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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/1161?offset=80</link>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/videolist/watch/5380/04-informatics-approach-to-cancer-interview-with-dr-joel-saltz</guid>
	<pubDate>Mon, 07 Oct 2013 14:35:43 -0500</pubDate>
	<link>https://bioinformaticsonline.com/videolist/watch/5380/04-informatics-approach-to-cancer-interview-with-dr-joel-saltz</link>
	<title><![CDATA[04- Informatics Approach to Cancer - Interview with Dr. Joel Saltz]]></title>
	<description><![CDATA[<iframe width="" height="" src="https://www.youtube-nocookie.com/embed/8Kf5EP4LY7k" frameborder="0" allowfullscreen></iframe>For additional information visit http://www.cancerquest.org/joel-saltz-interview.

Dr. Joel Saltz is a Professor in the Departments of Pathology, Biostatistics and Bioinformatics, and Mathematics and Computer Science at
Emory University. Dr. Saltz's research on bioinformatics spans several disciplines.  One project involves applying computer analysis to medical imaging to yield better results for patients.  As an example, a computer program may able to help doctors detect small cancers in a CT scan or mammogram. 

In this interview segment, Dr. Saltz  discusses the informatics approach to cancer.

To learn more about cancer and watch additional interviews, please visit the CancerQuest website at http://www.cancerquest.org.]]></description>
	
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	<guid isPermaLink="true">https://bioinformaticsonline.com/videolist/watch/4959/evolution-and-cancer</guid>
	<pubDate>Fri, 27 Sep 2013 11:28:49 -0500</pubDate>
	<link>https://bioinformaticsonline.com/videolist/watch/4959/evolution-and-cancer</link>
	<title><![CDATA[Evolution and Cancer]]></title>
	<description><![CDATA[<iframe width="" height="" src="https://www.youtube-nocookie.com/embed/j3uKOcNwYBw" frameborder="0" allowfullscreen></iframe>Air date:  Wednesday, January 04, 2012, 3:00:00 PM
Time displayed is Eastern Time, Washington DC Local  
 
Category:  Wednesday Afternoon Lectures  
Description:  There is a broad consensus that cancer is the result of somatic cells having serially gained, by a series of mutations, the ability to grow independently, to recruit resources from the circulation and the stroma, to invade local tissues, and to found anatomically distant metastases, ultimately killing the host. From the point of view of the cancer-causing somatic cell population, this is evolution driven by mutation and selection. Genomics has resulted in a parallel consensus that the central functions of all eukaryotes are highly conserved, not only at the level of individual protein functions, but also complex biological pathways and systems. These ideas motivated a comparison between results of molecular genetic studies of experimental evolution in yeast and the molecular genetic phenomena associated with tumorigenesis and tumor progression. We find some very striking similarities, including recurring genomic rearrangements, alterations of the regulation of specific growth-promoting genes, population-genetic features that affect the fitness trajectories of growth rate variants in evolving populations, and physiological and metabolic similarities derived from the conservation of the basic plan of growth and cell multiplication among all eukaryotes. It is hoped that some of the insights from yeast will aid the interpretation of sequence changes found in tumors, especially in the urgent necessity to distinguish 'driver' from 'passenger' mutations." 

David Botstein's fundamental contributions to modern genetics include the development of genetic methods for understanding biological functions and the discovery of the functions of many yeast and bacterial genes. In 1980, Botstein and three colleagues proposed a method for mapping human genes that laid the groundwork for the Human Genome Project. The basic principle of the mapping scheme was to develop, by recombinant DNA techniques, random single-copy DNA probes capable of detecting DNA sequence polymorphisms when hybridized to restriction digests, or specific fragments, of an individual's DNA. The method was used in subsequent years to identify several human disease genes, such as Huntington's and BRCA1. Variations of this method enabled the sequencing phase of the Human Genome Project. 

In the 1990s Botstein, having moved to Stanford University School of Medicine, collaborated with Patrick O. Brown of Stanford in exploiting DNA microarrays to study genome-wide gene expression patterns in yeast and in human cancers. This required developing a new statistical method and graphical interface, widely used today to interpret genomic data. Botstein also has helped to create, with Michael Ashburner and Gerald Rubin, a bioinformatics initiative to unify the representation of gene and gene product attributes across all species, called Gene Ontology. He graduated from Harvard College and earned his doctorate from the University of Michigan. He worked at Massachusetts Institute of Technology from 1967 to 1988; served as vice president for science at Genentech from 1988 to 1990; chaired the Department of Genetics at the Stanford University School of Medicine from 1990 to 2003; and joined the Princeton University faculty in 2003. He has sat on numerous editorial boards and was the founding editor of Molecular Biology of the Cell. Among recent major awards, Bostein won the Peter Gruber Foundation Prize in Genetics in 2003, the Apple Science Innovator Award in 2008, and the Albany Medical Center Prize in 2010. 

