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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/35543?offset=460</link>
	<atom:link href="https://bioinformaticsonline.com/related/35543?offset=460" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44628/uncovar-workflow-for-transparent-and-robust-virus-variant-calling-genome-reconstruction-and-lineage-assignment</guid>
	<pubDate>Mon, 05 Aug 2024 23:01:29 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44628/uncovar-workflow-for-transparent-and-robust-virus-variant-calling-genome-reconstruction-and-lineage-assignment</link>
	<title><![CDATA[UnCoVar: Workflow for Transparent and Robust Virus Variant Calling, Genome Reconstruction and Lineage Assignment]]></title>
	<description><![CDATA[<p>UnCoVar: Workflow for Transparent and Robust Virus Variant Calling, Genome Reconstruction and Lineage Assignment</p>
<ul>
<li>
<p>Using state of the art tools, easily extended for other viruses</p>
</li>
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<p>Tool and database updates for critical components via Conda</p>
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<p>Built using modern design patterns with Conda and Snakemake</p>
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<p>Extensible and easy to customize</p>
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<p>Submission Ready Genomes</p>
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<p>Customizable reporting with comprehensive visualization</p>
</li>
</ul>
<p>https://ikim-essen.github.io/uncovar/</p>
<p>Github&nbsp;https://github.com/IKIM-Essen/uncovar</p>
<p>&nbsp;</p>
<p>&nbsp;</p><p>Address of the bookmark: <a href="https://ikim-essen.github.io/uncovar/" rel="nofollow">https://ikim-essen.github.io/uncovar/</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/44754/early-genome-screening-the-new-health-horoscope</guid>
	<pubDate>Thu, 02 Jan 2025 19:44:36 -0600</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/44754/early-genome-screening-the-new-health-horoscope</link>
	<title><![CDATA[Early Genome Screening: The New Health Horoscope!]]></title>
	<description><![CDATA[<p>In an era where precision medicine is reshaping healthcare, genome screening is emerging as the modern equivalent of a health horoscope. It offers insights into our biological "stars," unraveling predispositions to various conditions and empowering individuals with knowledge to navigate their health journeys proactively. But how reliable is this "horoscope," and how does it impact our lives?</p><h3>Understanding Genome Screening</h3><p>Genome screening involves analyzing an individual's DNA to identify genetic variations that may influence health and disease susceptibility. This can range from simple single-gene tests to comprehensive whole-genome sequencing. By peering into our genetic blueprint, we can uncover risks for conditions like cancer, diabetes, cardiovascular diseases, and even rare genetic disorders.</p><p>The process is straightforward: a saliva or blood sample is collected, and advanced sequencing technologies decipher the genetic code. The results provide a personalized health map, guiding lifestyle modifications, preventive measures, or medical interventions.</p><h3>A Shift from Reactive to Proactive Healthcare</h3><p>Traditional healthcare often focuses on treating diseases after they manifest. Genome screening flips this model on its head, enabling a shift toward prevention and early intervention. For instance:</p><ul>
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<p><strong>Cancer Risk Management</strong>: Individuals with BRCA1 or BRCA2 gene mutations can opt for enhanced screening programs or preventive surgeries to mitigate their risk of breast and ovarian cancers.</p>
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<p><strong>Cardiovascular Health</strong>: Genetic predispositions to conditions like familial hypercholesterolemia can prompt early cholesterol monitoring and lifestyle adjustments.</p>
</li>
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<p><strong>Rare Diseases</strong>: Identifying carriers of genetic disorders can aid in family planning and reduce the incidence of inherited conditions.</p>
