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Posted to commits@taverna.apache.org by bu...@apache.org on 2015/02/26 13:14:44 UTC
svn commit: r941534 - in /websites/staging/taverna/trunk: cgi-bin/ content/
content/introduction/taverna-in-use/disease-research.html
Author: buildbot
Date: Thu Feb 26 12:14:44 2015
New Revision: 941534
Log:
Staging update by buildbot for taverna
Added:
websites/staging/taverna/trunk/content/introduction/taverna-in-use/disease-research.html
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websites/staging/taverna/trunk/cgi-bin/ (props changed)
websites/staging/taverna/trunk/content/ (props changed)
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+ <h1>Disease-related research</h1>
+ <div class="alert alert-info" role="alert"><p><span class="glyphicon glyphicon-info-sign" aria-hidden="true"></span>
+
+Taverna is transitioning to the Apache Incubator.
+This webpage reflects material not yet released under Apache Incubator.
+Instead it shows <a class="alert-link" href="http://www.taverna.org.uk/">taverna2</a> material that is expected to become part of the Apache Incubator project in the future.
+</div>
+
+
+ <div id="content"><p>Taverna is used by various projects and researchers for investigations into various diseases:</p>
+<ul>
+<li><a href="#vph-dareit">Dementia</a> (VPH-DARE@IT and VPH-SHARE)</li>
+<li><a href="#analysis-of-anthrax-bacterium">Analysis of the anthrax bacterium</a></li>
+<li><a href="#trypanosomiasis">Study of resistance into trypanosomiasis</a> (sleeping sickness)</li>
+<li><a href="#graves-disease">Identification of genes linked to Graves disease</a></li>
+<li><a href="#williams-beuren-syndrome">Characterisation of genes associated with Williams-Beuren syndrome</a></li>
+<li><a href="/introduction/related-projects#cagrid">Cancer research</a> (caGrid)</li>
+</ul>
+<p><a name="vph-dareit"></a></p>
+<h2 id="vph-dareit">VPH-DARE@IT</h2>
+<p>The Center for Computational Imaging and Simulation Technologies in Biomedicine at the
+ <a href="http://sheffield.ac.uk/">University of Sheffield</a>, is leading the âVirtual Physiological Human:
+ DementiA Research Enabled by ITâ (<a href="http://www.vph-dare.eu/">VPH-DARE@IT</a>) project,
+ which aims to provide a systematic,
+ multifactorial and multiscale modelling approach to understanding dementia onset and
+ progression and enable more objective, earlier,
+ predictive and individualised diagnoses and prognoses of dementias to cope with the challenge of an ageing European society.
+ See <a href="http://www.vph-dare.eu/">http://www.vph-dare.eu/</a> for more details.</p>
+<p>The project will use <a href="http://vph-share.eu/">VPH-SHARE</a> infrastructure and
+ the GIMIAS software along with Taverna Workbench and Taverna Server technology for the execution and
+ composition of medical simulation workflows.
+These workflows will be focused on the analysis of medical data from thousands of individuals and populations;
+ as well as genetic, biochemical and metabolic pathway models.
+The results of the analysis aim to support highly innovative clinical decision systems for
+ fighting the colossal health and societal burden resulting from dementias.</p>
+<p><a name="analysis-of-anthrax-bacterium"></a></p>
+<h2 id="analysis-of-anthrax-bacterium">Analysis of anthrax bacterium</h2>
+<p>Taverna has been used by Anil Wipat and others to automate a series of analyses on all the proteins
+ produced by a bacterium to create, by a process of selection and elimination,
+ a list of secreted proteins and their properties.</p>
+<p>The secreted proteins explain why anthrax can grow in animal hosts but not in soil.</p>
+<h3 id="publications">Publications</h3>
+<p>The <a href="http://www.mygrid.org.uk/outreach/publications/craddock2006/">paper</a>
+ <em>e-Science Tools For The Genomic Scale Characterisation Of Bacterial Secreted Proteins</em>
+ by Craddock et al. gives an overview of this work.</p>
+<p><a name="trypanosomiasis"></a></p>
+<h2 id="trypanosomiasis-sleeping-sickness">Trypanosomiasis (sleeping sickness)</h2>
+<p>One of the major goals of biology, and consequently bioinformatics,
+ is to successfully bridge the gap between genotype and phenotype.
+Microarray and Quantitative Trait Loci data are increasingly used to aid in the discovery of candidate genes
+ that might be responsible for phenotypic differences.
+In previous years, studies into genotype-phenotype correlations have been conducted manually.
+This has led to problems with regards to the identification of functional candidate genes,
+ primarily due to the scale of data being investigated and the reliance on specific expertise,
+ which may bias the investigations outcome.</p>
+<p>With the development and connection of Web services into workflows, however,
+ these large scale datasets can be processed systematically enabling detailed information to be gathered,
+ published and subsequently re-investigated,
+ enhancing the possibility of bridging the gap between genotype and phenotype using pathways.</p>
+<p>So far this investigation has highlighted the issues facing the manual analysis of microarray and QTL data,
+ and how automated approaches provide a systematic means to investigate genotype-phenotype correlations.
+We were able to illustrate how the large scale analysis of microarray gene expression and quantitative trait data,
+ investigated at the level of biological pathways,
+ enables links between genotype and phenotype to be successfully established.</p>
+<p>An example of a workflow used to gather pathway information for candidate genes from a QTL region is shown below.
