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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/26290?offset=160</link>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/872/jayaram-lab</guid>
  <pubDate>Sun, 14 Jul 2013 14:04:37 -0500</pubDate>
  <link></link>
  <title><![CDATA[Jayaram Lab]]></title>
  <description><![CDATA[
<p>Responsible (a) for developing Chemgenome, Bhageerath &amp; Sanjeevini methods &amp; softwares for genome annotation, protein tertiary structure prediction &amp; computer aided drug design respectively, (b) for setting up a multi-teraflop supercomputing facility for Bioinformatics &amp; Computational Biology at IIT Delhi, and (c) for making the hardware and software freely accessible at (www.scfbio-iitd.res.in) to the global scientific user community.</p>

<p>Faculty facilitator/Founder Director for two start-up companies (Leadinvent incubated at IIT, Delhi from 2006-2009 &amp; Novoinformatics, under incubation at IIT Delhi since 2011).</p>

<p>Research Interest <br />Genome Analysis, Protein Structure Prediction and Drug Design.</p>

<p>Link @ http://www.scfbio-iitd.res.in/</p>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/1161/genomics-for-bioinformatician</guid>
	<pubDate>Sat, 20 Jul 2013 07:03:00 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/1161/genomics-for-bioinformatician</link>
	<title><![CDATA[Genomics for Bioinformatician]]></title>
	<description><![CDATA[<p>Genomics is the study of the genomes of organisms. The field includes intensive efforts to determine the entire DNA sequence of organisms and fine-scale genetic mapping efforts. The field also includes studies of intragenomic phenomena such as heterosis, epistasis, pleiotropy and other interactions between loci and alleles within the genome. In contrast, the investigation of the roles and functions of single genes is a primary focus of molecular biology or genetics and is a common topic of modern medical and biological research. Research of single genes does not fall into the definition of genomics unless the aim of this genetic, pathway, and functional information analysis is to elucidate its effect on, place in, and response to the entire genome's networks.<br /><br />Genomics was established by Fred Sanger when he first sequenced the complete genomes of a virus and a mitochondrion. His group established techniques of sequencing, genome mapping, data storage, and bioinformatic analyses in the 1970-1980s. A major branch of genomics is still concerned with sequencing the genomes of various organisms, but the knowledge of full genomes has created the possibility for the field of functional genomics, mainly concerned with patterns of gene expression during various conditions. The most important tools here are microarrays and bioinformatics. Study of the full set of proteins in a cell type or tissue, and the changes during various conditions, is called proteomics. A related concept is materiomics, which is defined as the study of the material properties of biological materials (e.g. hierarchical protein structures and materials, mineralized biological tissues, etc.) and their effect on the macroscopic function and failure in their biological context, linking processes, structure and properties at multiple scales through a materials science approach. The actual term 'genomics' is thought to have been coined by Dr. Tom Roderick, a geneticist at the Jackson Laboratory (Bar Harbor, ME) over beer at a meeting held in Maryland on the mapping of the human genome in 1986.<br /><br />The outcome of almost two years of intense discussions with literally hundreds of scientists and members of the public, has three major areas of focus: Genomics to Biology, Genomics to Health, and Genomics to Society.<br /><br /><strong><em>Genomics to Biology:</em></strong>&nbsp;<br />The human genome sequence provides foundational information that now will allow development of a comprehensive catalog of all of the genome's components, determination of the function of all human genes, and deciphering of how genes and proteins work together in pathways and networks.<br /><br /><strong><em>Genomics to Health:<br /></em></strong>Completion of the human genome sequence offers a unique opportunity to understand the role of genetic factors in health and disease, and to apply that understanding rapidly to prevention, diagnosis, and treatment. This opportunity will be realized through such genomics-based approaches as identification of genes and pathways and determining how they interact with environmental factors in health and disease, more precise prediction of disease susceptibility and drug response, early detection of illness, and development of entirely new therapeutic approaches.<br /><br /><strong><em>Genomics to Society:</em>&nbsp;<br /></strong>Just as the HGP has spawned new areas of research in basic biology and in health, it has created new opportunities in exploring the ethical, legal, and social implications (ELSI) of such work. These include defining policy options regarding the use of genomic information in both medical and non-medical settings and analysis of the impact of genomics on such concepts as race, ethnicity, kinship, individual and group identity, health, disease, and "normality" for traits and behaviors.<br /><br />This vision for the future of genomics is not just about the NHGRI. It encompasses the whole field of genomics, including the work of all the other Institutes and Centers at the NIH and of a number of other federal agencies. All of the NIH Institutes are already taking full advantage of the sequence and will apply its data to the better understanding of both rare and common diseases, almost all of which have a genetic component. A recent example of the way that the HGP and the knowledge and new technologies it has spawned are already facilitating science is the extremely rapid sequencing by groups in Canada and at the Centers for Disease Control and Prevention (CDC) in Atlanta of the genome of the virus that causes Severe Acute Respiratory Syndrome (SARS). The sequencing of the SARS virus genome provides insight into this new and deadly disease at a speed never before possible in science. In turn, this should lead to the rapid development of diagnostic tests and, in time, vaccines and effective treatments.