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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/43243?offset=120</link>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/32730/ncbi-prokaryotic-genome-annotation-pipeline</guid>
	<pubDate>Tue, 16 May 2017 08:56:03 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/32730/ncbi-prokaryotic-genome-annotation-pipeline</link>
	<title><![CDATA[NCBI Prokaryotic Genome Annotation Pipeline]]></title>
	<description><![CDATA[<p>NCBI Prokaryotic Genome Annotation Pipeline is designed to annotate bacterial and archaeal genomes (chromosomes and plasmids).</p>
<p>Genome annotation is a multi-level process that includes prediction of protein-coding genes, as well as other functional genome units such as structural RNAs, tRNAs, small RNAs, pseudogenes, control regions, direct and inverted repeats, insertion sequences, transposons and other mobile elements.</p>
<p>NCBI has developed an automatic prokaryotic genome annotation pipeline that combines&nbsp;<em>ab initio</em>&nbsp;gene prediction algorithms with homology based methods. The first version of NCBI Prokaryotic Genome Automatic Annotation Pipeline (PGAAP;&nbsp;<a href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&amp;db=pubmed&amp;dopt=Abstract&amp;list_uids=18416670">see Pubmed Article</a>) developed in 2005 has been replaced with an upgraded version that is capable of processing a larger data volume. You can find a more detailed description of the new version of&nbsp;the pipeline in&nbsp;<a href="https://www.ncbi.nlm.nih.gov/books/NBK174280/">NCBI Handbook chapter</a>. NCBI's annotation pipeline depends on several internal databases and is not currently available for download or use outside of the NCBI environment.</p>
<p>https://www.ncbi.nlm.nih.gov/genome/annotation_prok/</p><p>Address of the bookmark: <a href="https://www.ncbi.nlm.nih.gov/genome/annotation_prok/" rel="nofollow">https://www.ncbi.nlm.nih.gov/genome/annotation_prok/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/1469/prime-minister%E2%80%99s-100k-genome-project</guid>
	<pubDate>Thu, 08 Aug 2013 09:40:39 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/1469/prime-minister%E2%80%99s-100k-genome-project</link>
	<title><![CDATA[Prime Minister’s 100k Genome Project]]></title>
	<description><![CDATA[<p>Genomics Ebgland is destined to sequence 100,000 patients over the next five year in England.&nbsp; A landmark project by british government.</p><p>Genomics England will play a key role in building on the UK&rsquo;s long track record as leader in medical science advances to push the boundaries by unlocking the power of DNA data. The UK will become the first ever country to introduce this technology in its mainstream health system &ndash; leading the global race for better tests, better drugs and above all better, more personalised care.</p><p>http://www.genomicsengland.co.uk/100k-genome-project/</p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/33794/senior-bioinformatics-software-developer-hyderabad-telangana</guid>
  <pubDate>Mon, 03 Jul 2017 10:10:31 -0500</pubDate>
  <link></link>
  <title><![CDATA[Senior Bioinformatics Software Developer, Hyderabad, Telangana]]></title>
  <description><![CDATA[
<p>DuPont Pioneer is the world leader in plant biotechnology area including discovery, development and delivery of elite crop genetics. DuPont Pioneer is aggressively building Big Data and Predictive Analytics capabilities in order to deliver improved services to our customers. We are currently seeking Senior Bioinformatics Software Developer at the DuPont Knowledge Center in Hyderabad, India for our global Data Science and Informatics group. At DuPont Pioneer, you’ll become part of a work environment that nurtures your interests, ignites your passion, creates opportunities to serve and helps you attain success–both personally and professionally. The hiring level will be commensurate with the level of experience. This is a critical position with the potential to make immediate, significant impact on our business.<br />The successful candidate will have an extensive background in computer science and bioinformatics through courses or academic degrees, and proven experience in bioinformatics software development. We are looking for those creative, smart, model driven, agile individuals who enjoy giving their all to tackle diverse software needs.<br />Duties / Responsibilities</p>

<p>Job Qualifications<br />Education and Experience<br />•	Master Degree in Bioinformatics, Computational biology, Scientific Computing or related field <br />•	3-5 years of Post-Master’s experience in Bioinformatics software development <br />•	Proven experience developing high throughput bioinformatics applications<br />Required Competencies<br />•	Strong proven experience in Python programming language in Linux environment<br />•	Proven High Performance computing experience (LSF/SGE/OGE)<br />•	Exposure in code versioning and repository management (GIT/SVN)<br />•	Proven experience in Bioinformatics algorithm development<br />•	Deep understanding in Bioinformatics tools, data types<br />Desired Competencies<br />•	Familiarity working in a scientific computing environment (NumPy, SciPy, Pandas etc.)<br />•	Familiarity working with Cloud technologies (AWS, Azure)<br />•	Ability to demonstrate solid analytical skills and exceptional attention to detail.<br />•	Experience in relational databases and data structures<br />•	Proven experience working with teams using agile software development methodologies and processes<br />•	Familiarity with Service Oriented Architecture (SOA)<br />•	Familiarity with build tools (Jenkins, make, ANT, Maven)<br />•	Exposure to project management tools (JIRA, Confluence, RED MINE, etc.)</p>

