:::System.Net.WebException: The underlying connection was closed: The remote name could not be resolved. at System.Net.HttpWebRequest.CheckFinalStatus() at System.Net.HttpWebRequest.EndGetResponse(IAsyncResult asyncResult) at System.Net.HttpWebRequest.GetResponse() at System.Xml.XmlDownloadManager.GetNonFileStream(Uri uri, ICredentials credentials) at System.Xml.XmlDownloadManager.GetStream(Uri uri, ICredentials credentials) at System.Xml.XmlUrlResolver.GetEntity(Uri absoluteUri, String role, Type ofObjectToReturn) at System.Xml.XmlTextReader.CreateScanner() at System.Xml.XmlTextReader.Init() at System.Xml.XmlTextReader.Read() at System.Xml.XmlValidatingReader.ReadWithCollectTextToken() at System.Xml.XmlValidatingReader.Read() at System.Xml.XmlLoader.Load(XmlDocument doc, XmlReader reader, Boolean preserveWhitespace) at System.Xml.XmlDocument.Load(XmlReader reader) at System.Xml.XmlDocument.Load(String filename) at Websites.xmlList.CreateChildControls() in \\tn3\development files\development projects\websites_v7\xmllist.cs:line 307 The Bioinformatics Information portal - eposter

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Reactome - a knowledgebase of human biological pathways
Esther E Schmidt, Michael Caudy, David Croft, Bernard de Bono, Phani V Garapati, Gopal Gopinath, Marc Gillespie, Robin Haw, Bijay Jassal, Steven Jupe, Alexander Kanapin, Shahana Mahajan, Lisa Matthews, Bruce May, Gavin O’Kelly, Imre Vastrik, Guanming Wu, Ewan Birney, Peter D'Eustachio, Lincoln Stein. European Bioinformatics Institute (EBI), Cambridge, United Kingdom; Cold Spring Harbor Laboratory, Cold Spring Harbor, USA; NYU School of Medicine, New York, USA; OICR Toronto, Canada

Reactome is a manually curated knowledgebase, created and peer-reviewed by experts in their field. Its robust data model describes life processes ranging from metabolism to signal transduction and the cell cycle. As of release 28, Reactome contains 3700 human proteins in 3200 reactions. Data is cross-referenced to publicly available web-based informatics resources. Reactome features the SkyPainter tool for analysis of high-throughput datasets, and the Mart query and data retrieval tool.

Adaptive mixture filtering: an alternative to particle filtering?
Jarad Niemi, Mike West. Duke University

This poster presents adaptive mixture filtering, an improvement on Gaussian sum filters, as an alternative to particle systems for filtering in state-space models.

Adaptive mixture filtering: an alternative to particle filtering?
Jarad Niemi, Mike West. Duke University

This poster presents adaptive mixture filtering, an improvement on Gaussian sum filters, as an alternative to particle systems for filtering in state-space models.

A Web Interface for Automatic Microarray Analysis
Enrico Glaab, Jonathan M. Garibaldi, Natalio Krasnogor. Nottingham University

DNA-Microarray technology provides a diagnostic tool for studying cancer and genetic diseases, allowing the experimenter to identify disease related genes and predict the tumour type for new cell samples. However, the statistical analysis of microarray data is a time-consuming and error-prone process. To address this problem we have developed a web interface for automatic DNA-microarray analysis, ArrayMining.net, which guides the user through the analysis process and performs automatic parameter

A modular and stochastic approach to the study of gene circuits using P systems
Romero-Campero FJ, Blakes J, Cao H, Camara M, Krasnogor N.. University of Nottingham

presented at Genomes to Systems Manchester, UK March 17-19 2008

Formal informatics and machine learning for more principled systems and synthetic biology
Romero-Campero FJ, Blakes J, Camara M, Willams P, Perez-Jimenez MJ, Krasnogor N. University of Nottingham

presented at European Conference on Synthetic Biology (ESF-UB Conference in Biomedicine), Sant Feliu de Guixols, Spain, 24-29 November 2007.

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