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	<link>https://bioinformaticsonline.com/related/27333?offset=430</link>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/videolist/watch/8175/the-future-of-personalized-medicine</guid>
	<pubDate>Thu, 06 Feb 2014 00:21:26 -0600</pubDate>
	<link>https://bioinformaticsonline.com/videolist/watch/8175/the-future-of-personalized-medicine</link>
	<title><![CDATA[The Future of Personalized Medicine]]></title>
	<description><![CDATA[<iframe width="" height="" src="https://www.youtube-nocookie.com/embed/WUQ_qVe9HGQ" frameborder="0" allowfullscreen></iframe>Howard Jacob speaking on Personalize Medicine at the Illumina Meeting in Feb. of 2013.]]></description>
	
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/33903/visiting-scientist-computational-genomics</guid>
  <pubDate>Mon, 17 Jul 2017 07:20:18 -0500</pubDate>
  <link></link>
  <title><![CDATA[Visiting Scientist - Computational Genomics]]></title>
  <description><![CDATA[
<p>ICRISAT is a non-profit, non-political organization that conducts agricultural research for development in Asia and sub-Saharan Africa with a wide array of partners throughout the world. ICRISAT and its partners help empower those living in the semi-arid tropics, especially smallholder farmers, to overcome poverty, hunger, malnutrition and a degraded environment through more efficient and profitable agriculture. </p>

<p>ICRISAT is headquartered in Patancheru near Hyderabad, India, with two regional hubs and five country offices in sub-Saharan Africa. ICRISAT, established in 1972, is a member of the CGIAR Consortium. For more details, see www.icrisat.org.</p>

<p>Job Responsibilities:<br />Planning and execution of different NGS/genomics data analysis<br />Apply, maintain, and support cutting-edge pipelines for the analysis and interpretation of NGS data<br />Analyze large-scale genomic datasets generated internally and through collaboration with others<br />Genome wide analysis- LD analysis, hapmap, genetic map construction and qtl mapping<br />Expression analysis based on RNA-seq, gene ontology and metabolic pathway data<br />Sequence level analysis like gene family analysis, orthology/paralogy etc.<br />Familiarity with genomic and biological information databases<br />Compilation and interpretation of results and writing reports<br />Experience working independently and in a team environment<br />Requirements:</p>

<p>PhD or M.Sc with 2-3 years experience from reputed institute in the area of life science or similar Knowledge in Next Generation Sequencing (NGS) data analysis. Should be familiar with various sequencing platforms. Sound knowledge of genomics and molecular biology is must. Proficient in any one of the programming/scripting in languages: Python, Perl, PHP, R, Shell Scripting. Must be experienced in working on Linux and CLI environment. Ability to work as team as well as independently with minimal support. Fluency in spoken and written English is essential. </p>

<p>NGS techniques like sequence alignment, variant calling based on whole genome re-sequencing and genotyping-by-sequencing (GBS), RNA-Seq/transcriptome analysis<br />Knowledge of various standard NGS related tool<br />Ability to solve complex problems in advanced genomics research areas<br />Ease and interest in working with people from diverse backgrounds<br />Excellent oral/written communication and interpersonal/networking skills<br />General: <br />This position is contract for a period of two years.</p>

<p>How to apply:<br />Applicants should apply on or before 27-July-2017, with latest Curriculum Vitae, and the names and contact information of three references that are knowledgeable about your professional qualifications and work experience. All applications will be acknowledged, however only short listed candidates will be contacted<br />Please CLICK HERE to submit your application. <br />ICRISAT is an equal opportunity employer</p>

<p>http://icrisat.careersitemanager.com/job-listings-Visiting-Scientist-Computational-Genomics-ICRISAT-Hyderabad-Secunderabad-2-to-4-years-060717000278</p>
]]></description>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/12593/visiting-scientist-computational-genomics-two-positions</guid>
  <pubDate>Mon, 07 Jul 2014 22:53:41 -0500</pubDate>
  <link></link>
  <title><![CDATA[Visiting Scientist - Computational Genomics (two positions)]]></title>
  <description><![CDATA[
<p>Scientific/Managerial &amp; International Recruitment</p>

<p>ICRISAT seeks applications from Indian nationals Visiting Scientist-Computational Genomics (2 positions), to be part of a team of Centre of Excellence in Genomics (CEG), (www.icrisat.org/ceg) to work on legume genomics projects.  The positions will be based at ICRISAT’s Headquarters in Patancheru, Hyderabad, India.</p>

