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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/19636?offset=910</link>
	<atom:link href="https://bioinformaticsonline.com/related/19636?offset=910" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
	
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/44650/manthey-research-group-%E2%80%93-evolutionary-genomics</guid>
  <pubDate>Thu, 22 Aug 2024 06:25:55 -0500</pubDate>
  <link></link>
  <title><![CDATA[Manthey Research Group – Evolutionary Genomics]]></title>
  <description><![CDATA[
<p>We focus on fundamental questions in genomics, ecology, and evolution. Our methods include fieldwork and labwork, but most of our time is spent analyzing genomics data using computational biology approaches.</p>

<p>Ant / bacteria co-evolution, landscape genomics, and population genomics<br />Vertebrate and/or invertebrate genome evolution</p>

<p>If you might be interested in joining our research group, send an email with your intent and why this group would potentially be a good fit for your future goals along with a CV / Resume to jdmanthey (at) gmail (dot) com</p>

<p>More at https://mantheylab.org/</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/view/1906</guid>
	<pubDate>Sun, 11 Aug 2013 11:13:58 -0500</pubDate>
	<link>https://bioinformaticsonline.com/view/1906</link>
	<title><![CDATA[Compressive Genomics]]></title>
	<description><![CDATA[<p>The key to finding a solution is to notice that most&nbsp;<a href="http://www.i-programmer.info/news/181-algorithms/4537-a-new-dna-sequence-search-compressive-genomics.html">genomic</a>sequences differ by very little. It may well be that the number of complete genome sequences being stored is increasing rapidly, but the actual amount of new data is very small. In other words, a single DNA sequence isn't particularly compressible but a set of sequences shares so much in common that the redundancy can be used to store them in a much smaller storage space. (Source:e-article from&nbsp;Alex Armstrong)</p><p><a href="http://www.i-programmer.info/news/181-algorithms/4537-a-new-dna-sequence-search-compressive-genomics.html">http://www.i-programmer.info/news/181-algorithms/4537-a-new-dna-sequence-search-compressive-genomics.html</a></p><p><a href="http://en.wikipedia.org/wiki/Compression_of_Genomic_Re-Sequencing_Data">http://en.wikipedia.org/wiki/Compression_of_Genomic_Re-Sequencing_Data</a></p><p><a href="http://www.nature.com/nbt/journal/v30/n7/full/nbt.2241.html">http://www.nature.com/nbt/journal/v30/n7/full/nbt.2241.html</a></p><p><a href="http://bioinformatics.oxfordjournals.org/content/29/13/i283.full">http://bioinformatics.oxfordjournals.org/content/29/13/i283.full</a></p><p><a href="http://groups.csail.mit.edu/cb/cast/">http://groups.csail.mit.edu/cb/cast/</a></p>]]></description>
	<dc:creator>Rahul Agarwal</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/26290/webinar-on-streamlining-large-scale-analysis-using-the-strand-ngs-pipeline-manager-on-24-feb-2016</guid>
	<pubDate>Fri, 05 Feb 2016 06:43:28 -0600</pubDate>
	<link>https://bioinformaticsonline.com/news/view/26290/webinar-on-streamlining-large-scale-analysis-using-the-strand-ngs-pipeline-manager-on-24-feb-2016</link>
	<title><![CDATA[Webinar on Streamlining large scale analysis using the Strand NGS Pipeline Manager on 24 Feb 2016]]></title>
	<description><![CDATA[<p><a href="http://www.strand-ngs.com/webinar_registration" title="webinar"><strong>Live Webinar on Streamlining large scale NGS data analysis using the Strand NGS Pipeline Manager on 24 Feb 2016</strong></a></p><p><strong>Abstract:</strong> Strand NGS includes comprehensive workflows for DNA-Seq, RNA-Seq, Small RNA-Seq, ChIP-Seq, MeDIP-Seq, and Methyl-Seq analysis. Each workflow includes a quality assessment and filter section, followed by a workflow-specific analysis section. The pipeline functionality in Strand NGS allows users to execute a sequence of analysis steps with specific parameters - all without any manual intervention. This simplifies the analysis in large scale sequencing projects where every sample needs to be processed identically.</p><p>In this webinar we will discuss the pre-packaged pipelines present in Strand NGS. The packaged pipelines have well-chosen default parameters and are suitable for users analyzing data for the first time in the tool. We will also show how advanced users can customize pipelines and share them with other Strand NGS users. Finally, we will show a brief glimpse of an elaborate pipeline that aligns reads, filters poor-quality matches, computes coverage metrics, identifies variants, checks for sample cross-contamination, and emails quality reports - all from within Strand NGS.</p><p><strong>Speaker:</strong> Dr. Vamsi Veeramachaneni, Vice President - Bioinformatics, Strand Life Sciences</p><p><strong>Details:</strong> Session 1: 2:30 PM IST, Session 2 : 10:30 PM IST<br /><strong>Register here:</strong> http://www.strand-ngs.com/webinar_registration</p><h3>&nbsp;</h3>]]></description>
