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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/29276?offset=520</link>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/videolist/watch/4960/genome-epigenome-new-understanding-of-the-pathogens-in-your-food</guid>
	<pubDate>Fri, 27 Sep 2013 11:30:45 -0500</pubDate>
	<link>https://bioinformaticsonline.com/videolist/watch/4960/genome-epigenome-new-understanding-of-the-pathogens-in-your-food</link>
	<title><![CDATA[Genome + Epigenome = New Understanding of the Pathogens in Your Food]]></title>
	<description><![CDATA[<iframe width="" height="" src="https://www.youtube-nocookie.com/embed/hGtHs_C1BFA" frameborder="0" allowfullscreen></iframe>UC Davis's Bart Weimer describes foodborne pathogens and their proclivity for rapid genome rearrangement. The 100K Pathogen Genome Project he leads is using PacBio long-read sequencing to close genomes and analyze methylation; Weimer reports that his team has already discovered new epigenetic modifications in Salmonella and Listeria with the technology. www.pacb.com/microbe]]></description>
	
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	<guid isPermaLink="true">https://bioinformaticsonline.com/poll/view/19921/which-of-the-followings-are-the-best-place-to-study-bioinformatics</guid>
	<pubDate>Sun, 28 Dec 2014 00:20:30 -0600</pubDate>
	<link>https://bioinformaticsonline.com/poll/view/19921/which-of-the-followings-are-the-best-place-to-study-bioinformatics</link>
	<title><![CDATA[Which of the followings are the best place to study Bioinformatics ?]]></title>
	<description><![CDATA[<p>Bioinformatics is a major growth area and qualified Bioinformaticians are in high demand. An explosion in biological data has resulted from genome projects, next generation sequencing and other 'omics' techniques. Bioinformatics provides the tools to analyse and exploit such data sets.<br /><br />Can you please suggest me the best place to study bioinformatics ( Grad/PostGrad).</p>]]></description>
	<dc:creator>Reshma Khatun</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/file/view/18653/genetic-code-amino-acid</guid>
	<pubDate>Sun, 26 Oct 2014 07:45:58 -0500</pubDate>
	<link>https://bioinformaticsonline.com/file/view/18653/genetic-code-amino-acid</link>
	<title><![CDATA[Genetic code - Amino Acid]]></title>
	<description><![CDATA[<p>The genetic code consists of 64 triplets of nucleotides. These triplets are called codons.With three exceptions, each codon encodes for one of the 20 amino acids used in the synthesis of proteins. That produces some redundancy in the code: most of the amino acids being encoded by more than one codon.</p><p>The image summarise all in one.</p><p>More at http://users.rcn.com/jkimball.ma.ultranet/BiologyPages/C/Codons.html</p>]]></description>
	<dc:creator>Poonam Mahapatra</dc:creator>
	<enclosure url="https://bioinformaticsonline.com/file/download/18653" length="226605" type="image/jpeg" />
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	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/20007/roche-has-acquired-bina-technologies</guid>
	<pubDate>Tue, 30 Dec 2014 09:42:16 -0600</pubDate>
	<link>https://bioinformaticsonline.com/news/view/20007/roche-has-acquired-bina-technologies</link>
	<title><![CDATA[Roche has acquired Bina Technologies !!!]]></title>
	<description><![CDATA[<p>Bina Technologies is a privately held company that provides a big data platform for centralized management and processing of next generation sequencing (NGS) data for the academic and translational research markets.&nbsp; Bina will be integrated into the Roche Sequencing Unit, and will continue to focus on development of their innovative genomic analysis solution.<br /><br />Roche has acquired Bina Technologies, a privately-owned biotech company based in California. The biotech&rsquo;s first product was the Bina Box, a platform for secondary genomic analysis, sequence alignment, and variant calling, but since 2012, it has developed other products and platforms. <br /><br />It is our shared vision with Roche that informatics and data sciences are critical elements of an end-to-end genomics solution. Fast, easy-to-use, scalable, and robust informatics solutions make a big difference in the quality and impact of the work of scientists and researchers. We believe in the future of data-driven, personalized medicine. We are passionate about accelerating that future together with Roche.<br /><br />Financial details of the deal were not disclosed. For Roche, the move is yet another in a string of acquisitions. Last week (December 18), Roche paid $489 million for antibody maker Dutalys. And earlier this month, Roche bought prenatal testing company Ariosa Diagnostics.</p><p>Reference</p><p>http://blog.bina.com/news/bina-technologies-acquired-by-roche?&amp;__hssc=109677338.1.1419953400266&amp;__hstc=109677338.b8350f2729889b08f1325906d5236cd3.1419953400266.1419953400266.1419953400266.1&amp;hsCtaTracking=96cac941-9372-4bbf-bacb-3ca6f1ff8cfd|3fce0f18-835b-4086-9345-388880861732</p><p>http://www.the-scientist.com/?articles.view/articleNo/41750/title/Roche-Buys-Bioinformatics-Firm/</p>]]></description>