<p>ICRISAT is a non-profit, non-political organization that conducts agricultural research for development in Asia and sub-Saharan Africa with a wide array of partners throughout the world. Covering 6.5 million square kilometers of land in 55 countries, the semi-arid tropics is home to over 2 billion people, with 650 million of these are the poorest of the poor. ICRISAT and its partners help empower those living in the semi-arid tropics, especially smallholder farmers, to overcome poverty, hunger, malnutrition and a degraded environment through more efficient and profitable agriculture. ICRISAT is headquartered in Greater Hyderabad, Andhra Pradesh, India and belongs to the Consortium of Centers supported by the Consultative Group on International Agricultural Research (CGIAR).</p>

<p>The Job: Responsibilities for these positions include:</p>

<p>    Analyzing and handling large-scale next generation sequencing DNA and RNA data<br />    Data mining and development of pipelines and troubleshooting<br />    Genome diversity analysis such as SNPs, Indels, Structural Variations, population structure<br />    Genome wide association study (GWAS) related analysis- LD analysis, hapmap and trait mapping<br />    Expression analysis based on RNA-Seq data, annotation, gene ontology and metabolic pathway analysis<br />    Epigenome analysis, small RNA identification<br />    Gene family analysis, sequence level protein analysis, orthology/paralogy and molecular modelling<br />    Compiling and analysis of results, writing reports and research papers</p>

<p>The Person:  Ph.D. or MSc/MTech/PGDCA with two years research experience in Biotechnology, Computational biology, Agricultural/ Plant Biotechnology, Genetics, Molecular Biology or related discipline. Good knowledge of programming/scripting in at least two of following languages: Perl, C, C++, R, Shell Scripting and Python is plus.</p>

<p>How to apply: Please apply latest by 20 July 2014.  The application should include the name of the position applied for, a letter of motivation, a full Curriculum Vita (CV), and the names and contact information of three references that are knowledgeable of the candidate’s professional qualifications and work experience. Technical details and more information about these positions can be obtained from R.K.VARSHNEY@CGIAR.ORG. All applications will be acknowledged, however only short listed candidates will be contacted.</p>

<p>Apply here https://recruit.zoho.com/ats/Portal.na?digest=T642sgLYWZOStExJ77cPrcM*sIMGZETWw4yPxngbmHA-</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34624/teacheng-teaching-engine-for-genomics</guid>
	<pubDate>Wed, 13 Dec 2017 17:55:23 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34624/teacheng-teaching-engine-for-genomics</link>
	<title><![CDATA[TeachEnG: Teaching Engine for Genomics]]></title>
	<description><![CDATA[<p>TeachEnG (pronounced &ldquo;teaching&rdquo;), a <span style="text-decoration: underline;">Teach</span>ing <span style="text-decoration: underline;">En</span>gine for <span style="text-decoration: underline;">G</span>enomics, provides educational games to help students and researchers understand key bioinformatics concepts. The current version includes interactive modules for sequence alignment and phylogenetic tree reconstruction algorithms, with accompanying video tutorials. <br><br> Please contact us via email (knoweng@illinois.edu) if you have any questions or suggestions.&nbsp;</p><p>Address of the bookmark: <a href="http://teacheng.illinois.edu/" rel="nofollow">http://teacheng.illinois.edu/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40955/the-global-alliance-for-genomics-and-health-ga4gh</guid>
	<pubDate>Sat, 08 Feb 2020 07:37:31 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40955/the-global-alliance-for-genomics-and-health-ga4gh</link>
	<title><![CDATA[The Global Alliance for Genomics and Health (GA4GH)]]></title>
	<description><![CDATA[<p>The Global Alliance for Genomics and Health (GA4GH) is a policy-framing and technical standards-setting organization, seeking to enable responsible genomic data sharing within a <a href="https://www.ga4gh.org/genomic-data-toolkit/regulatory-ethics-toolkit/framework-for-responsible-sharing-of-genomic-and-health-related-data/">human rights framework</a>.</p>
<p>GA4GH core funders and sponsors enable our work and allow us to convene the international genomic data sharing community.</p>
<p>https://www.ga4gh.org/</p><p>Address of the bookmark: <a href="https://www.ga4gh.org/" rel="nofollow">https://www.ga4gh.org/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/42470/the-new-corona-variant-has-23-mutations-in-all-which-is-unusually-huge</guid>
	<pubDate>Wed, 23 Dec 2020 03:50:50 -0600</pubDate>
	<link>https://bioinformaticsonline.com/news/view/42470/the-new-corona-variant-has-23-mutations-in-all-which-is-unusually-huge</link>
	<title><![CDATA[The new corona variant has 23 mutations in all, which is unusually huge !]]></title>
	<description><![CDATA[<p>The new SARS-CoV-2 version, B.1.1.7, which was first seen in the third week of September in Kent and Greater London, has since spread to other locations in the UK. According to the COVID-19 Genomics UK Consortium (COG-UK Consortium) that analysed the genome data of the virus and identified the variant, the new variant has been spreading "rapidly" over the last four weeks and has now been detected in other locations in the UK, suggesting further spread of the variant in the region.</p><p><span>According to a<span>&nbsp;</span></span><a href="https://virological.org/t/preliminary-genomic-characterisation-of-an-emergent-sars-cov-2-lineage-in-the-uk-defined-by-a-novel-set-of-spike-mutations/563"><strong><span>preliminary report</span></strong></a><span><span>&nbsp;</span>posted on December 19 by the COG-UK Consortium scientists, as of December 15, 1,623 variant genomes have been sequenced. In a<span>&nbsp;</span></span><a href="https://twitter.com/TheCGPS/status/1340749351803629569"><strong><span>December 21 tweet</span></strong></a><span>, COG-UK Consortium said that it added 2,963 more genome sequences of SARS-CoV-2, of which 942 (32%) belong to the new variant. The Consortium<span>&nbsp;</span></span><a href="https://twitter.com/CovidGenomicsUK/status/1341073233420955654"><strong><span>intends to sequence</span></strong></a><span><span>&nbsp;</span>20,000 more SARS-CoV-2 genomes in the next two weeks to further ascertain the spread of the variant.</span></p><p><span>There is no clear proof, at least not yet, that it does cause severe pandemic. But there is a justification for seriously taking the possibility. Another coronavirus lineage in South Africa has acquired one specific mutation that is also present in B.1.1.7. This variant is increasingly spreading across South Africa's coastal regions. And doctors have observed in preliminary research that individuals infected with this variant bear a higher viral load-a higher concentration of the virus in their upper respiratory tract. In many viral diseases, this is associated with more severe symptoms.</span></p><p>&nbsp;</p>]]></description>
	<dc:creator>Shruti Paniwala</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/12896/inspire-faculty-scheme-a-component-of-%E2%80%9Cassured-opportunity-for-research-career-aorc%E2%80%9D-under-inspire</guid>
  <pubDate>Sat, 19 Jul 2014 14:59:30 -0500</pubDate>
  <link></link>
  <title><![CDATA[INSPIRE Faculty Scheme: a component of “Assured Opportunity for Research Career (AORC)” under INSPIRE.]]></title>
  <description><![CDATA[
<p>Ministry of Science and Technology, Department of Science and Technology</p>

