Norman W. Paton
University of Manchester
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ACM Computing Surveys | 1999
Norman W. Paton; Oscar Díaz
Integrating a production rules facility into a database system provides a uniform mechanism for a number of advanced database features including integrity constraint enforcement, derived data maintenance, triggers, alerters, protection, version control, and others. In addition, a database system with rule processing capabilities provides a useful platform for large and effcient knowledge-base and expert systems. Database systems with production rules are referred to as active database systems, and the of active database systems has indeed been active. This chapter summarizes current work in active database systems; topics covered include active database rule models and languages, rule execution semantics, and implementation issues. 0
Archive | 1998
Norman W. Paton; F. Schneider; D. Gries
From the Publisher: Active rules provide a new and important method for developing database applications, and the subject is seeing an increasing amount of attention from commercial database companies. This book provides a timely survey of the field from the point of view of some of the subjects most active researchers. Database researchers and developers will find this book provides a valuable overview of the design and use of active database systems.
Nature Biotechnology | 2004
Helen Jenkins; Nigel Hardy; Manfred Beckmann; John Draper; A. R. Smith; Janet Taylor; Oliver Fiehn; Royston Goodacre; Raoul J. Bino; Robert D. Hall; Joachim Kopka; Geoffrey A. Lane; Markus Lange; Jang R Liu; Pedro Mendes; Basil J. Nikolau; Stephen G. Oliver; Norman W. Paton; Sue Rhee; Ute Roessner-Tunali; Kazuki Saito; Jørn Smedsgaard; Lloyd W. Sumner; Trevor L. Wang; Sean Walsh; Eve Syrkin Wurtele; Douglas B. Kell
The study of the metabolite complement of biological samples, known as metabolomics, is creating large amounts of data, and support for handling these data sets is required to facilitate meaningful analyses that will answer biological questions. We present a data model for plant metabolomics known as ArMet (architecture for metabolomics). It encompasses the entire experimental time line from experiment definition and description of biological source material, through sample growth and preparation to the results of chemical analysis. Such formal data descriptions, which specify the full experimental context, enable principled comparison of data sets, allow proper interpretation of experimental results, permit the repetition of experiments and provide a basis for the design of systems for data storage and transmission. The current design and example implementations are freely available (http://www.armet.org/). We seek to advance discussion and community adoption of a standard for metabolomics, which would promote principled collection, storage and transmission of experiment data.
Nature Biotechnology | 2003
Chris F. Taylor; Norman W. Paton; Kevin L. Garwood; Paul Kirby; David Stead; Zhikang Yin; Eric W. Deutsch; Laura Selway; Janet Walker; Isabel Riba-Garcia; Shabaz Mohammed; Michael J. Deery; Julie Howard; Tom P. J. Dunkley; Ruedi Aebersold; Douglas B. Kell; Kathryn S. Lilley; Peter Roepstorff; John R. Yates; Andy Brass; Alistair J. P. Brown; Phil Cash; Simon J. Gaskell; Simon J. Hubbard; Stephen G. Oliver
Both the generation and the analysis of proteome data are becoming increasingly widespread, and the field of proteomics is moving incrementally toward high-throughput approaches. Techniques are also increasing in complexity as the relevant technologies evolve. A standard representation of both the methods used and the data generated in proteomics experiments, analogous to that of the MIAME (minimum information about a microarray experiment) guidelines for transcriptomics, and the associated MAGE (microarray gene expression) object model and XML (extensible markup language) implementation, has yet to emerge. This hinders the handling, exchange, and dissemination of proteomics data. Here, we present a UML (unified modeling language) approach to proteomics experimental data, describe XML and SQL (structured query language) implementations of that model, and discuss capture, storage, and dissemination strategies. These make explicit what data might be most usefully captured about proteomics experiments and provide complementary routes toward the implementation of a proteome repository.
Bioinformatics | 1999
Patricia G. Baker; Carole A. Goble; Sean Bechhofer; Norman W. Paton; Robert Stevens; Andy Brass
MOTIVATION An ontology of biological terminology provides a model of biological concepts that can be used to form a semantic framework for many data storage, retrieval and analysis tasks. Such a semantic framework could be used to underpin a range of important bioinformatics tasks, such as the querying of heterogeneous bioinformatics sources or the systematic annotation of experimental results. RESULTS This paper provides an overview of an ontology [the Transparent Access to Multiple Biological Information Sources (TAMBIS) ontology or TaO] that describes a wide range of bioinformatics concepts. The present paper describes the mechanisms used for delivering the ontology and discusses the ontologys design and organization, which are crucial for maintaining the coherence of a large collection of concepts and their relationships. AVAILABILITY The TAMBIS system, which uses a subset of the TaO described here, is accessible over the Web via http://img.cs.man.ac.uk/tambis (although in the first instance, we will use a password mechanism to limit the load on our server). The complete model is also available on the Web at the above URL.