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

For more information, visit: The NIH Director's Wednesday Afternoon Lecture Series  
Author:  Dr. David Botstein, Princeton University  
Runtime:  00:59:58  

Permanent link:  http://videocast.nih.gov/launch.asp?17046]]></description>
	
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/5623/yau-group</guid>
  <pubDate>Tue, 15 Oct 2013 13:05:15 -0500</pubDate>
  <link></link>
  <title><![CDATA[Yau Group]]></title>
  <description><![CDATA[
<p>Yau Group are a new research group based at the Wellcome Trust Centre for Human Genetics and the Department of Statistics at the University of Oxford.</p>

<p>Yau Group develops statistical and computational methods for the analysis of genomic datasets with a particular interest in cancer sequencing applications and the use of Bayesian Statistics.</p>

<p>Yau Group are currently have projects in somatic mutation analysis of heterogeneous cancers, data fusion or integration techniques and single cell genomics.</p>

<p>More @ http://www.well.ox.ac.uk/~cyau/index.html</p>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/6561/mathomics-lab</guid>
  <pubDate>Tue, 19 Nov 2013 18:17:32 -0600</pubDate>
  <link></link>
  <title><![CDATA[MATHomics Lab]]></title>
  <description><![CDATA[
<p>Mathomics is a collaborative research group of the Center for Mathematical Modeling and the Center for Genome Regulation at University of Chile, created to play a central role in the development of biotechnological projects, providing state of the art bioinformatics and mathematical modeling tools,  allowing to face these problems from the point of view of Systems Biology. </p>

<p>Lab page @ http://www.mathomics.cl/</p>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/2728/statistics-of-current-sequencing-and-bioinformatics-market</guid>
	<pubDate>Wed, 21 Aug 2013 08:29:21 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/2728/statistics-of-current-sequencing-and-bioinformatics-market</link>
	<title><![CDATA[Statistics of current Sequencing and Bioinformatics market]]></title>
	<description><![CDATA[<p>This survey conducted by&nbsp;<strong>Oxford&nbsp;<a href="http://www.ogt.co.uk/" target="_blank">Gene</a>&nbsp;Technology,</strong>&nbsp;<span>provider of innovative&nbsp;genetics&nbsp;research and&nbsp;biomarker</span>&nbsp;<span>solutions to advance molecular medicine, has released the results from a recent survey of researchers using next generation sequencing. (Source:<a href="http://www.news-medical.net/news/20130821/Oxford-Gene-Technology-releases-next-generation-sequencing-survey-results.aspx">http://www.news-medical.net/news/20130821/Oxford-Gene-Technology-releases-next-generation-sequencing-survey-results.aspx</a>&nbsp;)</span></p>
<p>&nbsp;</p><p>Address of the bookmark: <a href="http://www.ogt.com/assets/0000/3190/NGS_Survey_2013_Infographic_Web.pdf" rel="nofollow">http://www.ogt.com/assets/0000/3190/NGS_Survey_2013_Infographic_Web.pdf</a></p>]]></description>
	<dc:creator>Rahul Agarwal</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/7816/boku-lab</guid>
  <pubDate>Wed, 08 Jan 2014 19:33:12 -0600</pubDate>
  <link></link>
  <title><![CDATA[BOKU Lab]]></title>
  <description><![CDATA[
<p>We are interested in the study of complex systems in living organisms. Novel views augmenting the classical gene by gene approaches are required to overcome the engineered redundancies and combinatorial effects prevalent in higher eukaryotes. We therefore combine work to establish improved quantitative experimental assays, such as microarrays or differential in-gel electrophoresis, and development of modern computational methods, such as hierarchical probabilistic models or integration of heterogeneous data sources, focussed by biological studies in our laboratory and collaborations.</p>

<p>Highlights of our research include:</p>

<p>    Optimization of microarray design, probe signal interpretation <br />    Advanced models and tools for expression profiling<br />    State-of-the-art applications and integrated analyses </p>

<p>Lab page @ http://bioinf.boku.ac.at/</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/3031/following-the-scientific-literature-a-personal-practical-guide-for-young-computational-biologists</guid>
	<pubDate>Fri, 23 Aug 2013 07:18:51 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/3031/following-the-scientific-literature-a-personal-practical-guide-for-young-computational-biologists</link>
	<title><![CDATA[Following the scientific literature: A personal practical guide for young computational biologists]]></title>
	<description><![CDATA[<p><span>The goal of this guide is to describe&nbsp;</span><strong>why</strong><span>,&nbsp;</span><strong>when</strong><span>,&nbsp;</span><strong>where</strong><span>&nbsp;and&nbsp;</span><strong>how</strong><span>&nbsp;can you follow the most up-to-date science of interest and&nbsp;</span><strong>what</strong><span>&nbsp;papers/journals you should follow. The guide is biased towards the fields of genomics/systems biology.(from article)</span></p>
<p><span>Source:&nbsp;<strong><span>&nbsp;<a href="http://www.cs.tau.ac.il/~ulitskyi/">Igor Ulitsky</a>&nbsp;&amp;&nbsp;<a href="http://www.cs.tau.ac.il/~rshamir/">Ron Shamir</a></span></strong></span></p><p>Address of the bookmark: <a href="http://acgt.cs.tau.ac.il/guides/LiteratureGuide.htm" rel="nofollow">http://acgt.cs.tau.ac.il/guides/LiteratureGuide.htm</a></p>]]></description>
	<dc:creator>Rahul Agarwal</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/9675/application-scientist-in-strand-lifesciences-bangalore</guid>
  <pubDate>Mon, 07 Apr 2014 08:17:32 -0500</pubDate>
  <link></link>
  <title><![CDATA[Application Scientist in Strand LifeSciences Bangalore]]></title>
  <description><![CDATA[
<p>Job Description<br />We are looking for a motivated application scientist to help evaluate, compare, and develop next generation sequencing (NGS) data analysis methods. The successful candidate should be able to quickly understand the state-of-art computational biology techniques, prototype them and perform benchmarking studies. The candidate must also be comfortable working with people from different disciplines and be able to present data analysis results in a clear and effective manner. The candidate is also expected to interact with customers as needed, write technical reports and publish new methods and/or data analysis findings in public forums.</p>