<p>7th ADVERTISEMENT – 2014 (2)</p>

<p>INSPIRE Faculty Scheme: a component of “Assured Opportunity for Research Career (AORC)” under INSPIRE.</p>

<p>The Department of Science and Technology, Government of India, has launched the “Innovation in Science Pursuit for Inspired Research (INSPIRE)” [http://www.inspire-dst.gov.in] program in 2008.</p>

<p>The program aims to attract talent for study of science and careers with research. INSPIRE includes many components. The importance of Assured Career Opportunity in R&amp;D sector has been recognized.</p>

<p>INSPIRE Faculty Scheme opens up an “Assured Opportunity for Research Career (AORC)” for young researchers in the age group of 27-32 years. It offers a contractual research awards to young achievers and opportunity for independent research in the near term and emerge as a future leader in the long term.</p>

<p>Eligibility</p>

<p>Essential Indian citizens and people of Indian origin including NRI/PIO status with PhD (in science, mathematics, engineering, pharmacy, medicine, and agriculture related subjects) from any recognized university in the world,</p>

<p>Those who have submitted their PhD Theses and are awaiting award of the degree are also<br />eligible. However, the award will be conveyed only after confirmation of the awarding the<br />PhD degree.</p>

<p>The upper age limit as on 1st July 2014 should be 32 years for considering support for a<br />period of 5 years. However, for SC and ST candidates, upper age limit will be 35 years.</p>

<p>Publication(s) in highly reputed Journals demonstrating research potential of the candidate.</p>

<p>Desirable</p>

<p>Candidates who are within top 1% at the School Leaving Examination, IIT-JEE rank, 1st Rank Holder either in graduation or post-graduation level university examination (which are used presently for identifying INSPIRE Scholars at under-graduate level and INSPIRE Fellows for doctoral degree)</p>