<br /><br /><strong>Links for the addition material available on Net</strong></p><p><a href="http://pevsnerlab.kennedykrieger.org/bioinformatics/bioinf10_genomes.htm">Genomes and genomics:</a></p><p><a href="http://www.123genomics.com/learning.html">Bioinformatics and Genomics:</a></p><p><a href="http://www.ebi.ac.uk/pdbe/docs/roadshow_tutorial/strgenomics/tutorial.html">Structural genomics tutorial:</a></p><p><a href="http://www.hgu.mrc.ac.uk/Users/Philippe.Gautier/tutorial/index.html">Comparative Genomics Tutorial:</a></p><p><a href="http://www.scfbio-iitd.res.in/tutorial/genomics.html">GENOME TUTORIAL:</a></p><p><a href="http://genomebiology.com/content/pdf/gb-2001-3-1-reviews2001.pdf">Tools and resources for identifying protein families, domains and motifs</a></p><p><a href="http://www.ornl.gov/sci/techresources/Human_Genome/posters/chromosome/tools.shtml">Bioinformatics Tools</a><a href="http://www.ornl.gov/sci/techresources/Human_Genome/posters/chromosome/tools.shtml">&nbsp;<br />Tips, Tutorials, and Terminology for Using Selected Resources in Genome Database Guide:</a></p><p><a href="http://www.doe-mbi.ucla.edu/Reprints/R31%20Strong%20A%20Web-based%20Comparative%20Genomics%20tutorial%20Microbiology%20Eduction%202004.pdf">A Web-Based Comparative Genomics Tutorial for Investigating Microbial Genomes:</a></p><p><a href="http://www.genome.gov/27530225">Free Online Tutorials Teach Anyone How to Use Genome Databases:</a></p><p><a href="http://mkweb.bcgsc.ca/circos/?tutorials">Circos to create concise, explanatory, unique and print-ready visualizations of your data:</a></p><p><a href="http://www.igd.cornell.edu/Comparative%20Genomics/Comparative%20Genomics%20Proj.html">Genomics and Comparative Genomics</a><a href="http://www.igd.cornell.edu/Comparative%20Genomics/Comparative%20Genomics%20Proj.html">&nbsp;Learning Module:</a></p><p><a href="http://psb.stanford.edu/psb10/conference-materials/tutorials/compgen-notes.pdf">Computational Challenges in Comparative Genomics</a></p><p><a href="http://psb.stanford.edu/psb10/conference-materials/tutorials/compgen-notes.pdf">A Tutorial:</a></p><p><a href="http://gramene.agrinome.org/tutorials/modules_tutorial.pdf">A Comparative Genomics Resource for Grains</a>:</p><p><a href="http://www.plantcell.org/cgi/content/full/21/12/3718">PLAZA: A Comparative Genomics Resource to Study Gene and Genome Evolution in Plants:</a></p><p><a href="http://en.wikipedia.org/wiki/VISTA_(comparative_genomics)">VISTA</a><a href="http://en.wikipedia.org/wiki/VISTA_(comparative_genomics)">:</a></p><p>Software for Genomics</p><ol>
<li><strong>Artemis</strong>&nbsp;Artemis is a free genome viewer and annotation tool that allows visualization of sequence features and the results of analyses within the context of the sequence, and its six-frame translation.</li>
<li><strong>Chromas&nbsp;</strong>It will display and prints chromatogram files from ABI automated DNA sequencers, and Staden SCF files which the analysis programs for ALF, Li-Cor and Visible Genetics OpenGene sequencers can create.</li>
<li><strong>Glimmer</strong>&nbsp;A system for finding genes in microbial DNA, especially the genomes of bacteria and archaea.Glimmer (Gene Locator and Interpolated Markov Modeler) uses interpolated Markov models (IMMs) to identify the coding regions and distinguish them from noncoding DN</li>
<li><strong>Glimmer</strong>&nbsp;HMM&nbsp;A fast and accurate gene finder based on a GHMM architecture, developed specifically for eukaryotes. It incorporates splice site models adapted from the GeneSplicer program and uses interpolated Markov models for evaluating the coding regions.</li>
<li><strong>Glimmer</strong>&nbsp;M&nbsp;A gene finder derived from Glimmer, but developed specifically for eukaryotes. It is based on a dynamic programming algorithm that considers all combinations of possible exons for inclusion in a gene model and chooses the best of these combinations. The d</li>
<li><strong>MUMmer</strong>&nbsp;MUMmer is a system for rapidly aligning entire genomes, whether in complete or draft form.</li>
<li><strong>pDRAW</strong>&nbsp;pDRAW32 is being developed as a free time hobby project. It is far from finished, but as it has reached a point where it could be helpful for many labs, it is now available to the scientific community.</li>
<li><strong>Sequin</strong>&nbsp;Sequin is a stand-alone software tool developed by the NCBI for submitting and updating entries to the GenBank, EMBL, or DDBJ sequence databases. It is capable of handling simple submissions that contain a single short mRNA sequence, and complex submissio</li>
<li><strong>Staden&nbsp;</strong>The Staden Package consists of a series of tools for DNA sequence preparation (pregap4), assembly (gap4), editing (gap4) and DNA/protein sequence analysis (spin).</li>
</ol><p>For more software @&nbsp;<a href="http://bioinformaticsonline.com/bookmarks/view/926/list-of-popular-bioinformatics-softwaretools">http://bioinformaticsonline.com/bookmarks/view/926/list-of-popular-bioinformatics-softwaretools</a></p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/videolist/watch/4003/personalised-medicine-animation</guid>
	<pubDate>Tue, 27 Aug 2013 10:07:24 -0500</pubDate>
	<link>https://bioinformaticsonline.com/videolist/watch/4003/personalised-medicine-animation</link>
	<title><![CDATA[Personalised Medicine - Animation]]></title>
	<description><![CDATA[<iframe width="" height="" src="https://www.youtube-nocookie.com/embed/fEY3Khsmuak" frameborder="0" allowfullscreen></iframe>Two animated case scenarios set now and in the future. These highlight potential differences in the way patients are treated now, and how they might be treated as healthcare becomes more tailored.]]></description>
	