</li>
</ul><h3>The Ethical and Practical Concerns</h3><p>While genome screening offers incredible promise, it is not without challenges:</p><ol>
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<p><strong>Accuracy and Interpretation</strong>: Genetic predisposition does not guarantee disease. Misinterpretation of results can lead to unnecessary anxiety or unwarranted medical interventions.</p>
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<p><strong>Privacy and Data Security</strong>: Genetic data is highly sensitive. Ensuring robust data protection measures is crucial to prevent misuse.</p>
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<p><strong>Accessibility and Equity</strong>: High costs and limited availability may restrict access to genome screening, exacerbating health disparities.</p>
</li>
</ol><h3>Balancing Science and Pseudoscience</h3><p>The comparison of genome screening to horoscopes isn&rsquo;t entirely unfounded. Both offer predictive insights, but the scientific foundation of genome screening distinguishes it from astrology. Unlike the alignment of celestial bodies, genetic predictions are based on rigorous data and evidence. However, the probabilistic nature of genetic predispositions underscores the importance of interpreting results in conjunction with clinical and lifestyle factors.</p><h3>The Road Ahead</h3><p>As genome screening becomes more affordable and integrated into routine healthcare, its potential to transform lives is immense. Policymakers, healthcare providers, and genetic counselors must collaborate to ensure ethical implementation, public awareness, and equitable access.</p><p>Imagine a future where your genetic "horoscope" is a trusted guide, not just a prediction. Early genome screening could help chart a healthier path for generations, making it a cornerstone of personalized medicine. After all, our genes might just hold the key to unlocking a future of better health and well-being.</p><p>&nbsp;</p>]]></description>
	<dc:creator>LEGE</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44902/hite-a-fast-and-accurate-dynamic-boundary-adjustment-approach-for-full-length-transposable-elements-detection-and-annotation-in-genome-assemblies</guid>
	<pubDate>Sat, 20 Sep 2025 09:34:04 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44902/hite-a-fast-and-accurate-dynamic-boundary-adjustment-approach-for-full-length-transposable-elements-detection-and-annotation-in-genome-assemblies</link>
	<title><![CDATA[HiTE: a fast and accurate dynamic boundary adjustment approach for full-length Transposable Elements detection and annotation in Genome Assemblies]]></title>
	<description><![CDATA[<p dir="auto"><code>HiTE</code>&nbsp;is a Python software that uses a dynamic boundary adjustment approach to detect and annotate full-length Transposable Elements in Genome Assemblies. In comparison to other tools, HiTE demonstrates superior performance in detecting a greater number of full-length TEs.</p>
<div dir="auto">
<h2 dir="auto">panHiTE</h2>
<a href="https://github.com/CSU-KangHu/HiTE#panhite"></a></div>
<p dir="auto">We have developed panHiTE, a comprehensive and accurate pipeline for TE detection in large-scale population genomes. It has been successfully applied to hundreds of plant population genomes, demonstrating its effectiveness and scalability.</p>
<p dir="auto">For detailed instructions, please refer to the&nbsp;<a href="https://github.com/CSU-KangHu/HiTE/wiki/panHiTE-tutorial">panHiTE tutorial</a>.</p><p>Address of the bookmark: <a href="https://github.com/CSU-KangHu/HiTE" rel="nofollow">https://github.com/CSU-KangHu/HiTE</a></p>]]></description>
	<dc:creator>LEGE</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/45273/a-subway-map-for-the-genome</guid>
	<pubDate>Fri, 04 Sep 2026 04:14:14 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/45273/a-subway-map-for-the-genome</link>
	<title><![CDATA[A Subway Map for the Genome]]></title>
