Matthew Poole

Bio: Matthew Poole is an academic researcher from University of Portsmouth. The author has contributed to research in topic(s): Particle swarm optimization & Swarm intelligence. The author has an hindex of 10, co-authored 20 publication(s) receiving 338 citation(s). Previous affiliations of Matthew Poole include Swansea University & University of Leeds.

A Swarm Intelligence Framework for Reconstructing Gene Networks: Searching for Biologically Plausible Architectures

Abstract: In this paper, we investigate the problem of reverse engineering the topology of gene regulatory networks from temporal gene expression data. We adopt a computational intelligence approach comprising swarm intelligence techniques, namely particle swarm optimization (PSO) and ant colony optimization (ACO). In addition, the recurrent neural network (RNN) formalism is employed for modeling the dynamical behavior of gene regulatory systems. More specifically, ACO is used for searching the discrete space of network architectures and PSO for searching the corresponding continuous space of RNN model parameters. We propose a novel solution construction process in the context of ACO for generating biologically plausible candidate architectures. The objective is to concentrate the search effort into areas of the structure space that contain architectures which are feasible in terms of their topological resemblance to real-world networks. The proposed framework is initially applied to the reconstruction of a small artificial network that has previously been studied in the context of gene network reverse engineering. Subsequently, we consider an artificial data set with added noise for reconstructing a subnetwork of the genetic interaction network of S. cerevisiae (yeast). Finally, the framework is applied to a real-world data set for reverse engineering the SOS response system of the bacterium Escherichia coli. Results demonstrate the relative advantage of utilizing problem-specific knowledge regarding biologically plausible structural properties of gene networks over conducting a problem-agnostic search in the vast space of network architectures.

Particle swarm optimization with an oscillating inertia weight

Abstract: In this paper, we propose an alternative strategy of adapting the inertia weight parameter during the course of particle swarm optimization, by means of a non-monotonic inertia weight function of time. Results demonstrate that an oscillating inertia weight function is competitive and in some cases better than established inertia weight functions, in terms of consistency and speed of convergence.

Coupled map lattices as computational systems

Abstract: The coupled map lattice (CML) as a mathematical model for a computer is considered. Using the theory of synchronous concurrent algorithms, it is shown that the CML is a valid new model for a parallel deterministic analog machine, but that, in principle, such a CML computer does not generate computations that cannot be reproduced by the standard mathematical models for computing on real numbers. The analysis is based on new general mathematical definitions of CMLs, and an axiomatic approach to determining which models of computation can be used to simulate CMLs.

Resistance gene expression determines the in vitro chemosensitivity of non-small cell lung cancer (NSCLC)

Abstract: Background: NSCLC exhibits considerable heterogeneity in its sensitivity to chemotherapy and similar heterogeneity is noted in vitro in a variety of model systems. This study has tested the hypothesis that the molecular basis of the observed in vitro chemosensitivity of NSCLC lies within the known resistance mechanisms inherent to these patients' tumors. Methods: The chemosensitivity of a series of 49 NSCLC tumors was assessed using the ATP-based tumor chemosensitivity assay (ATP-TCA) and compared with quantitative expression of resistance genes measured by RT-PCR in a Taqman Array™ following extraction of RNA from formalin-fixed paraffin-embedded (FFPE) tissue. Results: There was considerable heterogeneity between tumors within the ATP-TCA, and while this showed no direct correlation with individual gene expression, there was strong correlation of multi-gene signatures for many of the single agents and combinations tested. For instance, docetaxel activity showed some dependence on the expression of drug pumps, while cisplatin activity showed some dependence on DNA repair enzyme expression. Activity of both drugs was influenced more strongly still by the expression of anti- and pro-apoptotic genes by the tumor for both docetaxel and cisplatin. The doublet combinations of cisplatin with gemcitabine and cisplatin with docetaxel showed gene expression signatures incorporating resistance mechanisms for both agents. Conclusion: Genes predicted to be involved in known mechanisms drug sensitivity and resistance correlate well with in vitro chemosensitivity and may allow the definition of predictive signatures to guide individualized chemotherapy in lung cancer.

