Applications of the ACGT Master Ontology on Cancer

In this paper we present applications of the ACGT Master Ontology (MO) which is a new terminology resource for a transnational network providing data exchange in oncology, emphasizing the integration of both clinical and molecular data. The development of a new ontology was necessary due to problems with existing biomedical ontologies in oncology. The ACGT MO is a test case for the application of best practices in ontology development. This paper provides an overview of the application of the ontology within the ACGT project thus far

A Molecular Biology Database Digest

Computational Biology or Bioinformatics has been defined as the application of mathematical and Computer Science methods to solving problems in Molecular Biology that require large scale data, computation, and analysis [18]. As expected, Molecular Biology databases play an essential role in Computational Biology research and development. This paper introduces into current Molecular Biology databases, stressing data modeling, data acquisition, data retrieval, and the integration of Molecular Biology data from different sources. This paper is primarily intended for an audience of computer scientists with a limited background in Biology

From access and integration to mining of secure genomic data sets across the grid

The UK Department of Trade and Industry (DTI) funded BRIDGES project (Biomedical Research Informatics Delivered by Grid Enabled Services) has developed a Grid infrastructure to support cardiovascular research. This includes the provision of a compute Grid and a data Grid infrastructure with security at its heart. In this paper we focus on the BRIDGES data Grid. A primary aim of the BRIDGES data Grid is to help control the complexity in access to and integration of a myriad of genomic data sets through simple Grid based tools. We outline these tools, how they are delivered to the end user scientists. We also describe how these tools are to be extended in the BBSRC funded Grid Enabled Microarray Expression Profile Search (GEMEPS) to support a richer vocabulary of search capabilities to support mining of microarray data sets. As with BRIDGES, fine grain Grid security underpins GEMEPS

Data Workflow - A Workflow Model for Continuous Data Processing

Online data or streaming data are getting more and more important for enterprise information systems, e.g. by integrating sensor data and workflows. The continuous flow of data provided e.g. by sensors requires new workflow models addressing the data perspective of these applications, since continuous data is potentially infinite while business process instances are always finite.\ud In this paper a formal workflow model is proposed with data driven coordination and explicating properties of the continuous data processing. These properties can be used to optimize data workflows, i.e., reducing the computational power for processing the workflows in an engine by reusing intermediate processing results in several workflows

Introducing realist ontology for the representation of adverse events

The goal of the REMINE project is to build a high performance prediction, detection and monitoring platform for managing Risks against Patient Safety (RAPS). Part of the work involves developing in ontology enabling computer-assisted RAPS decision support on the basis of the disease history of a patient as documented in a hospital information system. A requirement of the ontology is to contain a representation for what is commonly referred to by the term 'adverse event', one challenge being that distinct authoritative sources define this term in different and context-dependent ways. The presence of some common ground in all definitions is, however, obvious. Using the analytical principles underlying Basic Formal Ontology and Referent Tracking, both developed in the tradition of philosophical realism, we propose a formal representation of this common ground which combines a reference ontology consisting exclusively of representations of universals and an application ontology which consists representations of defined classes. We argue that what in most cases is referred to by means of the term 'adverse event' - when used generically - is a defined class rather than a universal. In favour of the conception of adverse events as forming a defined class are the arguments that (1) there is no definition for 'adverse event' that carves out a collection of particulars which constitutes the extension of a universal, and (2) the majority of definitions require adverse events to be (variably) the result of some observation, assessment or (absence of) expectation, thereby giving these entities a nominal or epistemological flavour

Biomedical data integration in computational drug design and bioinformatics

[Abstract In recent years, in the post genomic era, more and more data is being generated by biological high throughput technologies, such as proteomics and transcriptomics. This omics data can be very useful, but the real challenge is to analyze all this data, as a whole, after integrating it. Biomedical data integration enables making queries to different, heterogeneous and distributed biomedical data sources. Data integration solutions can be very useful not only in the context of drug design, but also in biomedical information retrieval, clinical diagnosis, system biology, etc. In this review, we analyze the most common approaches to biomedical data integration, such as federated databases, data warehousing, multi-agent systems and semantic technology, as well as the solutions developed using these approaches in the past few years.Red Gallega de Investigación sobre Cáncer Colorrectal; Ref. 2009/58Programa Iberoamericano de Ciencia y Tecnología para el Desarrollo; 209RT- 0366Instituto de Salud Carlos III; PIO52048Instituto de Salud Carlos III; RD07/0067/0005Ministerio de Industria, Turismo y Comercio; TSI-020110-2009-

Version control of pathway models using XML patches

<p>Background: Computational modelling has become an important tool in understanding biological systems such as signalling pathways. With an increase in size complexity of models comes a need for techniques to manage model versions and their relationship to one another. Model version control for pathway models shares some of the features of software version control but has a number of differences that warrant a specific solution.</p> <p>Results: We present a model version control method, along with a prototype implementation, based on XML patches. We show its application to the EGF/RAS/RAF pathway.</p> <p>Conclusion: Our method allows quick and convenient storage of a wide range of model variations and enables a thorough explanation of these variations. Trying to produce these results without such methods results in slow and cumbersome development that is prone to frustration and human error.</p&gt

An object-oriented framework to organize genomic data

Bioinformatics resources should provide simple and flexible support for genomics research. A huge amount of gene mapping data, micro-array expression data, expressed sequence tags (EST), BAC sequence data and genome sequence data are already, or will soon be available for a number of livestock species. These species will have different requirements compared to typical biomedical model organisms and will need an informatics framework to deal with the data. In term of exploring complex-intertwined genomic data, the way to organize them will be addressed in this study. Therefore, we investigated two issues in this study: one is an independent informatics framework including both back end and front end; another is how an informatics framework simplifies the user interface to explore data. We have developed a fundamental informatics framework that makes it easy to organize and manipulate the complex relations between genomic data, and allow for query results to be presented via a user friendly web interface. A genome object-oriented framework (GOOF) was proposed with object-oriented Java technology and is independent of any database system. This framework seamlessly links the database system and web presentation components. The data models of GOOF collect the data relationships in order to provide users with access to relations across different types of data, meaning that users avoid constructing queries within the interface layer. Moreover, the module-based interface provided by GOOF could allow different users to access data in different interfaces and ways. In another words, GOOF not only gives a whole solution to informatics infrastructure, but also simplifies the organization of data modeling and presentation. In order to be a fast development solution, GOOF provides an automatic code engine by using meta-programming facilities in Java, which could allow users to generate a large amount of routine program codes. Moreover, the pre-built data layer in GOOF connecting with Chado simplifies the process to manage genomic data in the Chado schema. In summary, we studied the way to model genomic data into an informatics framework, a one-stop approach, to organize the data and addressed how GOOF constructs a bioinformatics infrastructure for users to access genomic data