<p>More at http://careers.dupont.com/jobsearch/job-details/senior-bioinformatics-software-developer/012939W-01/</p>
]]></description>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/1491/2013-nextgen-genomics-bioinformatics-technologies-ngbt-conference-new-delhi-india</guid>
  <pubDate>Thu, 08 Aug 2013 16:21:16 -0500</pubDate>
  <link></link>
  <title><![CDATA[2013 NextGen Genomics &amp; Bioinformatics Technologies (NGBT) Conference, New Delhi, INDIA]]></title>
  <description><![CDATA[
<p>2013 NextGen Genomics &amp; Bioinformatics Technologies (NGBT) Conference</p>

<p>SciGenom Research Foundation (SGRF) and Institute of Genomics and Integrative Biology (IGIB) are pleased to host the Next-Generation Sequencing and Bioinformatics for Genomics &amp; Healthcare conference.</p>

<p>In the ten years since the first human reference genome was completed for US$3 billion the sequencing technologies have radically changed leading to great reduction in sequencing cost. Today a human genome can be sequenced for under US$ 5000 in less than two weeks. It is expected that by the end of 2015 the cost of sequencing a human genome will drop to below thousand dollars. The next generation sequencing technologies over the past five years have enabled a large number of genomic studies that impact human health and disease. Also, this has made possible the growth of microbial, animal and plant genomics studies. While the data production has increased at a rapid pace challenges remain in analyzing and understanding the data. The conference will cover the next generation sequencing (NGS) technologies, bioinformatics for NGS and applications of NGS in many areas including personalized medicine.</p>

<p>For more info : http://www.scigenomconferences.com/2013/default.php</p>
]]></description>
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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>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/1720/postdoctoral-associate-bioinformatics-at-duke-university-medical-center</guid>
  <pubDate>Sat, 10 Aug 2013 18:38:38 -0500</pubDate>
  <link></link>
  <title><![CDATA[Postdoctoral Associate - Bioinformatics  at Duke University Medical Center]]></title>
  <description><![CDATA[
<p>The Department of Biostatistics and Bioinformatics at Duke University Medical Center is seeking a Postdoctoral Associate for a one year appointment to work on several high-dimensional research projects. The specific goals of the project are to identify genes or molecular markers that are predictive of clinical outcomes in renal and prostate cancer.</p>

<p>Candidates must have: a PhD degree in statistics, biostatistics or bioinformatics, extensive experience in analyzing high-dimensional data (microarray, SNP, CNVs) and of validation approaches. In addition, experience in penalized regression methods, data base manipulation; and strong programming skills in order to conduct Monte Carlo studies and applications (R). Candidate must have excellent communication skills (verbal, written and presentation), a strong proficiency in Linux system.</p>

<p>This position is available immediately and will be filled as soon as possible. Appointment could be extended beyond the first year based on additional funding.</p>

<p>For more information about the Department of Biostatistics and Bioinformatics, please visit our website: http://www.biostat.duke.edu.</p>

<p>For more info: http://biostat.duke.edu/sites/biostat.duke.edu/files/Halabi%20-%20Postdoc%20Job%20Posting%202013%20updated.pdf</p>