	<description><![CDATA[<p>Maya was looking at a genome graph on her computer. There were nodes, branches, and paths going in every direction.</p><p>&ldquo;It&rsquo;s like a subway map,&rdquo; she said, &ldquo;but for DNA.&rdquo;</p><p>That idea is exactly what Sequence Tube Map brings to life.</p><p>Instead of showing a genome as one long, confusing sequence, it displays different genomic paths like routes on a metro map. Where sequences are shared, the paths travel together. Where genetic variation occurs, they branch into different routes and may join again later.</p><p>This makes complex genome graphs much easier to explore.</p><p>Maya could now see how different haplotypes moved through the same genomic region and where they took different paths. She could even view sequencing reads mapped onto the graph, helping her understand what was happening in regions with genetic variation.</p><p>What once looked like a tangled network now looked like a journey.</p><p>Sequence Tube Map turns the complexity of graph genomes into a visual story&mdash;making it easier for scientists to see how DNA can take different routes.</p><p>Read more at&nbsp; https://github.com/vgteam/sequencetubemap&nbsp;</p><p>and</p><p>https://academic.oup.com/bioinformatics/article/35/24/5318/5542397</p><p>Demo at&nbsp;https://vgteam.github.io/sequenceTubeMap/</p>]]></description>
	<dc:creator>LEGE</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/45306/the-genes-that-travel-together-a-genomic-detective-story</guid>
	<pubDate>Fri, 11 Sep 2026 13:00:36 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/45306/the-genes-that-travel-together-a-genomic-detective-story</link>
	<title><![CDATA[The Genes That Travel Together: A Genomic Detective Story]]></title>
	<description><![CDATA[<p>Imagine looking through thousands of microbial genomes and discovering two genes that repeatedly appear together. The obvious conclusion is that they must somehow be connected&mdash;that perhaps they work together, participate in the same pathway, or depend on each other. But evolution has a way of leaving misleading clues. What if these two genes are found together simply because they were inherited from the same ancient ancestor? In that case, their apparent association may have little to do with their biological function; it may simply be a reflection of shared evolutionary history. This is the intriguing problem addressed by CORGIAS (https://github.com/ynishimuraLv/corgias), a computational framework developed to distinguish genuine gene associations from correlations created by common ancestry.</p><p>Instead of asking only whether two genes occur together across genomes, CORGIAS asks a deeper question: did these genes actually evolve together, repeatedly gaining or losing their presence in concert, or are they merely travelling together because of their inherited history? The framework introduces two complementary approaches, Ancestral State Adjustment (ASA) and the Simultaneous EVolution test (SEV), which incorporate evolutionary information into the search for gene associations. This distinction becomes increasingly important as genome sequencing continues to uncover enormous numbers of microbial genomes, many from organisms that have never been cultured and whose genes remain functionally mysterious. In this growing genomic landscape, simply finding a gene is no longer enough&mdash;we need clues about what that gene might be doing. CORGIAS approaches this problem almost like a genomic detective: rather than treating every association as evidence, it reconstructs the evolutionary story behind the association and asks whether the evidence survives that history. By doing so, it offers a way to separate coincidence from biological connection and potentially uncover functional relationships hidden within the vast microbial genomic landscape. The broader message is beautifully simple: genes do not evolve in isolation, and understanding what they do may require us to look beyond where they are today and reconstruct how they arrived there. Sometimes, the most important clue in a genome is not the gene itself, but the evolutionary journey it has taken.</p><p>More at&nbsp;https://academic.oup.com/nargab/article/7/4/lqaf182/8377910?</p>]]></description>
	<dc:creator>BioStar</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/40868/inrae-organises-open-competitions-to-recruit-research-scientists-on-permanent-positions</guid>