<p>More at http://www.inspire-dst.gov.in/faculty_scheme.html</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43362/machine-learning-for-genomics</guid>
	<pubDate>Thu, 09 Sep 2021 11:26:32 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43362/machine-learning-for-genomics</link>
	<title><![CDATA[Machine Learning for Genomics]]></title>
	<description><![CDATA[<h3>Module 1: Statistics for genomics (2-8 August 2021)</h3>
<ul>
<li>A simple intro to statistical distributions</li>
<li>hypothesis testing</li>
<li>linear models.</li>
</ul>
<p>reading:&nbsp;<a href="http://compgenomr.github.io/book/stats.html">http://compgenomr.github.io/book/stats.html</a></p>
<p>slides:&nbsp;<a href="https://github.com/BIMSBbioinfo/compgen2021/tree/main/week1/compgen2021_stats.pdf">https://github.com/BIMSBbioinfo/compgen2021/tree/main/week1/compgen2021_stats.pdf</a></p>
<p>exercises+code:&nbsp;<a href="https://github.com/BIMSBbioinfo/compgen2021/tree/main/week1/">https://github.com/BIMSBbioinfo/compgen2021/tree/main/week1/</a></p>
<h3><a href="https://github.com/BIMSBbioinfo/compgen2021#module-2-unsupervised-learning-for-genomics-9-15-august-2021"></a>Module 2: Unsupervised learning for genomics (9-15 August 2021)</h3>
<ul>
<li>Understanding basic intuition behind machine learning approaches.</li>
<li>Using unsupervised learning to cluster and visualise data points</li>
<li>Dimension reduction techniques for visualisation and as input to clustering methods</li>
</ul>
<p>reading:&nbsp;<a href="http://compgenomr.github.io/book/unsupervisedLearning.html">http://compgenomr.github.io/book/unsupervisedLearning.html</a></p>
<p>slides:&nbsp;<a href="https://github.com/BIMSBbioinfo/compgen2021/tree/main/week2/compgen2021_unsupervisedLearning.pdf">https://github.com/BIMSBbioinfo/compgen2021/tree/main/week2/compgen2021_unsupervisedLearning.pdf</a></p>
<p>exercises+code:&nbsp;<a href="https://github.com/BIMSBbioinfo/compgen2021/tree/main/week2/">https://github.com/BIMSBbioinfo/compgen2021/tree/main/week2/</a></p>
<h3><a href="https://github.com/BIMSBbioinfo/compgen2021#module-3-supervised-learning-for-genomics-16-22-august-2021"></a>Module 3: Supervised learning for genomics (16-22 August 2021)</h3>
<ul>
<li>Understanding and using supervised learning methods for predictive purposes</li>
<li>How to measure prediction performance</li>
<li>Understand and use cross-validation and related concepts</li>
</ul>
<p>reading:&nbsp;<a href="http://compgenomr.github.io/book/supervisedLearning.html">http://compgenomr.github.io/book/supervisedLearning.html</a></p>
<p>slides:&nbsp;<a href="https://github.com/BIMSBbioinfo/compgen2021/tree/main/week3/compgen2021_supervisedLearning.pdf">https://github.com/BIMSBbioinfo/compgen2021/tree/main/week3/compgen2021_supervisedLearning.pdf</a></p>
<p>exercises+code:&nbsp;<a href="https://github.com/BIMSBbioinfo/compgen2021/tree/main/week3/">https://github.com/BIMSBbioinfo/compgen2021/tree/main/week3/</a></p>
<p>https://github.com/BIMSBbioinfo/compgen2021</p><p>Address of the bookmark: <a href="https://github.com/BIMSBbioinfo/compgen2021" rel="nofollow">https://github.com/BIMSBbioinfo/compgen2021</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

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  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/44639/the-sheppard-lab</guid>
  <pubDate>Fri, 09 Aug 2024 02:48:34 -0500</pubDate>
  <link></link>
  <title><![CDATA[The Sheppard Lab]]></title>
  <description><![CDATA[
<p>Ineos Oxford Institute of Antimicrobial Research – Department of Biology – University of Oxford</p>

<p>Our research centres on the use of genetics/genomics and phenotypic studies to address complex questions in the ecology, epidemiology and evolution of microbes. Our most recent interest focuses upon comparative genome analysis to describe the core and flexible genome of pathogenic bacteria (Campylobacter, Acinetobacter, Escherichia coli, Helicobacter, Staphylococcus and Streptococcus suis) and how this is related to population genetic structuring, the maintenance of species, and the evolution of host/niche adaptation and virulence.</p>

<p>More at https://sheppardlab.com/research/</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/11603/ncbi-webinar</guid>
	<pubDate>Sun, 08 Jun 2014 02:47:01 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/11603/ncbi-webinar</link>
	<title><![CDATA[NCBI Webinar]]></title>
	<description><![CDATA[<p>In less than two weeks, NCBI will offer a webinar entitled "Introducing 3 NCBI Resources to Navigate Testing for Disease Linked Variants: MedGen, GTR and ClinVar". This webinar will delve into the lifecycle of genetic testing and teach attendees how to navigate the NIH Genetic Testing Registry, ClinVar, and MedGen resources. These resources can be used to prepare for clinical cases, access detailed information about orderable genetic tests, interpret test results, and more.</p><p>More at https://attendee.gotowebinar.com/register/8452228815737989634</p>]]></description>
	<dc:creator>Jit</dc:creator>
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