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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/29343?offset=290</link>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/34375/the-10th-north-east-bioinformatics-network-nebinet-annual-coordinators-meet</guid>
	<pubDate>Sat, 18 Nov 2017 15:02:44 -0600</pubDate>
	<link>https://bioinformaticsonline.com/news/view/34375/the-10th-north-east-bioinformatics-network-nebinet-annual-coordinators-meet</link>
	<title><![CDATA[The 10th North East Bioinformatics Network (NEBINet) Annual Coordinators' Meet]]></title>
	<description><![CDATA[<p>The 10th North East Bioinformatics Network (NEBINet) Annual Coordinators' Meet organised by the Bioinformatics Centre, St Edmund's College, Shillong and sponsored by the Department of Biotechnology, Government of India, was held at St Edmund's College Auditorium here on Thursday. Meghalaya Governor Ganga Prasad graced the inaugural programme as chief guest. <br />In his inaugural address, the Governor said the panorama of scientific scenario has greatly changed over the years, the thrust areas have undergone a metamorphosis but the conceptual underpinning of the basic sciences still continues. <br />"Of late, the activity of basic research has been intricately intertwined with technology. And we are determined to carry forward this change, for it is through technology that science can actually reach the masses in our country and afar, and the changing times have also inculcated a culture of cross-departmental and interdisciplinary research. Science and technology has always played a pivotal role in taking a nation towards greater heights by ways of innovations and inventions," he added. <br />Prasad also hoped that discussions, suggestions and sharing of innovative ideas during the two-day 10th NEBINet Annual Coordinators' Meet will open up new avenues to make substantial advancement in Biological Sciences which will provide a platform for proper and effective delivery mechanism for the common man. <br />During the inaugural function, Advisor of Department of Biotechnology Dr T Madhan Mohan gave an overview of the NEBINet and Bioinformatics programme. <br />President of Epygen Biotech FZ LLC, Dubai, UAE, Dr Debayan Ghosh, delivered the keynote address. <br />St Edmund's College governing body secretary Brother Simon Coelho and St Edmund's College Principal Dr Sylvanus Lamare also spoke during the function.</p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/35125/eugene-v-koonin-lab</guid>
  <pubDate>Tue, 09 Jan 2018 05:01:15 -0600</pubDate>
  <link></link>
  <title><![CDATA[Eugene V. Koonin Lab]]></title>
  <description><![CDATA[
<p>Interested in understanding the evolution of life. To obtain glimpses of such understanding, we employ existing and new methods of computational biology to perform research in several major areas.</p>

<p>https://www.ncbi.nlm.nih.gov/research/groups/koonin/</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37230/navigator-network-analysis-visualization-and-graphing-toronto</guid>
	<pubDate>Tue, 03 Jul 2018 05:05:55 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37230/navigator-network-analysis-visualization-and-graphing-toronto</link>
	<title><![CDATA[NAViGaTOR: Network Analysis, Visualization and Graphing Toronto]]></title>
	<description><![CDATA[NAViGaTOR –  Network Analysis, Visualization, &amp; Graphing TORonto is a software system for scaleable visualizing and analyzing networks.

The current version, NAViGaTOR 3, increases modularity, improves scaleability, extends input/output options, brings new network views and analysis algorithms.

