Web-enabled knowledge-based analysis of genetic data

We present a web-based implementation of GenePath, an intelligent assistant tool for data analysis in functional genomics. GenePath considers mutant data and uses expert-defined patterns to find gene-to-gene or gene-to-outcome relations. It presents the results of analysis as genetic networks, wherein a set of genes has various influence on one another and on a biological outcome. In the paper, we particularly focus on its web-based interface and explanation mechanisms

BCAS: A Web-enabled and GIS-based Decision Support System for the Diagnosis and Treatment of Breast Cancer

For decades, geographical variations in cancer rates have been observed but the precise determinants of such geographic differences in breast cancer development are unclear. Various statistical models have been proposed. Applications of these models, however, require that the data be assembled from a variety of sources, converted into the statistical models’ parameters and delivered effectively to researchers and policy makers. A web-enabled and GIS-based system can be developed to provide the needed functionality. This article overviews the conceptual web-enabled and GIS-based system (BCAS), illustrates the system’s use in diagnosing and treating breast cancer and examines the potential benefits and implications for breast cancer research and practice

BioNessie - a grid enabled biochemical networks simulation environment

The simulation of biochemical networks provides insight and understanding about the underlying biochemical processes and pathways used by cells and organisms. BioNessie is a biochemical network simulator which has been developed at the University of Glasgow. This paper describes the simulator and focuses in particular on how it has been extended to benefit from a wide variety of high performance compute resources across the UK through Grid technologies to support larger scale simulations

'BioNessie(G) - a grid enabled biochemical networks simulation environment

The simulation of biochemical networks provides insight and understanding about the underlying biochemical processes and pathways used by cells and organisms. BioNessie is a biochemical network simulator which has been developed at the University of Glasgow. This paper describes the simulator and focuses in particular on how it has been extended to benefit from a wide variety of high performance compute resources across the UK through Grid technologies to support larger scale simulations

Fostering innovation in a small open economy: The case of the New Zealand biotechnology sector

The New Zealand Biotechnology sector is worthy of study for several reasons. While there is a large and growing international literature on economic aspects of biotechnology innovation these studies concentrate on the United States and Europe. The New Zealand biotechnology sector may be expected to develop along a different trajectory as a consequence of a markedly different set of initial and framework conditions. Government has indicated a strong interest in fostering innovation and aims to concentrate on selected areas where New Zealand may be able to develop a new comparative advantage. One such area is biotechnology, which would build on New Zealand’s existing comparative advantage in the primary sector (dairy, forestry, meat, wool and horticulture). This paper describes the preliminary results of an ongoing study that aims to fill some of the gaps in our knowledge of innovation processes in New Zealand while using the international literature as a benchmark. The paper focuses on the drivers of innovation in the biotechnology sector; the role of networks and other linkages; the role of government and industry, the role of human and venture capital, and data from patenting

A Decision Technology System To Advance the Diagnosis and Treatment of Breast Cancer

Geographical variations in cancer rates have been observed for decades. Described spatial patterns and trends have provided clues for generating hypotheses about the etiology of cancer. For breast cancer, investigators have demonstrated that some variation can be explained by differences in the population distribution of known breast cancer risk factors such as menstrual and reproductive variables (Laden, Spiegelman, and Neas, 1997; Robbins, Bescianini, and Kelsey, 1997; Sturgeon, Schairer, and Gail, 1995). However, regional patterns also may reflect the effects of Workshop on Hormones, Hormone Metabolism, Environment, and Breast Cancer (1995): (a) environmental hazards (such as air and water pollution), (b) demographics and the lifestyle of a mobile population, (c) subgroup susceptibility, (d) changes and advances in medical practice and healthcare management, and (e) other factors. To accurately measure breast cancer risk in individuals and population groups, it is necessary to singly and jointly assess the association between such risk and the hypothesized factors. Various statistical models will be needed to determine the potential relationships between breast cancer development and estimated exposures to environmental contamination. To apply the models, data must be assembled from a variety of sources, converted into the statistical models’ parameters, and delivered effectively to researchers and policy makers. A Web-enabled decision technology system can be developed to provide the needed functionality. This chapter will present a conceptual architecture for such a decision technology system. First, there will be a brief overview of a typical geographical analysis. Next, the chapter will present the conceptual Web-based decision technology system and illustrate how the system can assist users in diagnosing and treating breast cancer. The chapter will conclude with an examination of the potential benefits from system use and the implications for breast cancer research and practice

Biodigital publics: personal genomes as digital media artifacts

The recent proliferation of personal genomics and direct-to-consumer (DTC) genomics has attracted much attention and publicity. Concern around these developments has mainly focused on issues of biomedical regulation and hinged on questions of how people understand genomic information as biomedical and what meaning they make of it. However, this publicity amplifies genome sequences which are also made as internet texts and, as such, they generate new reading publics. The practices around the generation, circulation and reading of genome scans do not just raise questions about biomedical regulation, they also provide the focus for an exploration of how contemporary public participation in genomics works. These issues around the public features of DTC genomic testing can be pursued through a close examination of the modes of one of the best known providers—23andMe. In fact, genome sequences circulate as digital artefacts and, hence, people are addressed by them. They are read as texts, annotated and written about in browsers, blogs and wikis. This activity also yields content for media coverage which addresses an indefinite public in line with Michael Warner’s conceptualisation of publics. Digital genomic texts promise empowerment, personalisation and community, but this promise may obscure the compliance and proscription associated with these forms. The kinds of interaction here can be compared to those analysed by Andrew Barry. Direct-to-consumer genetics companies are part of a network providing an infrastructure for genomic reading publics and this network can be mapped and examined to demonstrate the ways in which this formation both exacerbates inequalities and offers possibilities for participation in biodigital culture

Grid infrastructures for secure access to and use of bioinformatics data: experiences from the BRIDGES project

The BRIDGES project was funded by the UK Department of Trade and Industry (DTI) to address the needs of cardiovascular research scientists investigating the genetic causes of hypertension as part of the Wellcome Trust funded (£4.34M) cardiovascular functional genomics (CFG) project. Security was at the heart of the BRIDGES project and an advanced data and compute grid infrastructure incorporating latest grid authorisation technologies was developed and delivered to the scientists. We outline these grid infrastructures and describe the perceived security requirements at the project start including data classifications and how these evolved throughout the lifetime of the project. The uptake and adoption of the project results are also presented along with the challenges that must be overcome to support the secure exchange of life science data sets. We also present how we will use the BRIDGES experiences in future projects at the National e-Science Centre

A proposal for a coordinated effort for the determination of brainwide neuroanatomical connectivity in model organisms at a mesoscopic scale

In this era of complete genomes, our knowledge of neuroanatomical circuitry remains surprisingly sparse. Such knowledge is however critical both for basic and clinical research into brain function. Here we advocate for a concerted effort to fill this gap, through systematic, experimental mapping of neural circuits at a mesoscopic scale of resolution suitable for comprehensive, brain-wide coverage, using injections of tracers or viral vectors. We detail the scientific and medical rationale and briefly review existing knowledge and experimental techniques. We define a set of desiderata, including brain-wide coverage; validated and extensible experimental techniques suitable for standardization and automation; centralized, open access data repository; compatibility with existing resources, and tractability with current informatics technology. We discuss a hypothetical but tractable plan for mouse, additional efforts for the macaque, and technique development for human. We estimate that the mouse connectivity project could be completed within five years with a comparatively modest budget.Comment: 41 page