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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/40611?offset=270</link>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37602/indexcov-fast-coverage-quality-control-for-whole-genome-sequencing</guid>
	<pubDate>Wed, 29 Aug 2018 09:20:46 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37602/indexcov-fast-coverage-quality-control-for-whole-genome-sequencing</link>
	<title><![CDATA[Indexcov: fast coverage quality control for whole-genome sequencing]]></title>
	<description><![CDATA[<p><em>indexcov</em><span>, an efficient estimator of whole-genome sequencing coverage to rapidly identify samples with aberrant coverage profiles, reveal large-scale chromosomal anomalies, recognize potential batch effects, and infer the sex of a sample.&nbsp;</span><em>Indexcov</em><span>&nbsp;is available at&nbsp;</span><a href="https://github.com/brentp/goleft" target="_blank">https://github.com/brentp/goleft</a><span>&nbsp;under the MIT license.</span></p><p>Address of the bookmark: <a href="https://github.com/brentp/goleft" rel="nofollow">https://github.com/brentp/goleft</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37749/d2tools-the-toolbox-for-counting-the-frequency-of-k-tuple-from-sequencing-datasets-and-calculate-the-dissimilarity</guid>
	<pubDate>Thu, 20 Sep 2018 08:38:29 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37749/d2tools-the-toolbox-for-counting-the-frequency-of-k-tuple-from-sequencing-datasets-and-calculate-the-dissimilarity</link>
	<title><![CDATA[d2Tools: The toolbox for counting the frequency of k-tuple from sequencing datasets and calculate the dissimilarity]]></title>
	<description><![CDATA[<p><code>d2Tools</code>&nbsp;are the toolbox for counting the frequency of K-tuple from sequencing datasets and then calculating the pairwise dissimilarity matrix between samples with the&nbsp;<strong>d2-style</strong>(d2/d2<code>*</code>/d2S representing d2/d2Star/d2shepp, respectively) measures. Hao, Dai, Eucliean, Mahattan, and Chebyshev distance measures are also included in d2Tools.</p>
<p>Manual at&nbsp;https://code.google.com/archive/p/d2-tools/wikis/d2ToolMannual.wiki</p><p>Address of the bookmark: <a href="https://code.google.com/archive/p/d2-tools/" rel="nofollow">https://code.google.com/archive/p/d2-tools/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<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>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/39827/prof-dr-med-andreas-ramming</guid>
  <pubDate>Wed, 07 Aug 2019 03:25:48 -0500</pubDate>
  <link></link>
  <title><![CDATA[Prof. Dr. med. Andreas Ramming]]></title>
  <description><![CDATA[
<p>In many autoimmune diseases, a misdirected immune response leads to chronic inflammation and subsequently to fibrotic and degenerative tissue remodeling. Therapeutic options are available for inflammatory joint diseases, but only about 40% of patients respond to these existing therapies on a permanent basis. In the remaining cases, these therapies miss their target from the beginning or later during the course of treatment failure. There are currently no causal therapies available for the treatment of fibrotic autoimmune diseases such as systemic sclerosis. Therefore, there is an urgent need to develop new therapeutic options for the treatment of fibrotic and synovitic autoimmune diseases. His group is therefore deal with the molecular mechanisms of these misdirected signaling pathways for the development of novel, targeted therapies</p>

<p>http://www.medizin3.uk-erlangen.de/forschung/arbeitsgruppen/matrixbiologie-entzuendliche-signalwege-in-arthritis-und-fibrose/</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40701/fastgt-an-alignment-free-method-for-calling-common-snvs-directly-from-raw-sequencing-reads</guid>
	<pubDate>Tue, 28 Jan 2020 03:27:33 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40701/fastgt-an-alignment-free-method-for-calling-common-snvs-directly-from-raw-sequencing-reads</link>
	<title><![CDATA[FastGT: an alignment-free method for calling common SNVs directly from raw sequencing reads]]></title>
	<description><![CDATA[<p>FastGT is a program package for whole-genome genotyping of genome variants directly from raw sequencing reads. It is written in C and runs in Linux. FastGT uses a list of variant-specific k-mer pairs that are unique in human genome, counts the frequency of k-mers in sequencing data and predicts the genotype. All this takes less than 1 hour on average low-cost Linux server.</p>
<p><a href="http://bioinfo.ut.ee/FastGT/">http://bioinfo.ut.ee/FastGT/</a></p>
<p><strong><a href="https://github.com/bioinfo-ut/GenomeTester4/">https://github.com/bioinfo-ut/GenomeTester4/</a></strong></p><p>Address of the bookmark: <a href="http://bioinfo.ut.ee/FastGT/" rel="nofollow">http://bioinfo.ut.ee/FastGT/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41599/haslr-a-hybrid-assembler-which-uses-both-second-and-third-generation-sequencing-reads</guid>
	<pubDate>Mon, 04 May 2020 02:04:03 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41599/haslr-a-hybrid-assembler-which-uses-both-second-and-third-generation-sequencing-reads</link>
	<title><![CDATA[HASLR: a hybrid assembler which uses both second and third generation sequencing reads]]></title>
