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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/6027?offset=230</link>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36267/pspairwise-sequentially-markovian-coalescent-psmc-model</guid>
	<pubDate>Thu, 19 Apr 2018 05:29:23 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36267/pspairwise-sequentially-markovian-coalescent-psmc-model</link>
	<title><![CDATA[PSPairwise Sequentially Markovian Coalescent (PSMC) model]]></title>
	<description><![CDATA[<p><span>Implementation of the Pairwise Sequentially Markovian Coalescent (PSMC) model</span></p><p>Address of the bookmark: <a href="https://github.com/lh3/psmc" rel="nofollow">https://github.com/lh3/psmc</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/38649/ngs-platforms-launched-by-bgi%E2%80%99s-mgi-tech</guid>
	<pubDate>Thu, 10 Jan 2019 04:42:06 -0600</pubDate>
	<link>https://bioinformaticsonline.com/news/view/38649/ngs-platforms-launched-by-bgi%E2%80%99s-mgi-tech</link>
	<title><![CDATA[NGS Platforms launched by BGI’s MGI Tech]]></title>
	<description><![CDATA[<p>MGI Tech Co., Ltd. (MGI), a subsidiary of BGI Group, is committed to enabling effective and affordable healthcare solutions for all. Based on its proprietary technology, MGI produces sequencing devices, equipment, consumables and reagents to support life science research, medicine and healthcare. MGI's multi-omics platforms include genetic sequencing, mass spectrometry and medical imaging. Providing real-time, comprehensive, life-long solutions, its mission&nbsp;is to&nbsp;develop and promote advanced life science tools for future healthcare.</p><p>MGI, a subsidiary of global genomics leader BGI Group, announced pricing and its first early access customer for the new ultra high-throughput sequencer, MGISEQ-T7, saying it has driven down sequencing cost to&nbsp;$5&nbsp;per gigabyte, with exceptionally high accuracy. Such innovations are helping more people to realize the benefits of genomic information.</p><p>In October, MGI launched the MGISEQ-T7, a highly flexible production-scale platform that is the most powerful sequencer to date. It can produce as many as 60 whole human genomes in one day. The instrument sells for&nbsp;$1 million.</p><p>The T7 enables simultaneous but independent operation of up to four flow cells, which means different applications such as single-cell RNA sequencing, whole exome sequencing and whole genome sequencing can be run in different flow cells at the same time. This helps to reduce costs, allowing MGI to offer the most competitive sequencing price in the market.</p><p><span>Powered by DNBseq&trade;, MGISEQ delivers quality data with accuracy for SNP and Indel calling rate of 99.9% and 99%, respectively, along with decreased duplication rate down to less than 2 percent, and almost zero Index mis-assignment rate.</span></p><p><span><span>SOURCE MGI</span></span></p><p>https://www.bgi.com/global/company/news/bgis-mgi-tech-launches-two-new-ngs-platforms/</p><p>http://en.mgitech.cn/</p>]]></description>
	<dc:creator>Jit</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40834/nucleus-python-and-c-code-for-reading-and-writing-genomics-data</guid>
	<pubDate>Sun, 02 Feb 2020 08:14:19 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40834/nucleus-python-and-c-code-for-reading-and-writing-genomics-data</link>
	<title><![CDATA[Nucleus: Python and C++ code for reading and writing genomics data.]]></title>
	<description><![CDATA[<p>Nucleus is a library of Python and C++ code designed to make it easy to read, write and analyze data in common genomics file formats like SAM and VCF. In addition, Nucleus enables painless integration with the TensorFlow machine learning framework, as anywhere a genomics file is consumed or produced, a TensorFlow tfrecords file may be used instead.</p><p>Address of the bookmark: <a href="https://github.com/google/nucleus" rel="nofollow">https://github.com/google/nucleus</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41493/coronavirus-resources</guid>
	<pubDate>Wed, 25 Mar 2020 17:11:33 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41493/coronavirus-resources</link>
	<title><![CDATA[Coronavirus Resources !]]></title>
	<description><![CDATA[<p><span>2019nCoVR features comprehensive integration of genomic and proteomic sequences as well as their metadata information from the GISAID, NCBI, NMDC and CNCB/NGDC. It also incorporates a wide range of relevant information including scientific literatures, news, and popular articles for science dissemination, and provides visualization functionalities for genome variation analysis results based on all collected 2019-nCoV strains.</span></p>
<p><span>Annotation</span></p>
<p><span><a href="https://bigd.big.ac.cn/ncov/variation/annotation">https://bigd.big.ac.cn/ncov/variation/annotation</a></span></p>
<p><span>Genome wharehouse&nbsp;</span></p>
<p><span><a href="https://bigd.big.ac.cn/gwh/browse/index">https://bigd.big.ac.cn/gwh/browse/index</a></span></p>
<p>Released Genome</p>
<p><a href="https://bigd.big.ac.cn/ncov/release_genome">https://bigd.big.ac.cn/ncov/release_genome</a></p>
<p>Download data&nbsp;</p>
<p><a href="ftp://download.big.ac.cn/Genome/Viruses/Coronaviridae/">ftp://download.big.ac.cn/Genome/Viruses/Coronaviridae/</a></p>
<p>Raw data</p>
<p><a href="https://bigd.big.ac.cn/gsa/browse/run/?tag=Coronaviridae">https://bigd.big.ac.cn/gsa/browse/run/?tag=Coronaviridae</a></p><p>Address of the bookmark: <a href="https://bigd.big.ac.cn/ncov/about" rel="nofollow">https://bigd.big.ac.cn/ncov/about</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/42793/fully-funded-position-as-phd-research-fellow-in-genomicsbioinformatics</guid>
  <pubDate>Wed, 03 Feb 2021 04:18:57 -0600</pubDate>
  <link></link>
  <title><![CDATA[Fully funded position as PhD Research Fellow in genomics/bioinformatics]]></title>
  <description><![CDATA[
<p>A fully funded position as PhD Research Fellow in genomics/bioinformatics is available at the Section for Genetics and Evolutionary Biology (EVOGENE) at the Department of Biosciences, University of Oslo.</p>