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	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/1515/list-of-pharmacogenomics-companies-in-india</guid>
	<pubDate>Fri, 09 Aug 2013 13:26:56 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/1515/list-of-pharmacogenomics-companies-in-india</link>
	<title><![CDATA[List of pharmacogenomics companies in India]]></title>
	<description><![CDATA[<p>pharmacogenomics companies in India are making their good impacts. Here is the list of few pharmacogenomics companies. Please add more if not mentioned here.</p><p>Genomics in India <br /><a href="http://www.ganitlabs.in/">www.ganitlabs.in</a> <br /><a href="http://www.sandor.co.in/">www.sandor.co.in</a> <br /><a href="http://www.igib.res.in/">www.igib.res.in</a> <br /><a href="http://www.genotypic.co.in/">www.genotypic.co.in</a> <br /><a href="http://www.ocimumbio.com/">www.ocimumbio.com</a> <br /><a href="http://www.abcgenomics.com/">www.abcgenomics.com</a> <br /><a href="http://www.xcelrisgenomics.com/">www.xcelrisgenomics.com</a> <br /><a href="http://www.ayugen.com/">www.ayugen.com</a> <br /><a href="http://www.geneombiotech.com/">www.geneombiotech.com</a></p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/6458/bigre-lab</guid>
  <pubDate>Sun, 17 Nov 2013 10:35:49 -0600</pubDate>
  <link></link>
  <title><![CDATA[BIGRE Lab]]></title>
  <description><![CDATA[
<p>The Laboratoire de Bioinformatique des Génomes et des Réseaux (Genome and Network Bioinformatics) is specialized in the conception, implementation, evaluation and application of bioinformatics approaches for the analysis of genome, transcriptome, proteome and metabolism.<br />Our main activities include</p>

<p>Analysis of regulatory sequences (RSAT project)<br />Classification and analysis of mobile genetic elements (ACLAME project).<br />Analysis of molecular interaction networks (NeAT project)<br />Inference of metabolic pathways from genomic and post-genomic data <br />(metabolic pathfinding, see also metabolic pathfinding in NeAT)<br />Critical assesment of protein interactions (CAPRI)</p>