	<dc:creator>Yeshodari</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/34912/list-of-cancer-genomics-research-web-resources</guid>
	<pubDate>Wed, 27 Dec 2017 20:33:09 -0600</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/34912/list-of-cancer-genomics-research-web-resources</link>
	<title><![CDATA[List of cancer genomics research web resources !]]></title>
	<description><![CDATA[<p>Major web resources for cancer genomics research</p><p>CGHub <br />https://cghub.ucsc.edu/ <br />Comprehensive data repository; huge data size</p><p>EGA <br />https://www.ebi.ac.uk/ega/ <br />Comprehensive data repository; huge data size</p><p>COSMIC <br />http://cancer.sanger.ac.uk <br />Largest somatic mutation database; genome sequencing paper curation</p><p>CPRG <br />http://www.broadinstitute.org/software/cprg <br />Interface for cancer program resources</p><p>GDAC <br />http://gdac.broadinstitute.org/ <br />Data analysis; automatic pipelines; user-friendly reports</p><p>SNP500Cancer <br />http://snp500cancer.nci.nih.gov <br />Sequence and genotype verification of SNPs</p><p>canEvolve <br />www.canevolve.org/ <br />Comprehensive analysis of tumor profile; Data from 90 studies involving more than 10,000 patients</p><p>MethyCancer <br />http://methycancer.psych.ac.cn <br />Relationship among DNA methylation, gene expression and cancer</p><p>SomamiR <br />http://compbio.uthsc.edu/SomamiR/ <br />Correlation between somatic mutation and microRNA; genome-wide displaying</p><p>cBioPortal <br />http://www.cbioportal.org/public-portal/ <br />Graphical summaries; gene alteration; processed data; visualization</p><p>UCSC Cancer Genomics Browser <br />https://genome-cancer.soe.ucsc.edu/ <br />Clinical information; gene expression; copy number variation; visualization</p><p>CGWB <br />https://cgwb.nci.nih.gov/ <br />Visualization; gene mutation and variation; automated analysis pipeline</p><p>GDSC <br />http://www.cancerrxgene.org <br />Drug sensitivity information; drug response information</p><p>canSAR <br />https://cansar.icr.ac.uk/ <br />Multidisciplinary information; drug discovery</p><p>NONCODE <br />http://www.noncode.org/ ncRNAs; <br />lncRNAs; up-to-date and comprehensive resource</p>]]></description>
	<dc:creator>biogeek</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/24462/icar-project-ra-position-institute-of-bioinformatics-iob-bangalore</guid>
  <pubDate>Tue, 22 Sep 2015 23:41:31 -0500</pubDate>
  <link></link>
  <title><![CDATA[ICAR project RA position @ Institute of Bioinformatics (IOB) Bangalore]]></title>
  <description><![CDATA[
<p>Applications are invited for the post of Research Associate (RA) in the ICAR project on "Lactation stress associated postpartum anestrus SNP array in buffaloes". We are looking for a motivated candidate for handling Next Generation sequencing data analysis with a strong background in bioinformatics and programming.</p>

<p>The position is open for immediate appointment and available for two years and then extendable for additional one year. The applicant will be appointed as Research Associate based on qualifications as detailed below:</p>

<p>Research Associate:</p>

<p>-Master’s degree with bioinformatics with at least 2 years of research experience in Next Generation sequencing data analysis as evidence from Fellowship/ Associateship / Training / other engagements.</p>

<p>-Familiarity with bioinformatics tools, database development, programming skills</p>

<p>-Minimum 1 publication in any peer reviewed journal</p>

<p>Salary will be as per ICAR rules and guidelines. Application will be shortlisted based on CV, reference letters from mentors and telephonic interview. Candidates will be called for a personal interview at Bangalore before appointment. No travel expense will be provided for attending interview at Bangalore.</p>