http://142.150.188.236/navigatorwp/<p>Address of the bookmark: <a href="http://142.150.188.236/navigatorwp/" rel="nofollow">http://142.150.188.236/navigatorwp/</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/40248/industrial-training-in-computer-aided-drug-designing-cadd</guid>
	<pubDate>Wed, 13 Nov 2019 05:00:44 -0600</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/40248/industrial-training-in-computer-aided-drug-designing-cadd</link>
	<title><![CDATA[Industrial Training in Computer Aided Drug Designing (CADD)]]></title>
	<description><![CDATA[<p>Learn More about&nbsp; Computer Aided Drug Designing (CADD)!!!</p><p>#rasalsi #rasa In our Industrial program you will get Knowledge on RNA Seq, CHIP Seq,</p><h2 style="text-align: center;"><strong>Batch Starts From 18<sup>th</sup> November 2019</strong></h2><p>#hurryup #registernow #enquirenow The primary goal of the industrial training program is to provide students with necessary skills making with employable. RASA LSI trains students with the enhanced skills required for them to excel in jobs in biotechnology, pharmaceuticals, BioIT and related industry sectors. At Rasa you will&nbsp; learn from industry leaders&nbsp;how to apply these skills in life science &amp; have a command over software developing process &nbsp;by using various methodologies. For Registration visit us on: https://www.rasalsi.com/index.php/front-page/industrial-training/</p>]]></description>
	<dc:creator>RASA Life Sciences</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34715/delta-a-new-web-based-3d-genome-visualization-and-analysis-platform</guid>
	<pubDate>Wed, 20 Dec 2017 08:49:55 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34715/delta-a-new-web-based-3d-genome-visualization-and-analysis-platform</link>
	<title><![CDATA[Delta: a new Web-based 3D genome visualization and analysis platform]]></title>
	<description><![CDATA[<p><em>Delta</em><span>&nbsp;is an integrative visualization and analysis platform to facilitate visually annotating and exploring the 3D physical architecture of genomes.&nbsp;</span><em>Delta</em><span>&nbsp;takes Hi-C or ChIA-PET contact matrix as input and predicts the topologically associating domains and chromatin loops in the genome. It then generates a physical 3D model which represents the plausible consensus 3D structure of the genome.&nbsp;</span><em>Delta</em><span>features a highly interactive visualization tool which enhances the integration of genome topology/physical structure with extensive genome annotation by juxtaposing the 3D model with diverse genomic assay outputs.</span></p>
<p>https://github.com/zhangzhwlab/delta</p><p>Address of the bookmark: <a href="https://github.com/zhangzhwlab/delta" rel="nofollow">https://github.com/zhangzhwlab/delta</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/41041/post-doc-computational-biology-bioinformatics-network-biology-data-science-ngs-mfd</guid>
  <pubDate>Sat, 15 Feb 2020 06:13:35 -0600</pubDate>
  <link></link>
  <title><![CDATA[Post Doc Computational Biology, Bioinformatics - Network Biology &amp; Data Science, NGS (m/f/d)]]></title>
  <description><![CDATA[
<p>https://www.jobvector.de/jobs-stellenangebote/biologie-life-sciences/forschung-entwicklung/post-doc-computational-biology-bioinformatics-network-biology-data-science-ngs-129867.html?suid=e522e9793b41817e52ac58d6963b94e2519920df</p>