  <pubDate>Sun, 02 Feb 2020 23:08:36 -0600</pubDate>
  <link></link>
  <title><![CDATA[INRAE organises open competitions to recruit research scientists on permanent positions.]]></title>
  <description><![CDATA[
<p>Each year, INRAE organises open competitions to recruit research scientists on permanent positions. The recruitment campaign is generally aimed at researchers who have recently obtained their PhD. Candidates are recruited on the basis of their scientific competence which they will put to the service of INRAE's major research axes by responding to a research topic. Candidates must have published articles on the results of their PhD.</p>

<p>Campaign calendar:</p>

<p>- Opening date for applications: January 30, 2020<br />- Deadline for applications: March 5, 2020<br />- Pre-selections: April-May 2020<br />- Final selections: May-June 2020<br />- Starting date for appointments: from September 2020</p>

<p>More at https://jobs.inrae.fr/en/open-competitions/open-competions-research-scientists-crcn</p>
]]></description>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/43768/summer-school-open-to-phd-students</guid>
  <pubDate>Wed, 02 Feb 2022 06:08:35 -0600</pubDate>
  <link></link>
  <title><![CDATA[Summer school open to PhD students]]></title>
  <description><![CDATA[
<p>Some PhD students are organizing a summer school open to PhD students with different backgrounds and interests.</p>

<p>Several sessions and workshops will be held within five focus groups, and one common theme: mountain research.</p>

<p>The summer school will take place in Obergurgl, in the middle of the Austrian Alps, September 5-9.</p>

<p>Abstract submission is now open, until February 16th: https://www.imc2022.info/summerschool/</p>

<p>The summer school takes place in the context of the International Mountain Conference 2022, Innsbruck, Austria: https://www.imc2022.info/</p>

<p>Please feel free to spread the word among potentially interested colleagues and PhD students.</p>

<p>"Capponi, Lisa"</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/926/list-of-popular-bioinformatics-softwaretools</guid>
	<pubDate>Tue, 16 Jul 2013 14:30:30 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/926/list-of-popular-bioinformatics-softwaretools</link>
	<title><![CDATA[List of popular bioinformatics software/tools]]></title>
	<description><![CDATA[<p><a href="http://samtools.sourceforge.net/swlist.shtml">I</a>n current genome era, our day to day work is to handle the huge geneome sequences, expression data, several other datasets. This link provide a comprehensive list of commonly used sofware/tools.</p><p>Address of the bookmark: <a href="http://samtools.sourceforge.net/swlist.shtml" rel="nofollow">http://samtools.sourceforge.net/swlist.shtml</a></p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/8265/list-of-generic-simulation-softwaretoolsresource-with-brief-description-and-homepage</guid>
	<pubDate>Mon, 10 Feb 2014 05:57:29 -0600</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/8265/list-of-generic-simulation-softwaretoolsresource-with-brief-description-and-homepage</link>
	<title><![CDATA[List of generic simulation software/tools/resource with brief description and homepage !!!]]></title>
	<description><![CDATA[<p>List of generic simulation software/tools/resource with brief description and homepage</p><p><img src="http://www.evolution-of-life.com/fileadmin/images/carousel/genetic.PNG" alt="image" style="border: 0px;"></p><p>ALF <br />A Simulation Framework for Genome Evolution <br />http://www.cbrg.ethz.ch/alf<br /><br />Bayesian Serial SimCoal <br />Bayesian Serial SimCoal, (BayeSSC) is a modification of SIMCOAL 1.0, a program written by Laurent Excoffier, John Novembre, and Stefan Schneider. <br />http://www.stanford.edu/group/hadlylab/ssc/index.html<br /><br />BEERS <br />BEERS was designed to benchmark RNA-Seq alignment algorithms and also algorithms that aim to reconstruct different isoforms and alternate splicing from RNA-Seq data <br />http://cbil.upenn.edu/beers/<br /><br />BOTTLENECK <br />Bottleneck is a program for detecting recent effective population size reductions from