<p>The fellowship will be for a period of 3 years, or for a period of 4 years, with 25 % compulsory work (e.g. teaching responsibilities at the department) contingent on the qualifications of the candidate and the teaching needs of the department.</p>

<p>Starting date no later than October 1, 2021.</p>

<p>More at https://www.jobbnorge.no/en/available-jobs/job/199984/phd-research-fellow-in-genomics-and-bioinformatics</p>
]]></description>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/43928/bioinformaticians-in-comparative-and-evolutionary-genomics</guid>
  <pubDate>Tue, 02 Aug 2022 01:22:48 -0500</pubDate>
  <link></link>
  <title><![CDATA[Bioinformaticians in comparative and evolutionary genomics]]></title>
  <description><![CDATA[
<p>NBIS is now looking for a new member to support Swedish research in evolutionary, comparative, and population genomics, with a particular focus on conifer genomics.</p>

<p>Your tasks will consist of:</p>

<p>Advanced bioinformatics analyses within research projects across Sweden, including key involvement in a major research effort in conifer genomics.<br />Development of bioinformatics tools and workflows.<br />Educating other scientists in bioinformatics through collaboration within supported projects, teaching at national courses, and through participating in various networks.<br />Taking part in the continuous development of NBIS/SciLifeLab at a national level</p>