	<dc:creator>Jit</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/32948/simba-a-web-tool-for-managing-bacterial-genome-assembly-generated-by-ion-pgm-sequencing-technology</guid>
	<pubDate>Tue, 23 May 2017 05:28:56 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/32948/simba-a-web-tool-for-managing-bacterial-genome-assembly-generated-by-ion-pgm-sequencing-technology</link>
	<title><![CDATA[SIMBA: a web tool for managing bacterial genome assembly generated by Ion PGM sequencing technology]]></title>
	<description><![CDATA[<p><span>SIMBA</span><span>, SImple Manager for Bacterial Assemblies, is a Web interface for managing assembly projects of bacterial genomes. SIMBA was created to assist bioinformaticians to assemble bacterial genomes sequenced with NextGeneration Sequencing (NGS) platforms quickly, easily and effectively. SIMBA also is open source tool, i.e., can be freely downloaded, shared and modified.</span></p>
<p>https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-016-1344-7</p><p>Address of the bookmark: <a href="http://ufmg-simba.sourceforge.net/" rel="nofollow">http://ufmg-simba.sourceforge.net/</a></p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/20331/type-hinting</guid>
	<pubDate>Fri, 09 Jan 2015 22:26:13 -0600</pubDate>
	<link>https://bioinformaticsonline.com/news/view/20331/type-hinting</link>
	<title><![CDATA[Type Hinting]]></title>
	<description><![CDATA[<p>Python creator Guido van Rossum&rsquo;s proposal for static type-checking annotations is inching closer to reality, and the feature has taken on a new name: type hinting.</p><p><img src="http://sdtimes.com/wp-content/uploads/2015/01/0107.sdt-python-typehinting.png" alt="image" width="619" height="219" style="border: 0px; border: 0px;"></p><p>Back in August, van Rossum published a proposal on the Python mailing list recommending type-checking annotations as a valuable feature for the next version of Python to improve the performance of editors and IDEs, linter capabilities, standard notation, and refactoring. Van Rossum&rsquo;s <a href="http://lwn.net/Articles/627558/">latest proposal</a>, posted late last month, outlined plans to publish a Python Enhancement Proposal (PEP) in early January to put the feature now known as type hinting on track for inclusion in Python 3.5, slated for release this September.</p><p>Reference</p><p>https://quip.com/r69HA9GhGa7J</p>]]></description>
	<dc:creator>Pranjali Yadav</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34216/meraculous-de-novo-genome-assembly-with-short-paired-end-reads</guid>
	<pubDate>Tue, 07 Nov 2017 04:36:10 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34216/meraculous-de-novo-genome-assembly-with-short-paired-end-reads</link>
	<title><![CDATA[Meraculous: De Novo Genome Assembly with Short Paired-End Reads]]></title>
	<description><![CDATA[<p><span>We describe a new algorithm, meraculous, for whole genome assembly of deep paired-end short reads, and apply it to the assembly of a dataset of paired 75-bp Illumina reads derived from the 15.4 megabase genome of the haploid yeast&nbsp;</span><em>Pichia stipitis</em><span>. More than 95% of the genome is recovered, with no errors; half the assembled sequence is in contigs longer than 101 kilobases and in scaffolds longer than 269 kilobases. Incorporating fosmid ends recovers entire chromosomes. Meraculous relies on an efficient and conservative traversal of the subgraph of the&nbsp;</span><em>k</em><span>-mer (deBruijn) graph of oligonucleotides with unique high quality extensions in the dataset, avoiding an explicit error correction step as used in other short-read assemblers. A novel memory-efficient hashing scheme is introduced. The resulting contigs are ordered and oriented using paired reads separated by &sim;280 bp or &sim;3.2 kbp, and many gaps between contigs can be closed using paired-end placements. Practical issues with the dataset are described, and prospects for assembling larger genomes are discussed.</span></p><p>Address of the bookmark: <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3158087/" rel="nofollow">https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3158087/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/20363/postdoctoral-researcher-in-cancer-systems-biology</guid>
  <pubDate>Mon, 12 Jan 2015 01:44:11 -0600</pubDate>
  <link></link>
  <title><![CDATA[Postdoctoral Researcher in Cancer Systems Biology]]></title>
  <description><![CDATA[
<p>Postdoctoral Researcher in Cancer Systems Biology<br />Department of Oncology, Old Road Campus Research Building, Roosevelt Drive, Oxford<br />Grade 7: £30,434 - £37,394 with a discretionary range to £40,847 p.a.<br />Applications are invited for a Postdoctoral Researcher in Cancer Systems Biology to join a rapidly developing Bioinformatics Research Core group headed by Dr Anastasia Samsonova. The purpose of the role is to develop and deliver integrative approaches to dissect the complexity of cancer as a genomic disease. The research will focus on development and application of effective strategies for mining and integration of complex human *omics datasets and clinical/phenotypic data in cancer studies.</p>