<p>Candidate Requirements:<br />A PhD in computer science, computational biology, Bioinformatics, or a related field, along with sufficient programming skills for prototyping. Experience with next generation sequencing data analysis is required. Candidates with MS degree but with relevant work experience can also be considered. </p>

<p>To Apply<br />To apply, please send your updated CV and cover letter to Dr. Rohit Gupta (rohit@strandls.com). </p>

<p>Source: http://www.strandls.com/application-scientist</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/7913/the-genome-factory</guid>
	<pubDate>Thu, 16 Jan 2014 02:09:31 -0600</pubDate>
	<link>https://bioinformaticsonline.com/news/view/7913/the-genome-factory</link>
	<title><![CDATA[The genome factory !!!]]></title>
	<description><![CDATA[<p>Illumina, Inc. announced Tuesday that its new HiSeq X Ten Sequencing System has broken the &ldquo;sound barrier&rdquo; of human genomics by enabling the $1,000 genome. &ldquo;This platform includes dramatic technology breakthroughs that enable researchers to undertake studies of unprecedented scale by providing the throughput to sequence tens of thousands of human whole genomes in a single year in a single lab,&rdquo; Illumina stated.</p><p>Initial customers for the HiSeq X Ten System, which will ship in Q1 2014, include Macrogen, based in Seoul, South Korea and its CLIA laboratory in Rockville, Maryland, the Broad Institute in Cambridge, Massachusetts, and the Garvan Institute of Medical Research in Sydney, Australia.</p><p>&ldquo;For the first time, it looks like it will be possible to deliver the $1,000 genome, which is tremendously exciting,&rdquo; said Eric Lander, founding director of the Broad Institute and a professor of biology at MIT. &ldquo;The HiSeq X Ten should give us the ability to analyze complete genomic information from huge sample populations. Over the next few years, we have an opportunity to learn as much about the genetics of human disease as we have learned in the history of medicine.&rdquo;</p><p>&ldquo;The HiSeq X Ten is an ideal platform for scientists and institutions focused on the discovery of genotypic variation to enable a deeper understanding of human biology and genetic disease,&rdquo; Illumina stated. &ldquo;It can sequence tens of thousands of samples annually with high-quality, high-coverage sequencing, delivering a comprehensive catalog of human variation within and outside coding regions.&rdquo;</p><p>HiSeq X Ten utilizes a number of advanced design features to generate massive throughput. Patterned flow cells, which contain billions of nanowells at fixed locations, combined with a new clustering chemistry deliver a significant increase in data density (6 billion clusters per run). Using state-of-the art optics and faster chemistry, HiSeq X Ten can process sequencing flow cells more quickly than ever before &mdash; generating a 10x increase in daily throughput when compared to current HiSeq 2500 performance.</p><p>The HiSeq X Ten is sold as a set of 10 or more ultra-high throughput sequencing systems, each generating up to 1.8 terabases (Tb) of sequencing data in less than three days or up to 600 gigabases (Gb) per day, per system, providing the throughput to sequence tens of thousands of high-quality, high-coverage genomes per year. Illumina says the $1,000 includes typical instrument depreciation, DNA extraction, library preparation, and estimated labor.</p>]]></description>
	<dc:creator>Madhvan Reddy</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/8442/assistant-professor-king-saud-university-riyadh</guid>
  <pubDate>Fri, 21 Feb 2014 05:57:18 -0600</pubDate>
  <link></link>
  <title><![CDATA[Assistant Professor @ King Saud University Riyadh]]></title>
  <description><![CDATA[
<p>Qualifications: Candidates must have a Ph.D. and a strong background in Molecular and Cellular Biology, protein expression, FACS, or computational biology, and ability to work collaboratively.</p>

<p>This position will have a significant focus on providing analytical support for next generation sequencing data analysis – Exome-sequencing, Targetted sequencing as well as high-throughput genotyping on Illumina platform.</p>

<p>Job location:</p>

<p>Genome Research Chair<br />King Saud University, Riyadh-11451<br />KSA</p>

<p>Interested candidate may forward their CV to grcksu@gmail.com</p>
]]></description>
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