+These workflows have so far been applied to two different genotype-phenotype problems:</p>
+<ul>
+<li>The study of resistance to African Trypanosomiasis in mice, infected with Trypanosoma congolen</li>
+<li>The study of immunological effects and parasite expulsion in mice infected with Trichuris muris</li>
+</ul>
+<p>Using this systematic,
+ pathway driven approach, we were able to successfully identify a candidate gene and
+ biological pathway believed to be strongly associated with resistance to African Trypanosomiasis.</p>
+<p>The workflow for performing this analysis is available on
+ <a href="http://www.myexperiment.org/workflows/16">myExperiment</a>.</p>
+<p><a href="http://www.myexperiment.org/workflows/16"><img alt="pathways_and_gene_annotations_for_qtl_phenotype_28303_3" src="/img/trypanosomiasis.jpg" /></a></p>
+<h3>Publications</h3>
+
+<p><a href="http://www.mygrid.org.uk/bibsearch-results/?bibliography_subject=trypanosomiasis">Articles and papers</a>
+ about the success of Taverna for trypanosomiasis (sleeping sickness) research.</p>
+<p><a name="graves-disease"></a></p>
+<h2 id="graves-disease">Graves disease</h2>
+<h3 id="graves-disease-scenario">Graves disease scenario</h3>
+<p>The aim of this scenario is to identify and characterise genes which are located in regions on human chromosomes
+ which show linkage to Graves disease (GD) (shown in figure below).
+GD is an autoimmune disease of the thyroid in which the immune system of an individual attacks cells
+ in the thyroid gland resulting in hyperthyroidism.
+This is caused by the stimulation of the thyrotrophin receptor by thyroid-stimulating autoantibodies secreted by
+ lymphocytes of the immune system.</p>
+<p><a href="/img/gravesdiseasescenario_1.png">
+ <img title="gravesdiseasescenario_1" src="/img/gravesdiseasescenario_1.png"
+ alt="Graves Disease Scenario" width="249" height="300" /></p>
+<h3 id="affymetrix-microarray-studies">Affymetrix microarray studies</h3>
+<p>The GD candidate genes were identified by microarray analysis.
+Affymetrix U95A arrays were probed with RNA extracted from CD4 positive lymphocytes from four GD patients
+ and four healthy controls.
+The four GD microarray datasets were then compared to the four control datasets using
+ the Affymetrix data mining tool to identify differentially expressed genes.</p>
+<h3 id="annotation-pipeline">Annotation pipeline</h3>
+<p>Over 50 genes were found to be differentially-expressed in CD4 positive lymphocytes from GD patients.
+In order to understand why these genes were expressed in lymphocytes from GD patients but not in healthy individuals,
+ the GD biologist would like to use myGrid to query public databases such as
+ EMBL, GO, HGVBASE and MEDLINE to view information about gene structure and function,
+ chromosome location, the presence of single nucleotide polymorphisms (SNPs),
+ expression control features and association with other genetic diseases.
+The experimental conditions and diseases in which the expression of the candidate genes
+ are significantly altered also need to be identified from OMIM.</p>
+<h3 id="genotype-assay-design-system">Genotype assay design system</h3>
+<p>SNPs are small (single base pair) changes genetic variations which are found in the genome amongst individuals.
+The differential expression of the candidate genes in GD individuals may be due or related to the presence of
+ SNPs associated with GD.
+The GD biologist is interested in identifying and determining the frequency of those SNPs which are found in her GD patients.</p>
+<p>Restriction fragment length polymorphism (RFLP) assays are developed to genotype SNPs in her candidate genes.
+A region flanking either side of the SNP is amplified using polymerase chain reaction (PCR).
+The amplified PCR product is digested with a suitable restriction enzyme
+ (i.e. one that will cut at one SNP allele and not the other)
+ and the products are run on agarose gels to view product size and determine the genotype.</p>
+<p>The GD biologist would like to use myGrid to:</p>
+<ul>
+<li>Query databases to retrieve SNP information associated with candidate genes.</li>
+<li>Aid in the design of primers
+ (bits of DNA which signify the start and end points of the section of the DNA sequence which she wants to amplify)
+ for the PCR experiment.</li>
+<li>Select the restriction enzyme that is specific to a particular SNP for the RFLP experiment.</li>
+</ul>
+<h3 id="3d-protein-structure-wzxhzdk11-effect-of-coding-snp-on-protein-active-site">3D protein structure & effect of coding SNP on protein active site</h3>
+<p>Any SNPs occurring in the coding regions of a candidate gene may potentially give rise to
+ a change in the amino acid sequence of the protein encoded by the gene.
+The GD biologist would like to use myGrid to:</p>
+<ul>
+<li>Query a protein structure database, e.g. PDB or MSD,
+ to determine whether a structure of the protein encoded by her candidate gene is available.
+ If so, view the protein structure to study how it relates to the function of the protein.</li>
+<li>Obtain information about the protein, e.g. its function and functional domains, by querying SWISS-PROT and InterPro.
+ Use Sheffieldâs AMBIT Web service to retrieve information about an active site whose characteristics
+ may be altered due to the presence of a coding SNP which has affected a change in the amino acid sequence
+ of the protein where the active site is encoded.</li>
+</ul>
+<p>The <a href="http://www.myexperiment.org/workflows/28">workflow</a>
+ for the Graves Disease analysis is published on <a href="http://www.myexperiment.org/">myExperiment</a>.</p>
+<h3 id="publications_1">Publications</h3>
+<p><a href="http://www.mygrid.org.uk/bibsearch-results/?bibliography_subject=graves-disease">Articles and papers</a>
+ about the success of Taverna for Graves Disease research.</p></div>
+
+ </div>
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