	<description><![CDATA[<p><span>HASLR, a hybrid assembler which uses both second and third generation sequencing reads to efficiently generate accurate genome assemblies. Our experiments show that HASLR is not only the fastest assembler but also the one with the lowest number of misassemblies on all the samples compared to other tested assemblers. Furthermore, the generated assemblies in terms of contiguity and accuracy are on par with the other tools on most of the samples. Availability. HASLR is an open source tool available at https://github.com/vpc-ccg/haslr.</span></p><p>Address of the bookmark: <a href="https://github.com/vpc-ccg/haslr" rel="nofollow">https://github.com/vpc-ccg/haslr</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41941/svengine-allele-specific-and-haplotype-aware-structural-variants-simulator</guid>
	<pubDate>Sat, 04 Jul 2020 05:52:34 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41941/svengine-allele-specific-and-haplotype-aware-structural-variants-simulator</link>
	<title><![CDATA[SVEngine: Allele Specific and Haplotype Aware Structural Variants Simulator]]></title>
	<description><![CDATA[<p>SVEngine (Structural Variants Engine)</p>
<ul>
<li>SVEngine is a multi-purpose and self-contained simulator for whole genome scale spike-in of thousands of SV events of various types in both single-sample and matched sample scenarios.</li>
<li>SVEngine takes as input reference contigs in FASTA files, variant meta distribution as specified in META files (see Manual) or specific variant information as specified in VAR files (see Manual) and NEWICK files for specifying clonal phylogenetic trees in cancer.</li>
<li>SVEngine outpus alterred contigs in FASTA files, spiked-in variants in VAR files (see Manual), simulated short read in FASTQ files and aligned short reads in BAM files.</li>
</ul>
<p>&nbsp;</p><p>Address of the bookmark: <a href="https://bitbucket.org/charade/svengine/src/master/" rel="nofollow">https://bitbucket.org/charade/svengine/src/master/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41144/seqmule-automated-human-exomegenome-variants-detection</guid>
	<pubDate>Tue, 18 Feb 2020 03:22:54 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41144/seqmule-automated-human-exomegenome-variants-detection</link>
	<title><![CDATA[SeqMule: Automated human exome/genome variants detection]]></title>
	<description><![CDATA[<p>SeqMule takes single-end or paird-end FASTQ or BAM files, generates a script consisting of more than 10 popular alignment, analysis tools and runs the script line by line. Users can change the pipeline or fine-tune the parameters by modifying its configuration file.</p><p>Address of the bookmark: <a href="https://doc-openbio.readthedocs.io/projects/seqmule/en/latest/" rel="nofollow">https://doc-openbio.readthedocs.io/projects/seqmule/en/latest/</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/17176/arvados</guid>
	<pubDate>Sat, 20 Sep 2014 16:54:21 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/17176/arvados</link>
	<title><![CDATA[Arvados]]></title>
	<description><![CDATA[<p>Arvados is a free and open&nbsp;source bioinformatics&nbsp;platform for genomic and&nbsp;biomedical data. User can&nbsp;Store | Organize | Compute | Share the data for free.&nbsp;</p>
<p><img src="https://arvados.org/images/dax.png" width="400" height="535" alt="image" style="border: 0px;"></p><p>Address of the bookmark: <a href="https://arvados.org/" rel="nofollow">https://arvados.org/</a></p>]]></description>
	<dc:creator>Martin Jones</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/28117/quin%E2%80%99s-web-server</guid>
	<pubDate>Mon, 27 Jun 2016 10:44:16 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/28117/quin%E2%80%99s-web-server</link>
	<title><![CDATA[QuIN’s web server]]></title>
	<description><![CDATA[<p><span>Recent studies of the human genome have indicated that regulatory elements (e.g. promoters and enhancers) at distal genomic locations can interact with each other via chromatin folding and affect gene expression levels. Genomic technologies for mapping interactions between DNA regions, e.g., ChIA-PET and HiC, can generate genome-wide maps of interactions between regulatory elements. These interaction datasets are important resources to infer distal gene targets of non-coding regulatory elements and to facilitate prioritization of critical loci for important cellular functions. With the increasing diversity and complexity of genomic information and public ontologies, making sense of these datasets demands integrative and easy-to-use software tools. Moreover, network representation of chromatin interaction maps enables effective data visualization, integration, and mining. Currently, there is no software that can take full advantage of network theory approaches for the analysis of chromatin interaction datasets. To fill this gap, we developed a web-based application, QuIN, which enables: 1) building and visualizing chromatin interaction networks, 2) annotating networks with user-provided private and publicly available functional genomics and interaction datasets, 3) querying network components based on gene name or chromosome location, and 4) utilizing network based measures to identify and prioritize critical regulatory targets and their direct and indirect interactions.&nbsp;</span></p>
<p><strong>AVAILABILITY:</strong><span>&nbsp;QuIN&rsquo;s web server is available at&nbsp;</span><a href="http://quin.jax.org/">http://quin.jax.org</a><span>&nbsp;QuIN is developed in Java and JavaScript, utilizing an Apache Tomcat web server and MySQL database and the source code is available under the GPLV3 license available on GitHub:</span><a href="https://github.com/UcarLab/QuIN/">https://github.com/UcarLab/QuIN/</a><span>.</span></p><p>Address of the bookmark: <a href="http://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1004809" rel="nofollow">http://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1004809</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

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