allele data frequencies <br />http://www.ensam.inra.fr/urlb/bottleneck/bottleneck.html<br /><br />BottleSim <br />BottleSim is a computer simulation program for simulating the process of population bottlenecks <br />http://chkuo.name/software/bottlesim.html<br /><br />CASS <br />Protein Sequence Simulation <br />http://www.wyomingbioinformatics.org/liberlesgroup/cass/<br /><br />CDPOP <br />CDPOP is a landscape genetics tool for simulating the emergence of spatial genetic structure in populations resulting from specified landscape processes governing organism movement behavior. <br />http://cel.dbs.umt.edu/cdpop<br /><br />CoalFace <br />CoalFace is a simulation of the coalescent process with the visual display of gene genealogies. <br />http://web.up.ac.za/default.asp?ipkcategoryid=3283<br /><br />CoaSim <br />CoaSim is a tool for simulating the coalescent process with recombination and geneconversion under various demographic models. <br />http://users-birc.au.dk/mailund/coasim/index.html<br /><br />cosi <br />The cosi package is written in C and is available as a tar file. <br />http://www.broadinstitute.org/~sfs/cosi/<br /><br />CS-PSeq-Gen <br />A program to simulate the evolution of protein sequences under the constraints of the information of a particular reconstructed phylogeny <br />http://bioserv.rpbs.univ-paris-diderot.fr/software/cs-pseq-gen.html<br /><br />DAWG <br />An application designed to simulate the evolution of recombinant DNA sequences in continuous time <br />http://scit.us/projects/dawg<br /><br />Easypop <br />EASYPOP is an individual based model intended to simulate datasets under a very broad range of conditions <br />http://www.unil.ch/dee/page36926_fr.html<br /><br />EggLib <br />EggLib is a C++/Python library and program package for evolutionary genetics and genomics. <br />http://egglib.sourceforge.net/<br /><br />EvolSimulator <br />A simulation test bed for hypotheses of genome evolution <br />http://acb.qfab.org/acb/evolsim/<br /><br />EvolveAGene <br />A realistic coding sequence simulation program that separates mutation from selection and allows the user to set selection conditions <br />http://bellinghamresearchinstitute.com/software/index.html<br /><br />fastsimcoal <br />A continuous-&not;‐time coalescent simulator of genomic diversity under arbitrarily complex evolutionary scenarios <br />http://cmpg.unibe.ch/software/fastsimcoal/<br /><br />FastSLINK <br />Simulation of Marker and Phenotype Data in Pedigrees <br />http://watson.hgen.pitt.edu/<br /><br />FFPopSim <br />C++/Python library for population genetics. <br />http://webdav.tuebingen.mpg.de/ffpopsim/<br /><br />FLUX SIMULATOR <br />The Flux Simulator aims at providing a deterministic in silico reproduction of the experimental pipelines for RNA-Seq, employing a minimal set of parameters. <br />http://flux.sammeth.net/simulator.html<br /><br />ForSim <br />ForSim: A Forward Evolutionary Computer Simulation <br />http://www.anthro.psu.edu/weiss_lab/research.shtml<br /><br />ForwSim <br />The program given below is based on the algorithm described in Padhukasahasram et al. 2008 to simulate genetic drift in a standard Wright-Fisher process. <br />http://badri-populationgeneticsimulators.blogspot.com/<br /><br />FPG <br />Forward Population Genetic simulation <br />http://genfaculty.rutgers.edu/hey/software#fpg<br /><br />FREGENE <br />FREGENE is a C++ program that simulates sequence-like data over large genomic regions in large diploid populations. <br />http://www.ebi.ac.uk/projects/bargen/download/fregen/documentation_html.html<br /><br />GAMETES <br />Genetic Architecture Model Emulator for Testing and Evaluating Software: Simulates complex SNP models with pure, strict epistatic interactions with n-loci. <br />http://sourceforge.net/projects/gametes/?source=navbar<br /><br />GASP <br />Genometric Analysis Simulation Program. A software tool for testing and investigating methods in statistical genetics by generating samples of family data based on user specified models. <br />http://research.nhgri.nih.gov/gasp/<br /><br />GemSIM <br />Next generation sequencing read simulator <br />http://sourceforge.net/projects/gemsim/<br /><br />GeneArtisan <br />Simulation of Markers in Case-Control Study Designs <br />http://www.rannala.org/?page_id=241<br /><br />GENOME <br />A rapid coalescent-based whole genome simulator <br />http://www.sph.umich.edu/csg/liang/genome/<br /><br />GenomePop2 <br />GenomePop2 is a specialization of the program GenomePop just to manage SNPs under more flexible and useful settings. If you need models with more than 2 alleles please use the GenomePop program version. <br />http://webs.uvigo.es/acraaj/genomepop2.htm<br /><br />GenomeSimla <br />GenomeSIMLA is currently under development- however, we have a beta release that we are asking to be tested <br />http://chgr.mc.vanderbilt.edu/genomesimla/<br /><br />GENS2 <br />Simulates interactions among two genetic and one environmental factor and also allows for epistatic interactions. <br />https://sourceforge.net/projects/gensim/<br /><br />GWAsimulator <br />A rapid whole genome simulation program <br />http://biostat.mc.vanderbilt.edu/wiki/main/gwasimulator<br /><br />HAP-SAMPLE <br />An association simulator for candidate regions or genome scans <br />http://www.hapsample.org/<br /><br />HAPGEN <br />A simulator for the simulation of case control datasets at SNP markers <br />https://mathgen.stats.ox.ac.uk/genetics_software/hapgen/hapgen2.html<br /><br />HapSim <br />A simulation tool for generating haplotype data with pre-specified allele frequencies and LD coefficients <br />http://cran.r-project.org/web/packages/hapsim/index.html<br /><br />HAPSIMU <br />A program that simulates heterogeneous populations with various known and controllable structures under the continuous migration model or the discrete model <br />http://l.web.umkc.edu/liujian/<br /><br />IBDsim <br />IBDSim is a computer package for the simulation of genotypic data under general isolation by distance models. <br />http://raphael.leblois.free.fr/<br /><br />indel-Seq-Gen <br />A biological sequence simulation program that simulates highly divergent DNA sequences and protein superfamilies <br />http://bioinfolab.unl.edu/~cstrope/isg/<br /><br />Indelible <br />A powerful and flexible simulator of biological evolution <br />http://abacus.gene.ucl.ac.uk/software/indelible/<br /><br />invertFREGENE <br />InvertFREGENE is a forward-in-time simulator of inversions in population genetic data <br />http://www.ebi.ac.uk/projects/bargen/<br /><br />kernalPop <br />A spatially explicit population genetic simulation engine <br />http://cran.r-project.org/src/contrib/archive/kernelpop/<br /><br />MaCS <br />Markovian Coalescent Simulator <br />http://www-hsc.usc.edu/~garykche/<br /><br />Mason <br />A package for the simulation of nucleotide data. <br />http://www.seqan.de/projects/mason/<br /><br />mbs <br />modifying Hudson's ms software to generate samples of DNA sequences with a biallelic site under selection <br />http://www.sendou.soken.ac.jp/esb/innan/innanlab/software.html<br /><br />Mendel's Accountant <br />Mendel's Accountant (MENDEL) is an advanced numerical simulation program for modeling genetic change over time and was developed collaboratively by Sanford, Baumgardner, Brewer, Gibson and ReMine <br />http://mendelsaccount.sourceforge.net/<br /><br />MetaSim <br />A tool to generate collections of synthetic reads that reflect the diverse taxonomical composition of typical metagenome data sets <br />http://ab.inf.uni-tuebingen.de/software/metasim/<br /><br />mlcoalsim <br />Multilocus Coalescent Simulations <br />http://code.google.com/p/mlcoalsim-v1/<br /><br />ms <br />The purpose of this program is to allow one to investigate the statistical properties of such samples, to evaluate estimators or statistical tests, and generally to aid in the interpretation of polymorphism data sets. <br />http://home.uchicago.edu/~rhudson1/source/mksamples.html<br /><br />msHOT <br />The purpose of this program is to allow one to investigate the statistical properties of such samples, to evaluate estimators or statistical tests, and generally to aid in the interpretation of polymorphism data sets. <br />http://home.uchicago.edu/~rhudson1/<br /><br />msms <br />A coalescent Simlation tool with selection. <br />http://www.mabs.at/ewing/msms/index.shtml<br /><br />MySSP <br />A program for the simulation of DNA sequence evolution across a phylogenetic tree <br />http://www.rosenberglab.net/software.php<br /><br />Nemo <br />A forward-time, individual-based, genetically explicit, and stochastic simulation program designed to study the evolution of genetic markers, life history traits, and phenotypic traits in a flexible (meta-)population framework. <br />http://nemo2.sourceforge.net/<br /><br />NetRecodon <br />Coalescent simulation of coding DNA sequences with recombination (inter and intracodon), migration and demography <br />http://code.google.com/p/netrecodon/<br /><br />PEDAGOG <br />Software for simulating eco-evolutionary population dynamics <br />https://bcrc.bio.umass.edu/pedigreesoftware/node/5<br /><br />phenosim <br />A tool to add phenotypes to simulated genotypes <br />http://evoplant.uni-hohenheim.de/doku.php?id=software:software<br /><br />PhyloSim <br />An R package for the Monte Carlo simulation of sequence evolution <br />http://bit.ly/rlsim-git<br /><br />pIRS <br />Profile-based Illumina pair-end reads simulator <br />https://code.google.com/p/pirs/<br /><br />ProteinEvolver <br />Simulation of protein evolution along phylogenies under structure-based substitution models <br />http://code.google.com/p/proteinevolver/<br /><br />QMSim <br />QTL and Marker Simulator <br />http://www.aps.uoguelph.ca/~msargol/qmsim/<br /><br />quantiNEMO <br />An individual-based program for the analysis of quantitative traits with explicit genetic architecture potentially under selection in a structured population <br />http://www2.unil.ch/popgen/softwares/quantinemo/<br /><br />RECOAL <br />Simulates new haplotype data from a reference population of haplotypes. <br />ftp://popgen.usc.edu/<br /><br />Recodon <br />Coalescent simulation of coding DNA sequences with recombination, migration and demography <br />http://code.google.com/p/recodon/<br /><br />rlsim <br />A package for simulating RNA-seq library preparation with parameter estimation <br />http://bit.ly/rlsim-git<br /><br />Rmetasim <br />Rmetasim is a front-end for the metasim engine that is implemented as a package that runs in the statistical computing environment R <br />http://linum.cofc.edu/software.html#metasim<br /><br />RNA Seq Simulator <br />RSS takes SAM alignment files from RNA-Seq data and simulates over dispersed, multiple replica, differential, non-stranded RNA-Seq datasets. <br />http://useq.sourceforge.net/cmdlnmenus.html#rnaseqsimulator<br /><br />Rose <br />Random model of sequence evolution <br />http://bibiserv.techfak.uni-bielefeld.de/rose/<br /><br />SelSim <br />SelSim is a program for Monte Carlo simulation of DNA polymorphism data for a recom- bining region within which a single bi-allelic site has experienced natural selection <br />http://www.well.ox.ac.uk/~spencer/selsim/<br /><br />Seq-Gen <br />An application for the Monte Carlo simulation of molecular sequence evolution along phylogenetic trees. <br />http://tree.bio.ed.ac.uk/software/seqgen/<br /><br />SEQPower <br />Statistical power analysis for sequence-based association studies <br />http://bioinformatics.org/spower/<br /><br />SeqSIMLA <br />SeqSIMLA can simulate sequence data with user-specified disease and quantitative trait models. Family or unrelated case-control data can be simulated. <br />http://seqsimla.sourceforge.net/<br /><br />Serial NetEvolve <br />A flexible utility for generating serially-sampled sequences along a tree or recombinant network <br />http://biorg.cis.fiu.edu/sne/<br /><br />SFS_CODE <br />SFS_CODE can perform forward population genetic simulations under a general Wright-Fisher model with arbitrary migration, demographic, selective, and mutational effects. <br />http://sfscode.sourceforge.net/sfs_code/index/index.html<br /><br />SIBSIM <br />Quantitative phenotype simulation in extended pedigrees <br />http://sourceforge.net/projects/sibsim/<br /><br />SIMCOAL2 <br />A coalescent program for the simulation of complex recombination patterns over large genomic regions under various demographic models <br />http://cmpg.unibe.ch/software/simcoal2/<br /><br />SimCopy <br />An R package