<p>The role sits at the critical interface between genetics and cancer systems biology, and would suit a candidate who is interested in developing a career at the confluence of Statistics/Data Mining/Machine Learning and Biology. Ideally, you will have experience in development of analytical approaches to high-throughput and multivariate data mining and integration gained through a PhD (or equivalent) in a quantitative subject (eg mathematics, statistics, physics, engineering or computer science).</p>

<p>Experience of statistics and/or machine learning techniques is highly desirable as is evidence of prior experience of developing bioinformatics software and/or analysing complex *omics data sets. You will be able to work as part of a team and independently and deliver results to the required standard and schedule. You should be able to organise and prioritise your own work, as well as have excellent communication skills, both written and oral. The post will involve interactions with collaborators from such diverse fields as applied mathematics, statistics, computer science and medicine.</p>

<p>This is a full-time post, fixed-term until 31 March 2017. For informal enquiries, contact Dr Anastasia Samsonova (bioinformatics@oncology.ox.ac.uk).</p>

<p>All applicants must complete a short application form and upload a CV and supporting statement.</p>

<p>The closing date for applications is 12.00 noon on 26 January 2015.</p>

<p>More at https://www.recruit.ox.ac.uk/pls/hrisliverecruit/erq_jobspec_version_4.display_form</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37746/funannotate-eukaryotic-genome-annotation-pipeline</guid>
	<pubDate>Wed, 19 Sep 2018 07:47:22 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37746/funannotate-eukaryotic-genome-annotation-pipeline</link>
	<title><![CDATA[funannotate: Eukaryotic Genome Annotation Pipeline]]></title>
	<description><![CDATA[<p><span>Funannotate is a genome prediction, annotation, and comparison software package. It was originally written to annotate fungal genomes (small eukaryotes ~ 30 Mb genomes), but has evolved over time to accomodate larger genomes. The impetus for this software package was to be able to accurately and easily annotate a genome for submission to NCBI GenBank. Existing tools (such as Maker) require significant manually editing to comply with GenBank submission rules, thus funannotate is aimed at simplifying the genome submission process.</span></p><p>Address of the bookmark: <a href="https://github.com/nextgenusfs/funannotate" rel="nofollow">https://github.com/nextgenusfs/funannotate</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/20439/interactive-market-intelligence</guid>
	<pubDate>Mon, 19 Jan 2015 08:20:38 -0600</pubDate>
	<link>https://bioinformaticsonline.com/news/view/20439/interactive-market-intelligence</link>
	<title><![CDATA[Interactive Market Intelligence]]></title>
	<description><![CDATA[<p>BioInformatics LLC, a premier research and advisory firm serving the life science industry, has launched groundbreaking, dynamic-data presentation platform, Interactive Market Intelligence&mdash; the only cloud-based market research analytics tool for the life science tools industry.<br /><br />Superior to traditional PDF and PowerPoint reports, Interactive Market Intelligence allows end-users to filter, create and export literally thousands of views of data &mdash; all easily obtainable from a set of core metrics that include market, brand, customer and workflow analytics in well-defined segments of the life science market.<br /><br />The Market for Real-Time PCR is the first in a series of topics to be explored using the Interactive Market Intelligence platform. The primary research analysis is based on a survey of 900+ international scientists performing qPCR in their laboratories.<br /><br />Key data findings from "The Market for Real-Time PCR": Global market for qPCR in 2015 is estimated to be $3.6B; The average growth in qPCR throughput is expected to be at 9.8% in 2015; 22% of respondents are highly likely to switch primary suppliers of qPCR products; 50% of respondents use pre-designed primer/probe sets.</p>]]></description>
	<dc:creator>Pranjali Yadav</dc:creator>
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