Journal of Biology | 2007
Juan I. Castrillo; Leo Zeef; David C. Hoyle; Nianshu Zhang; Andrew Hayes; David C. J. Gardner; Michael Cornell; June Petty; Luke Hakes; Leanne Wardleworth; Bharat Rash; Marie Brown; Warwick B. Dunn; David Broadhurst; Kerry O'Donoghue; Svenja Hester; Tom P. J. Dunkley; Sarah R. Hart; Neil Swainston; Peter Li; Simon J. Gaskell; Norman W. Paton; Kathryn S. Lilley; Douglas B. Kell; Stephen G. Oliver
BACKGROUND Cell growth underlies many key cellular and developmental processes, yet a limited number of studies have been carried out on cell-growth regulation. Comprehensive studies at the transcriptional, proteomic and metabolic levels under defined controlled conditions are currently lacking. RESULTS Metabolic control analysis is being exploited in a systems biology study of the eukaryotic cell. Using chemostat culture, we have measured the impact of changes in flux (growth rate) on the transcriptome, proteome, endometabolome and exometabolome of the yeast Saccharomyces cerevisiae. Each functional genomic level shows clear growth-rate-associated trends and discriminates between carbon-sufficient and carbon-limited conditions. Genes consistently and significantly upregulated with increasing growth rate are frequently essential and encode evolutionarily conserved proteins of known function that participate in many protein-protein interactions. In contrast, more unknown, and fewer essential, genes are downregulated with increasing growth rate; their protein products rarely interact with one another. A large proportion of yeast genes under positive growth-rate control share orthologs with other eukaryotes, including humans. Significantly, transcription of genes encoding components of the TOR complex (a major controller of eukaryotic cell growth) is not subject to growth-rate regulation. Moreover, integrative studies reveal the extent and importance of post-transcriptional control, patterns of control of metabolic fluxes at the level of enzyme synthesis, and the relevance of specific enzymatic reactions in the control of metabolic fluxes during cell growth. CONCLUSION This work constitutes a first comprehensive systems biology study on growth-rate control in the eukaryotic cell. The results have direct implications for advanced studies on cell growth, in vivo regulation of metabolic fluxes for comprehensive metabolic engineering, and for the design of genome-scale systems biology models of the eukaryotic cell.
PLOS ONE | 2008
Darren M. Soanes; Intikhab Alam; Mike Cornell; Han Min Wong; Cornelia Hedeler; Norman W. Paton; Magnus Rattray; Simon J. Hubbard; Stephen G. Oliver; Nicholas J. Talbot
Fungi and oomycetes are the causal agents of many of the most serious diseases of plants. Here we report a detailed comparative analysis of the genome sequences of thirty-six species of fungi and oomycetes, including seven plant pathogenic species, that aims to explore the common genetic features associated with plant disease-causing species. The predicted translational products of each genome have been clustered into groups of potential orthologues using Markov Chain Clustering and the data integrated into the e-Fungi object-oriented data warehouse (http://www.e-fungi.org.uk/). Analysis of the species distribution of members of these clusters has identified proteins that are specific to filamentous fungal species and a group of proteins found only in plant pathogens. By comparing the gene inventories of filamentous, ascomycetous phytopathogenic and free-living species of fungi, we have identified a set of gene families that appear to have expanded during the evolution of phytopathogens and may therefore serve important roles in plant disease. We have also characterised the predicted set of secreted proteins encoded by each genome and identified a set of protein families which are significantly over-represented in the secretomes of plant pathogenic fungi, including putative effector proteins that might perturb host cell biology during plant infection. The results demonstrate the potential of comparative genome analysis for exploring the evolution of eukaryotic microbial pathogenesis.
grid computing | 2002
James Smith; Anastasios Gounaris; Paul Watson; Norman W. Paton; Alvaro A. A. Fernandes; Rizos Sakellariou
Distributed query processing (DQP) has been widely used in data intensive applications where data of relevance to users is stored in multiple locations. This paper argues: (i) that DQP can be important in the Grid, as a means of providing high-level, declarative languages for integrating data access and analysis; and (ii) that the Grid provides resource management facilities that are useful to developers of DQP systems. As well as discussing and illustrating how DQP technologies can be deployed within the Grid, the paper describes a prototype implementation of a DQP system running over Globus.
statistical and scientific database management | 1999
Norman W. Paton; Robert Stevens; Patricia G. Baker; Carole A. Goble; Sean Bechhofer; Andy Brass
Conducting bioinformatic analyses involves biologists in expressing requests over a range of highly heterogeneous information sources and software tools. Such activities are laborious, and require detailed knowledge of the data structures and call interfaces of the different sources. The TAMBIS (Transparent Access to Multiple Bioinformatics Information Sources) project seeks to make the diversity in data structures, call interfaces and locations of bioinformatics sources transparent to users. In TAMBIS, queries are expressed in terms of an ontology implemented using a description logic, and queries over the ontology are rewritten to a middleware level for execution over the diverse sources. The paper describes query processing in TAMBIS, focusing in particular on the way source-independent concepts in the ontology are related to source-dependent middleware calls, and describing how the planner identifies efficient ways of evaluating user queries.
IEEE Software | 2003
P.P. da Silva; Norman W. Paton
Although user interfaces represent an essential part of software systems, the Unified Modeling Language )UML) seems to have been developed with little specific attention given to user interface issues. Several researchers have investigated integrating interface modeling techniques with UML. In UML, one models tasks using extended activity diagrams rather than by incorporating a completely new notation into UML. UMLi also addresses the relationships between use cases, tasks, and views, and thoroughly addresses the relationship between tasks and the data on which they act. UMLi is probably the most technically mature proposal for interface development in UML.