<p>More at https://www.uu.se/en/about-uu/join-us/details/?positionId=518909</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/44799/unlocking-evolutionary-secrets-a-dive-into-comparative-genomics-methods</guid>
	<pubDate>Tue, 20 May 2025 00:25:09 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/44799/unlocking-evolutionary-secrets-a-dive-into-comparative-genomics-methods</link>
	<title><![CDATA[Unlocking Evolutionary Secrets: A Dive into Comparative Genomics Methods]]></title>
	<description><![CDATA[<p>Comparative genomics is the art and science of comparing genomes&mdash;across species, within species, or even among individuals&mdash;to unravel evolutionary relationships, functional elements, and genetic adaptations. As sequencing technologies have advanced and genome databases have expanded, comparative genomics has become a cornerstone of modern biology, shedding light on everything from antibiotic resistance in bacteria to human disease genetics.</p><p>In this post, we&rsquo;ll explore the core methods used in comparative genomics, the questions they help answer, and how they&rsquo;re shaping our understanding of life.</p><p><strong>1. Whole-Genome Alignment</strong><br />Whole-genome alignment involves mapping the entire genome of one species to another. Tools like MUMmer, MAUVE, and LASTZ perform large-scale sequence alignments to detect conserved regions, rearrangements, insertions, and deletions.</p><p>Use Case:<br />Comparing human and chimpanzee genomes to identify evolutionary conserved sequences (ECS) and regions of divergence.</p><p>Key Challenges:<br />Handling repetitive sequences and genome rearrangements.</p><p>Computational complexity in large genomes.</p><p><strong>2. Synteny and Collinearity Analysis</strong><br />Synteny refers to conserved blocks of gene order across species. Tools like MCScanX, SynMap, or CHITRA (for visualizing synteny interactively) detect these blocks to understand chromosomal evolution.</p><p>Use Case:<br />Studying ancient genome duplications in plants.</p><p>Investigating chromosomal rearrangements in cancer genomes.</p><p><strong>3. Ortholog and Paralog Detection</strong><br />Orthologs are genes in different species that evolved from a common ancestor, while paralogs are genes duplicated within a genome. Identifying them is crucial for functional annotation and evolutionary studies.</p><p>Popular Tools:<br />OrthoFinder, Orthologous MAtrix (OMA), InParanoid, and EggNOG.</p><p>Use Case:<br />Functional prediction of uncharacterized genes based on orthologs in model organisms.</p><p>Tracing gene family evolution.</p><p><strong>4. Phylogenomic Analysis</strong><br />Phylogenomic methods combine phylogenetics and genomics to infer evolutionary trees based on genome-wide data. These methods can handle dozens to hundreds of genomes, using concatenated alignments or gene trees.</p><p>Tools:<br />RAxML, IQ-TREE, ASTRAL, Phylip, BEAST.</p><p>Use Case:<br />Resolving the evolutionary relationships between microbial species.</p><p>Studying speciation events.</p><p><strong>5. Pan-Genome Analysis</strong><br />The pan-genome consists of the core genome (shared by all strains) and the accessory genome (strain-specific genes). This is especially popular in microbial genomics.</p><p>Tools:<br />Roary, Panaroo, BPGA, PGAP.</p><p>Use Case:<br />Understanding virulence factor diversity in E. coli.</p><p>Designing broad-spectrum vaccines.</p><p><strong>6. Comparative Transcriptomics</strong><br />Comparing transcriptomes across species or conditions reveals conserved and unique expression patterns. RNA-seq data can be mapped to reference genomes to identify orthologous expression profiles.</p><p>Use Case:<br />Comparing stress response in extremophiles and model species.</p><p>Studying conserved regulatory networks.</p><p><strong>7. Functional Element Comparison</strong><br />Beyond genes, comparative genomics also targets non-coding regions&mdash;enhancers, promoters, miRNAs. Conservation across species often implies functional importance.</p><p>Tools:<br />PhastCons, GERP, phyloP (based on multiple alignments).</p><p>Use Case:<br />Detecting conserved non-coding elements in vertebrates.</p><p>Studying regulatory divergence in human evolution.</p><p><strong>8. Horizontal Gene Transfer (HGT) Detection</strong><br />In microbes, genes often jump across species boundaries. Comparative genomics can detect HGT by identifying genes that defy the expected phylogenetic pattern.</p><p>Tools:<br />HGTector, DarkHorse, AlienHunter, SIGI-HMM.</p><p>Use Case:<br />Tracing antibiotic resistance genes.</p><p>Exploring microbial adaptability in extreme environments.</p><p><strong>Final Thoughts</strong><br />Comparative genomics is a powerful lens to observe the diversity and unity of life. With a broad toolkit&mdash;from aligners to orthology pipelines, phylogenetic engines to visualization tools&mdash;it allows scientists to ask big questions: How did genomes evolve? What makes species unique? Where do new genes come from?</p><p>Whether you're studying extremophiles, building better crops, or exploring human ancestry, comparative genomics offers the methods to connect the dots across the tree of life.</p><p>&nbsp;</p>]]></description>
	<dc:creator>LEGE</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/4099/sequencing-solutions-to-world-health</guid>
	<pubDate>Thu, 29 Aug 2013 15:05:35 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/4099/sequencing-solutions-to-world-health</link>
	<title><![CDATA[Sequencing Solutions to World Health]]></title>
	<description><![CDATA[<p>"<em>New technology that quickly, easily and economically reveals the genomes of viruses and pathogens transforms public health and medicine."</em></p>
<p><strong>Source</strong>: Life technologies</p><p>Address of the bookmark: <a href="http://www.lifetechnologies.com/global/en/home/communities-social/blog/blogs/sequencing-solutions-to-world-health.html?cid=social_blogseries_20130829_11098264" rel="nofollow">http://www.lifetechnologies.com/global/en/home/communities-social/blog/blogs/sequencing-solutions-to-world-health.html?cid=social_blogseries_20130829_11098264</a></p>]]></description>
	<dc:creator>Rahul Agarwal</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/videolist/watch/5965/if-your-genes-revealed-you-would-get-a-disease-would-you-want-to-know</guid>
	<pubDate>Wed, 30 Oct 2013 19:35:31 -0500</pubDate>
	<link>https://bioinformaticsonline.com/videolist/watch/5965/if-your-genes-revealed-you-would-get-a-disease-would-you-want-to-know</link>
	<title><![CDATA[If your genes revealed you would get a disease, would you want to know?]]></title>
	<description><![CDATA[<iframe width="" height="" src="https://www.youtube-nocookie.com/embed/ZdDN8pm6gbY" frameborder="0" allowfullscreen></iframe><p>A massive, groundbreaking new study underway at Kaiser Permanente and the University of California San Francisco may shed light one day on the genetic roots of diseases such as Parkinson's, cancer, Alzheimer's. We asked people in San Francisco's Union Square for their take on this question: If a genetic test revealed you were at high risk for getting a disease, would want to know?</p>]]></description>
	
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