<p>Requirements<br />Doctoral degree in Bioinformatics, Computational Biology, (Bio)physics/-mathematics, Biochemistry/Biology or similar with strong quantitative and numeric focus<br />Ability to numerically process complex and large data sets<br />Good programming skills (R/Bioconductor and/or Python preferred, Linux is a plus)<br />Experience in analyzing next-generation sequencing data sets using network biology<br />Scientific publication record in applied bioinformatics<br />Familiarity with single cell NGS analyses and other –omics techniques is a plus, but not essential</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/35384/mgcv-the-microbial-genomic-context-viewer-for-comparative-genome-analysis</guid>
	<pubDate>Mon, 29 Jan 2018 04:55:46 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/35384/mgcv-the-microbial-genomic-context-viewer-for-comparative-genome-analysis</link>
	<title><![CDATA[MGcV: the microbial genomic context viewer for comparative genome analysis]]></title>
	<description><![CDATA[<p><span>MGcV is an interactive web-based visalization tool tailored to facilitate small scale genome analysis. To start using MGcV:</span></p>
<ol>
<li>Supply your genes/genomic segments/phylogenetic tree of interest in the input-box by
<ul>
<li>selecting the type of identifier and pasting identifiers (one per line)</li>
<li><em><strong>or</strong></em>&nbsp;by using the&nbsp;<a>gene ID search tool</a></li>
<li><em><strong>or</strong></em>&nbsp;with the&nbsp;<a>BLAST search tool</a></li>
</ul>
</li>
<li>Click "Visualize context".</li>
</ol>
<p><span>Consult the&nbsp;</span><a href="http://mgcv.cmbi.ru.nl/help.html" target="_blank">documentation</a><span>&nbsp;to learn more about MGcV.</span></p><p>Address of the bookmark: <a href="http://mgcv.cmbi.ru.nl/" rel="nofollow">http://mgcv.cmbi.ru.nl/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40611/deepvariant-an-analysis-pipeline-that-uses-a-deep-neural-network-to-call-genetic-variants-from-next-generation-dna-sequencing-data</guid>
	<pubDate>Sat, 25 Jan 2020 13:28:09 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40611/deepvariant-an-analysis-pipeline-that-uses-a-deep-neural-network-to-call-genetic-variants-from-next-generation-dna-sequencing-data</link>
	<title><![CDATA[DeepVariant : an analysis pipeline that uses a deep neural network to call genetic variants from next-generation DNA sequencing data.]]></title>
	<description><![CDATA[<p><span>DeepVariant is an analysis pipeline that uses a deep neural network to call genetic variants from next-generation DNA sequencing data.</span></p>
<p><span><span>DeepVariant is an analysis pipeline that uses a deep neural network to call genetic variants from next-generation DNA sequencing data. DeepVariant relies on&nbsp;</span><a href="https://github.com/google/nucleus">Nucleus</a><span>, a library of Python and C++ code for reading and writing data in common genomics file formats (like SAM and VCF) designed for painless integration with the&nbsp;</span><a href="https://www.tensorflow.org/">TensorFlow</a><span>&nbsp;machine learning framework.</span></span></p>
<p><span><a href="https://ai.googleblog.com/2017/12/deepvariant-highly-accurate-genomes.html">https://ai.googleblog.com/2017/12/deepvariant-highly-accurate-genomes.html</a></span></p>
<p><span><a href="https://www.biorxiv.org/content/10.1101/092890v6">https://www.biorxiv.org/content/10.1101/092890v6</a></span></p>
<p><span><img src="https://4.bp.blogspot.com/-2KlXZO60sWE/WiGc8qlZfxI/AAAAAAAACOs/s1pNiKI8jsAvJLr1E_po5udDO8eObm_awCLcBGAs/s640/image3.png" width="640" height="427" alt="image" style="border: 0px;"></span></p><p>Address of the bookmark: <a href="https://github.com/google/deepvariant" rel="nofollow">https://github.com/google/deepvariant</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44472/pipesnake-bioinformatics-best-practice-analysis-pipeline-for-phylogenomic-reconstruction</guid>
	<pubDate>Wed, 21 Feb 2024 06:19:41 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44472/pipesnake-bioinformatics-best-practice-analysis-pipeline-for-phylogenomic-reconstruction</link>
	<title><![CDATA[pipesnake: bioinformatics best-practice analysis pipeline for phylogenomic reconstruction]]></title>
	<description><![CDATA[<p dir="auto"><span>ausarg/pipesnake</span>&nbsp;is a bioinformatics best-practice analysis pipeline for phylogenomic reconstruction starting from short-read 'second-generation' sequencing data.</p>
<p dir="auto">The pipeline is built using&nbsp;<a href="https://www.nextflow.io/">Nextflow</a>, a workflow tool to run tasks across multiple compute infrastructures in a very portable manner. It uses Docker/Singularity containers making installation trivial and results highly reproducible. The&nbsp;<a href="https://www.nextflow.io/docs/latest/dsl2.html">Nextflow DSL2</a>&nbsp;implementation of this pipeline uses one container per process which makes it much easier to maintain and update software dependencies.</p><p>Address of the bookmark: <a href="https://github.com/AusARG/pipesnake" rel="nofollow">https://github.com/AusARG/pipesnake</a></p>]]></description>
	<dc:creator>LEGE</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/43292/bioinformatics-scientist-production-bioinformatics-south-san-francisco-ca</guid>
  <pubDate>Thu, 19 Aug 2021 08:45:24 -0500</pubDate>
  <link></link>
  <title><![CDATA[Bioinformatics Scientist, Production Bioinformatics @ South San Francisco, CA]]></title>
  <description><![CDATA[
<p>wist is looking for a Bioinformatics Scientist to join our Production Bioinformatics Team. You will work alongside research scientists, software engineers and data scientists to further deliver on our mission to expand access to best-in-class synthetic biology and next-generation sequencing applications. You will be developing and engineering tools to better evaluate and build hardened, production quality pipelines, optimize data quality, and automate lab and bioinformatics processes. Our ideal candidate is an organized problem solver with a background in developing and building novel production-quality bioinformatics tools and packages. Equally excellent communication skills and a proven ability to work independently are required.</p>

<p>More at https://boards.greenhouse.io/twistbioscience/jobs/3135495?gh_src=9ecc0b941us</p>
]]></description>
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