<p>Lab Page http://www.bigre.ulb.ac.be/</p>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/videolist/watch/2464/computer-theory-genetics-george-chao-at-tedxumnsalon</guid>
	<pubDate>Thu, 15 Aug 2013 22:08:10 -0500</pubDate>
	<link>https://bioinformaticsonline.com/videolist/watch/2464/computer-theory-genetics-george-chao-at-tedxumnsalon</link>
	<title><![CDATA[Computer Theory & Genetics: George Chao at TEDxUMNSalon]]></title>
	<description><![CDATA[<iframe width="" height="" src="https://www.youtube-nocookie.com/embed/7_GL17oiak8" frameborder="0" allowfullscreen></iframe>George Chao is an undergraduate senior studying Genetics and Computer Science at the University of Minnesota. Having started genetics research as soon as he entered the university, he has worked in labs spanning multiple disciplines as well as in Japan. Some of these researches include developmental genetics in Drosophila, computational techniques for analyzing protein interactions, and helping with the development of algorithms to analyze motion capture data of patients with neck pain. During this time, George steadily developed a fascination with the field of bioinformatics, the study of using computational techniques to learn from genetic data. He would like to go into a career of research into the application of bioinformatics in various fields.

----

The individuals involved with TEDxUMN have a passion for bringing together the great thinkers at the University of Minnesota and giving them the opportunity to share their ideas worth spreading and to discuss our shared future. We provide these great people the opportunity to share these ideas on a global stage and with an incredibly diverse audience. We believe in the power of ideas to change attitudes, lives and ultimately the world.

Check out TEDxUMN at http://www.TEDxUMN.com/

In the spirit of ideas worth spreading, TEDx is a program of local, self-organized events that bring people together to share a TED-like experience. At a TEDx event, TEDTalks video and live speakers combine to spark deep discussion and connection in a small group. These local, self-organized events are branded TEDx, where x = independently organized TED event. The TED Conference provides general guidance for the TEDx program, but individual TEDx events are self-organized.* (*Subject to certain rules and regulations)]]></description>
	
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	<guid isPermaLink="true">https://bioinformaticsonline.com/videolist/watch/3964/what-is-life-a-21st-century-perspective-by-dr-craig-venter</guid>
	<pubDate>Mon, 26 Aug 2013 17:09:17 -0500</pubDate>
	<link>https://bioinformaticsonline.com/videolist/watch/3964/what-is-life-a-21st-century-perspective-by-dr-craig-venter</link>
	<title><![CDATA['What is Life? A 21st Century Perspective' by Dr Craig Venter]]></title>
	<description><![CDATA[<iframe width="" height="" src="https://www.youtube-nocookie.com/embed/qi2MhsUSu0U" frameborder="0" allowfullscreen></iframe>One of the landmark events of 20th century science was celebrated and reinterpreted for the 21st century in Trinity College Dublin on 12 July 2012 as part of the Science in the City programme of ESOF2012. Dr Craig Venter, one of the leaders of the Human Genome Project in the 1990s and a pioneer of synthetic biology delivered a lecture entitled, 'What is Life? A 21st century perspective' recreating the Irish event that inspired the discovery of the structure of DNA. 

In February, 1943 one of the most distinguished scientists of the 20th Century, Erwin Schrödinger, delivered a seminal lecture, entitled 'What is Life?', under the auspices of the Dublin Institute for Advanced Studies, in Trinity College Dublin. The lecture presented far-sighted ideas on how hereditary information could be encoded in a chemical structure (aperiodic crystal) in living cells. Schrödinger's book (1944) of the same title is considered to be a scientific classic. The book was cited by Crick and Watson as one of the inspirations which ultimately led them to unravel the structure of DNA in 1953, a breakthrough which won them the Nobel prize.]]></description>
	
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/4657/giovanni-parmigiani-lab</guid>
  <pubDate>Fri, 20 Sep 2013 13:21:41 -0500</pubDate>
  <link></link>
  <title><![CDATA[Giovanni Parmigiani Lab]]></title>
  <description><![CDATA[
<p>Scientific Interests:</p>

<p>Models and software for predicting who is at risk of carrying genetic variants that confer susceptibility to cancer. Application to breast, ovarian, colorectal, pancreatic and skin cancer.</p>

<p>Statistical methods for the analysis of high throughput genomic data: analysis of cancer genome sequencing projects; integration of genomic information across technologies; cross-study validation of genomics results.</p>

<p>Statistical methods for comparative effectiveness research: comprehensive models for lifetime history of chronic disease outcomes; Bayesian meta-analysis; Bayesian causal inference; decision analysis.</p>

<p>Bayesian modeling and computation: multilevel models; decision theoretic approaches to inference; sequential experimental design and their application to adaptive and multistage studies in clinical and epidemiological research.</p>

<p>http://bcb.dfci.harvard.edu/~gp/index.html</p>

<p>http://scholar.google.com/citations?user=OlpYP3UAAAAJ&amp;hl=en</p>
]]></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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