simulating the evolution of copy number profiles along a tree. <br />http://bit.ly/simcopy<br /><br />SIMLA <br />SIMLA is a SIMuLAtion program that generates data sets of families for use in Linkage and Association studies. <br />http://www.chg.duke.edu/research/simla.html<br /><br />SimPed <br />A Simulation Program to Generate Haplotype and Genotype Data for Pedigree Structures <br />http://www.hgsc.bcm.tmc.edu/content/simped<br /><br />Simprot <br />A program to simulate protein evolution by substitution, insertion and deletion <br />http://www.uhnresearch.ca/labs/tillier/software.htm#3<br /><br />SimRare <br />Rare variant simulation and analysis tool <br />http://code.google.com/p/simrare/<br /><br />simuGWAS <br />A forward-time simulator that simulates realistic samples for genome-wide association studies. <br />http://simupop.sourceforge.net/cookbook/simucomplexdisease<br /><br />simuPOP <br />simuPOP is a general-purpose individual-based forward-time population genetics simulation environment. <br />http://simupop.sourceforge.net/<br /><br />SISSI <br />A software tool to generate data of related sequences along a given phylogeny, taking into account user defined system of neighbourhoods and instantaneous rate matrices. <br />http://www.cibiv.at/software/sissi/<br /><br />SNPsim <br />Coalescent simulation of hotspot recombination <br />http://code.google.com/p/phylosoftware/<br /><br />SPIP <br />SPIP simulates the transmission of genes from parents to offspring in a population having demographic structure defined by the user <br />http://swfsc.noaa.gov/textblock.aspx?division=fed&amp;id=3434<br /><br />Splatche <br />Spatial and Temporal Coalescences in Heterogeneous Environment <br />http://www.splatche.com/<br /><br />srv <br />Simulator of Rare Varaints (srv) is a simulator for the simulation of the introduction and evolution of (rare) genetic variants. <br />http://simupop.sourceforge.net/cookbook/simurarevariants<br /><br />SUP <br />SLINK/FastSLINK utility program <br />http://mlemire.freeshell.org/software.html<br /><br />TreesimJ <br />A flexible, forward-time population genetic simulator <br />http://code.google.com/p/treesimj/<br /><br />Vortex <br />VORTEX is an individual-based simulation model for population viability analysis (PVA). <br />http://www.vortex9.org/vortex.html<br /><br />References:</p><p>Image www.evolution-of-life.com</p><p>www.cancer.gov</p>]]></description>
	<dc:creator>Jit</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/17924/software-developed-in-pevsner-lab</guid>
	<pubDate>Mon, 06 Oct 2014 12:41:26 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/17924/software-developed-in-pevsner-lab</link>
	<title><![CDATA[Software developed in pevsner lab]]></title>
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<p><a href="http://pevsnerlab.kennedykrieger.org/dragon.htm">DRAGON</a>: Database Referencing of Array Genes Online</p>
<p><a href="http://pevsnerlab.kennedykrieger.org/php/node/96">SNOMAD</a>: Standardization and Normalization of Microarray Data</p>
<p><a href="http://pevsnerlab.kennedykrieger.org/php/node/70">SNPduo</a>: SNP Analysis Between Two Individuals</p>
<p><a href="http://pevsnerlab.kennedykrieger.org/php/node/71">SNPtrio</a>: Analyzing and Visualizing and Inheritance Patterns in Trios</p>
<p><a href="http://pevsnerlab.kennedykrieger.org/php/node/64">SNPscan</a>: Data Analysis and Visualization of SNP Data</p>
<p><a href="http://pevsnerlab.kennedykrieger.org/php/node/64">pediSNP</a>: Analyze SNP Data From a Pedigree of Two Generations</p>
<p><a href="http://pevsnerlab.kennedykrieger.org/php/node/73">kcoeff</a>: Calculate Cotterman Coefficients of SNP Genotype Data</p>
<p><a href="http://pevsnerlab.kennedykrieger.org/php/node/113">triPOD:</a> Detects chromosomal abnormalities in parent-child trio-based microarray data</p>
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</div><p>Address of the bookmark: <a href="http://pevsnerlab.kennedykrieger.org/php/?q=software" rel="nofollow">http://pevsnerlab.kennedykrieger.org/php/?q=software</a></p>]]></description>
	<dc:creator>Robert M Willioms</dc:creator>
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