<p>Interested candidates may send a Letter of Interest and CV by email to: keshav@ibioinformatics.org before September 29, 2015.</p>
]]></description>
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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>
</item>
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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>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/43046/postdoctoral-fellow-for-a-large-scale-microbial-comparative-genomics</guid>
  <pubDate>Thu, 29 Apr 2021 08:44:53 -0500</pubDate>
  <link></link>
  <title><![CDATA[postdoctoral fellow for a large-scale microbial comparative genomics !]]></title>
  <description><![CDATA[
<p>Asaf Levy hiring a postdoctoral fellow for a large-scale microbial comparative genomics project at the Hebrew University of Jerusalem (Israel). <br />The project is a continuation of Levy Asaf et al. Nature Genetics 2018 paper.<br />Requirements: <br />1.Experience with programming in at least one programming language, preferably Python.<br />2.A PhD in bioinformatics/computational biology<br />3.At least one first authorship publication in a good journal, preferably more.<br />4.Good communication skills in English <br />5.Ability to enter and study in Israel (not applicable for Pakistani people, for example). <br />6.Ability to work in a team.<br />Please send CV to alevy@mail.huji.ac.il</p>
]]></description>
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<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/24463/project-fellow-at-indian-institute-of-chemical-biology-iicb</guid>
  <pubDate>Tue, 22 Sep 2015 23:47:35 -0500</pubDate>
  <link></link>
  <title><![CDATA[Project Fellow at Indian Institute of Chemical Biology (IICB)]]></title>
  <description><![CDATA[
<p>Advertisement No. : R&amp;C/CD/427/2015  ,Vacancy Code: 4271501    </p>

<p>Project Fellow Bioinformatics recruitment in Indian Institute of Chemical Biology (IICB) purely temporary </p>

<p>Name of the Project:  "Genomics and Informatics Solutions for Integrating Biology(Genesis)".     </p>

<p>No. of Vacancies: 1     </p>

<p>Qualification required : M.Sc in Bioinformatics with 55% Marks. </p>

<p>Experience (Desirable): Candidate should be well versed with sequencing data analysis,assembly and annotation of whole genome sequence. Experience in transcriptional data analysis is also preferred.</p>

<p>Age Limit : 28 Years   <br />  <br />Stipend : Rs.16000<br />How to apply<br />Interested candidates may appear for the walk-in-interview to be held on 28.09.2015 from 11.00 a.m. in the Red Carpet Room with the following documents self attested copy - (1) Matriculation Certificate in support of your date of birth, (2) Degree/Diploma Certificate, (3) Original reprints of all testimonials regarding educational qualification, (4) No Objection Certificate from the employer if employed, (5) Final Mark Sheet of M.Sc. Examination, (6) One Passport size photograph.</p>

<p>http://www.career.iicb.res.in/Recruitment%20Notice.php</p>
]]></description>
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<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44661/lovis4u-locus-visualisation-tool-for-comparative-genomics</guid>
	<pubDate>Tue, 17 Sep 2024 02:30:57 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44661/lovis4u-locus-visualisation-tool-for-comparative-genomics</link>
	<title><![CDATA[LoVis4u: Locus Visualisation tool for comparative genomics]]></title>
	<description><![CDATA[<p dir="auto"><a href="https://github.com/art-egorov/lovis4u/blob/main/docs/img/lovis4u_logo.png" target="_blank"><img src="https://github.com/art-egorov/lovis4u/raw/main/docs/img/lovis4u_logo.png" alt="image" width="300" style="border: 0px; border: 0px;"></a></p>
<div dir="auto">
<h2 dir="auto">Description</h2>
<a href="https://github.com/art-egorov/lovis4u#description"></a></div>
<p dir="auto"><span>LoVis4u</span>&nbsp;is a bioinformatics tool for&nbsp;<span>Lo</span>ci&nbsp;<span>Vis</span>ualisation.</p>
<p dir="auto"><span>LoVis4u, a command-line tool and Python API designed for highly customizable and fast visualisation of multiple genomic loci. LoVis4u generates vector images in PDF format based on annotation data from GenBank or GFF files. It is capable of visualising entire genomes of bacteriophages as well as plasmids and user-defined regions of longer prokaryotic genomes. Additionally, LoVis4u offers optional data processing steps to identify and highlight accessory and core genes in input sequences.</span></p>
<p dir="auto">https://art-egorov.github.io/lovis4u/</p>
<p dir="auto">&nbsp;</p><p>Address of the bookmark: <a href="https://github.com/art-egorov/lovis4u" rel="nofollow">https://github.com/art-egorov/lovis4u</a></p>]]></description>
	<dc:creator>LEGE</dc:creator>
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