<p>Duke University is an Equal Opportunity/Affirmative Action Employer.</p>
]]></description>
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<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/34916/bioinformatics-tools-developed-for-oxford-nanopore-data-analysis</guid>
	<pubDate>Wed, 27 Dec 2017 20:47:30 -0600</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/34916/bioinformatics-tools-developed-for-oxford-nanopore-data-analysis</link>
	<title><![CDATA[Bioinformatics tools developed for Oxford Nanopore data analysis !]]></title>
	<description><![CDATA[<p><span>MinION is the only portable real-time device for DNA and RNA&nbsp;</span><span>sequencing</span><span>. Each consumable flow cell can now generate 10&ndash;20 Gb of DNA&nbsp;</span><span>sequence</span><span>&nbsp;data. Ultra-</span><span>long read lengths are possible (hundreds of kb) as you can choose your fragment length.&nbsp;</span>One of the technical advantages of ONT data is the read length, which offers great prospects for genome assembly. Generally, assemblers are based on several different types of algorithms, such as greedy, overlap-layout-consensus (OLC), de Bruijn graph (DBG), and string graph.</p><p><span>List of analysis tools developed for Oxford Nanopore data</span></p><p>BWA <br />Fast nanopore data tuned alignment tool <br />https://github.com/lh3/bwa</p><p>GraphMap<br />Mapper for long and error-prone reads<br />https://github.com/isovic/graphmap</p><p>LAST<br />Nanopore tuned alignment tool<br />http://last.cbrc.jp/</p><p>LINKS<br />Software tool for long read scaffolding <br />https://github.com/warrenlr/LINKS/</p><p>marginAlign<br />Tools to align nanopore reads to a reference<br />https://github.com/benedictpaten/marginAlign</p><p>minoTour<br />Real time analysis tools<br />http://minotour.nottingham.ac.uk/</p><p>nanoCORR<br />Error-correction tool for nanopore sequence data<br />https://github.com/jgurtowski/nanocorr</p><p>NanoOK<br />Software for nanopore data, quality and error profiles<br />https://documentation.tgac.ac.uk/display/NANOOK/NanoOK</p><p>Nanopolish<br />Nanopore analysis and genome assembly software<br />https://github.com/jts/nanopolish</p><p>nanopore<br />Variant-detection tool for nanopore sequence data<br />https://github.com/mitenjain/nanopore</p><p>Nanocorrect<br />Error-correction tool for nanopore sequence data<br />https://github.com/jts/nanocorrect/</p><p>npReader<br />Real-time conversion and analysis of nanopore reads<br />https://github.com/mdcao/npReader</p><p>poRe<br />Tool for analyzing and visualizing nanopore data<br />https://sourceforge.net/p/rpore/wiki/Home/</p><p>PoreSeq<br />Error-correction and variant-calling software<br />https://github.com/tszalay/poreseq</p><p>Poretools<br />Nanopore sequence analysis and visualization software <br />https://github.com/arq5x/poretools</p><p>SSPACE-LongRead<br />Genome scaffolding tool <br />http://www.baseclear.com/genomics/bioinformatics/basetools/SSPACE-longread</p><p>SMIS<br />Genome scaffolding tool <br />https://sourceforge.net/projects/phusion2/files/smis/</p><p>&nbsp;</p><p>List of assemblers for Oxford Nanopore MinION long reads</p><p>LQS<br />DALIGNER, Celera OLC Nanocorrect, <br />Nanopolish corrector<br />https://github.com/jts/nanopolish</p><p>PBcR<br />HGAP or BLASR, Celera OLC <br />PBcR corrector<br />http://wgs-assembler.sourceforge.net/wiki/index.php/PBcR<br /> &ndash;<br />Canu<br />MHAP, Celera OLC <br />Canu corrector<br />https://github.com/marbl/canu</p><p>Falcon<br />String graph, Celera OLC <br />Falcon corrector<br />https://github.com/PacificBiosciences/falcon</p><p>Miniasm <br />OLC<br />https://github.com/lh3/miniasm</p><p>ra-integrate<br />OLC<br />https://github.com/mariokostelac/ra-integrate/</p><p>ALLPATHS-LG<br />de Bruijn graph <br />ALLPATHS-L corrector<br />https://www.broadinstitute.org/software/allpaths-lg/blog/?page_id=12</p><p>SPAdes <br />de Bruijn graph <br />SPAdes corrector<br />http://bioinf.spbau.ru/spades</p>]]></description>
	<dc:creator>biogeek</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/view/2021</guid>
	<pubDate>Mon, 12 Aug 2013 09:27:57 -0500</pubDate>
	<link>https://bioinformaticsonline.com/view/2021</link>
	<title><![CDATA[What are the difference between BioRuby and BioGem?]]></title>
	<description><![CDATA[<p>I came across two diferent but matching term BioRuby and BioGem. What are the difference between these two term? If both are using same Ruby language for development then why did they develope two different biological packages.</p>]]></description>
	<dc:creator>Neel</dc:creator>
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<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/35552/the-brent-lab</guid>
  <pubDate>Fri, 09 Feb 2018 10:55:27 -0600</pubDate>
  <link></link>
  <title><![CDATA[The Brent Lab]]></title>
  <description><![CDATA[
<p>The Brent Lab is developing and applying computational methods for mapping gene regulation networks, modeling them quantitatively, and engineering new behaviors into them.</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/videolist/watch/4090/computational-biology-in-the-21st-century-making-sense-out-of-massive-data</guid>
	<pubDate>Thu, 29 Aug 2013 08:32:26 -0500</pubDate>
	<link>https://bioinformaticsonline.com/videolist/watch/4090/computational-biology-in-the-21st-century-making-sense-out-of-massive-data</link>
	<title><![CDATA[Computational Biology in the 21st Century: Making Sense out of Massive Data]]></title>
	<description><![CDATA[<iframe width="" height="" src="https://www.youtube-nocookie.com/embed/I99UiA_vaJQ" frameborder="0" allowfullscreen></iframe>Computational Biology in the 21st Century: Making Sense out of Massive Data    
    
Air date:  Wednesday, February 01, 2012, 3:00:00 PM
Category:  Wednesday Afternoon Lectures  
 
Description:  The last two decades have seen an exponential increase in genomic and biomedical data, which will soon outstrip advances in computing power to perform current methods of analysis. Extracting new science from these massive datasets will require not only faster computers; it will require smarter algorithms. We show how ideas from cutting-edge algorithms, including spectral graph theory and modern data structures, can be used to attack challenges in sequencing, medical genomics and biological networks. 

The NIH Wednesday Afternoon Lecture Series includes weekly scientific talks by some of the top researchers in the biomedical sciences worldwide. 

Author:  Dr. Bonnie Berger  
Runtime:  00:58:06  
Permanent link:  http://videocast.nih.gov/launch.asp?17563]]></description>
	
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