Security-oriented data grids for microarray expression profiles

Microarray experiments are one of the key ways in which gene activity can be identified and measured thereby shedding light and understanding for example on biological processes. The BBSRC funded Grid enabled Microarray Expression Profile Search (GEMEPS) project has developed an infrastructure which allows post-genomic life science researchers to ask and answer the following questions: who has undertaken microarray experiments that are in some way similar or relevant to mine; and how similar were these relevant experiments? Given that microarray experiments are expensive to undertake and may possess crucial information for future exploitation (both academically and commercially), scientists are wary of allowing unrestricted access to their data by the wider community until fully exploited locally. A key requirement is thus to have fine grained security that is easy to establish and simple (or ideally transparent) to use across inter-institutional virtual organisations. In this paper we present an enhanced security-oriented data Grid infrastructure that supports the definition of these kinds of queries and the analysis and comparison of microarray experiment results

Systems approaches and algorithms for discovery of combinatorial therapies

Effective therapy of complex diseases requires control of highly non-linear complex networks that remain incompletely characterized. In particular, drug intervention can be seen as control of signaling in cellular networks. Identification of control parameters presents an extreme challenge due to the combinatorial explosion of control possibilities in combination therapy and to the incomplete knowledge of the systems biology of cells. In this review paper we describe the main current and proposed approaches to the design of combinatorial therapies, including the empirical methods used now by clinicians and alternative approaches suggested recently by several authors. New approaches for designing combinations arising from systems biology are described. We discuss in special detail the design of algorithms that identify optimal control parameters in cellular networks based on a quantitative characterization of control landscapes, maximizing utilization of incomplete knowledge of the state and structure of intracellular networks. The use of new technology for high-throughput measurements is key to these new approaches to combination therapy and essential for the characterization of control landscapes and implementation of the algorithms. Combinatorial optimization in medical therapy is also compared with the combinatorial optimization of engineering and materials science and similarities and differences are delineated.Comment: 25 page

Penguins Search Optimisation Algorithm for Association Rules Mining

Association Rules Mining (ARM) is one of the most popular and well-known approaches for the decision-making process. All existing ARM algorithms are time consuming and generate a very large number of association rules with high overlapping. To deal with this issue, we propose a new ARM approach based on penguins search optimisation algorithm (Pe-ARM for short). Moreover, an efficient measure is incorporated into the main process to evaluate the amount of overlapping among the generated rules. The proposed approach also ensures a good diversification over the whole solutions space. To demonstrate the effectiveness of the proposed approach, several experiments have been carried out on different datasets and specifically on the biological ones. The results reveal that the proposed approach outperforms the well-known ARM algorithms in both execution time and solution quality

Visual and computational analysis of structure-activity relationships in high-throughput screening data

Novel analytic methods are required to assimilate the large volumes of structural and bioassay data generated by combinatorial chemistry and high-throughput screening programmes in the pharmaceutical and agrochemical industries. This paper reviews recent work in visualisation and data mining that can be used to develop structure-activity relationships from such chemical/biological datasets