid>
	<pubDate>Thu, 08 Aug 2024 23:31:18 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/44637/tools-to-access-the-quality-of-your-assembled-genome</link>
	<title><![CDATA[Tools to access the quality of your assembled genome !]]></title>
	<description><![CDATA[<ul dir="auto">
<li><a href="https://github.com/linsalrob/fasta_validator">FASTA VALIDATOR</a>&nbsp;+&nbsp;<a href="https://github.com/shenwei356/seqkit">SEQKIT RMDUP</a>: FASTA validation</li>
<li><a href="https://genometools.org/tools/gt_gff3validator.html">GENOMETOOLS GT GFF3VALIDATOR</a>: GFF3 validation</li>
<li><a href="https://github.com/PlantandFoodResearch/assemblathon2-analysis/blob/a93cba25d847434f7eadc04e63b58c567c46a56d/assemblathon_stats.pl">ASSEMBLATHON STATS</a>: Assembly statistics</li>
<li><a href="https://genometools.org/tools/gt_stat.html">GENOMETOOLS GT STAT</a>: Annotation statistics</li>
<li><a href="https://github.com/ncbi/fcs">NCBI FCS ADAPTOR</a>: Adaptor contamination pass/fail</li>
<li><a href="https://github.com/ncbi/fcs">NCBI FCS GX</a>: Foreign organism contamination pass/fail</li>
<li><a href="https://gitlab.com/ezlab/busco">BUSCO</a>: Gene-space completeness estimation</li>
<li><a href="https://github.com/tolkit/telomeric-identifier">TIDK</a>: Telomere repeat identification</li>
<li><a href="https://github.com/oushujun/LTR_retriever/blob/master/LAI">LAI</a>: Continuity of repetitive sequences</li>
<li><a href="https://github.com/DerrickWood/kraken2">KRAKEN2</a>: Taxonomy classification</li>
<li><a href="https://github.com/igvteam/juicebox.js">HIC CONTACT MAP</a>: Alignment and visualisation of HiC data</li>
<li><a href="https://github.com/mummer4/mummer">MUMMER</a>&nbsp;&rarr;&nbsp;<a href="http://circos.ca/documentation/">CIRCOS</a>&nbsp;+&nbsp;<a href="https://plotly.com/">DOTPLOT</a>&nbsp;&amp;&nbsp;<a href="https://github.com/lh3/minimap2">MINIMAP2</a>&nbsp;&rarr;&nbsp;<a href="https://github.com/schneebergerlab/plotsr">PLOTSR</a>: Synteny analysis</li>
<li><a href="https://github.com/marbl/merqury">MERQURY</a>: K-mer completeness, consensus quality and phasing assessment</li>
</ul>]]></description>
	<dc:creator>LEGE</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/19545/walk-%E2%80%93-in-%E2%80%93-interview-agricultural-knowledge-management-unit-indian-agricultural-research-institute-new-delhi-110012</guid>
  <pubDate>Fri, 12 Dec 2014 21:33:02 -0600</pubDate>
  <link></link>
  <title><![CDATA[WALK – IN – INTERVIEW @ Agricultural Knowledge Management Unit Indian Agricultural Research Institute, New Delhi-110012]]></title>
  <description><![CDATA[
<p>Walk-in-interview for the following temporary positions will be conducted on 20th December 2014 (between 10:00 AM to 01:00 PM) at Agricultural Knowledge Management Unit, A0 block (Ground Floor), LBS Building, Indian Agricultural Research Institute, New Delhi-110012:</p>

<p>1 Dr. A.K.Mishra Coordinator &amp; PI (BTISnet)</p>

<p>Traineeship (two) for one year</p>

<p>Rs. 5000/- (consolidated)</p>

<p>M.Sc. (Bioinformatics) with 60 % marks from a recognized University</p>

<p>20-12-2014 (10:00 AM -11:00 AM)</p>

<p>Studentship (four) for one year</p>

<p>Rs. 2500/- (consolidated)</p>

<p>Final year M.Sc./ M.Tech (Bioinformatics) Students from a recognized University</p>

<p>20-12-2014 (11:00 AM- 1:00 PM)</p>

<p>The positions are purely temporary and co-terminus with the DBT Programme. Eligible candidates are requested to submit the application form in the prescribed format along with original certificates/ documents (Degree, Marks sheets, Work experience, if any) at the time of interview. No TA/DA will be paid. Maximum age limit is 28 years for all positions. Age relaxation of 5 yrs for SC/ST and woman candidates and 3 years for OBC candidates will be given. Canvassing in any form invites disqualification.</p>

<p>Advertisement: http://www.iari.res.in/files/BIC-08122014-20141208-172344.pdf</p>
]]></description>
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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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