The molecular basis of the chemosensitivity of metastatic cutaneous melanoma to chemotherapy

Abstract: Background Chemotherapy benefits relatively few patients with cutaneous melanoma. The assessment of tumour chemosensitivity by the ATP-based tumour chemosensitivity assay (ATP-TCA) has shown strong correlation with outcome in cutaneous melanoma, but requires fresh tissue and dedicated laboratory facilities. Aim To examine whether the results of the ATP-TCA correlate with the expression of genes known to be involved in resistance to chemotherapy, based on the hypothesis that the molecular basis of chemosensitivity lies within known drug resistance mechanisms. Method The chemosensitivity of 47 cutaneous melanomas was assessed using the ATP-TCA and correlated with quantitative expression of 93 resistance genes measured by quantitative reverse transcriptase PCR (qRT-PCR) in a Taqman Array after extraction of total RNA from formalin-fixed paraffin-embedded tissue. Results Drugs susceptible to particular resistance mechanisms showed good correlation with genes linked to these mechanisms using signatures of up to 17 genes. Comparison of these signatures for DTIC, treosulfan and cisplatin showed several genes in common. HSP70 , at least one human epidermal growth factor receptor, genes involved in apoptosis ( IAP2 , PTEN ) and DNA repair ( ERCC1 , XPA , XRCC1 , XRCC6 ) were present for these agents, as well as genes involved in the regulation of proliferation ( Ki67 , p21, p27). The combinations tested included genes represented in the single agent signatures. Conclusions These data suggest that melanoma chemosensitivity is influenced by known resistance mechanisms, including susceptibility to apoptosis. Use of a candidate gene approach may increase understanding of the mechanisms underlying chemosensitivity to drugs active against melanoma and provide signatures with predictive value.

Inertia Weight strategies in Particle Swarm Optimization

Abstract: Particle Swarm Optimization is a popular heuristic search algorithm which is inspired by the social learning of birds or fishes. It is a swarm intelligence technique for optimization developed by Eberhart and Kennedy [1] in 1995. Inertia weight is an important parameter in PSO, which significantly affects the convergence and exploration-exploitation trade-off in PSO process. Since inception of Inertia Weight in PSO, a large number of variations of Inertia Weight strategy have been proposed. In order to propose one or more than one Inertia Weight strategies which are efficient than others, this paper studies 15 relatively recent and popular Inertia Weight strategies and compares their performance on 05 optimization test problems.

A survey of stream processing

Abstract: Stream processing is a term that is used widely in the literature to describe a variety of systems. We present an overview of the historical development of stream processing and a detailed discussion of the different languages and techniques for programming with streams that can be found in the literature. This includes an analysis of dataflow, specialized functional and logic programming with streams, reactive systems, signal processing systems, and the use of streams in the design and verification of hardware.

Epigenetic Resensitization to Platinum in Ovarian Cancer

Abstract: Preclinical studies have shown that hypomethylating agents reverse platinum resistance in ovarian cancer. In this phase II clinical trial, based upon the results of our phase I dose defining study, we tested the clinical and biologic activity of low-dose decitabine administered before carboplatin in platinum-resistant ovarian cancer patients. Among 17 patients with heavily pretreated and platinum-resistant ovarian cancer, the regimen induced a 35% objective response rate (RR) and progression-free survival (PFS) of 10.2 months, with nine patients (53%) free of progression at 6 months. Global and gene-specific DNA demethylation was achieved in peripheral blood mononuclear cells and tumors. The number of demethylated genes was greater (P < 0.05) in tumor biopsies from patients with PFS more than 6 versus less than 6 months (311 vs. 244 genes). Pathways enriched at baseline in tumors from patients with PFS more than 6 months included cytokine-cytokine receptor interactions, drug transporters, and mitogen-activated protein kinase, toll-like receptor and Jak-STAT signaling pathways, whereas those enriched in demethylated genes after decitabine treatment included pathways involved in cancer, Wnt signaling, and apoptosis (P < 0.01). Demethylation of MLH1, RASSF1A, HOXA10, and HOXA11 in tumors positively correlated with PFS (P < 0.05). Together, the results of this study suggest that low-dose decitabine altered DNA methylation of genes and cancer pathways, restoring sensitivity to carboplatin in patients with heavily pretreated ovarian cancer and resulting in a high RR and prolonged PFS.

Purinergic signalling and cancer

Abstract: Receptors for extracellular nucleotides are widely expressed by mammalian cells. They mediate a large array of responses ranging from growth stimulation to apoptosis, from chemotaxis to cell differentiation and from nociception to cytokine release, as well as neurotransmission. Pharma industry is involved in the development and clinical testing of drugs selectively targeting the different P1 nucleoside and P2 nucleotide receptor subtypes. As described in detail in the present review, P2 receptors are expressed by all tumours, in some cases to a very high level. Activation or inhibition of selected P2 receptor subtypes brings about cancer cell death or growth inhibition. The field has been largely neglected by current research in oncology, yet the evidence presented in this review, most of which is based on in vitro studies, although with a limited amount from in vivo experiments and human studies, warrants further efforts to explore the therapeutic potential of purinoceptor targeting in cancer.

Computational biology of the heart , edited by Alexander V. Panfilov and Arun V. Holden. Pp. 416. £70. 1997. ISBN 0 471 96020 9 (John Wiley & Sons).

Abstract: Partial table of contents: Modelling Cardiac Excitation and Excitability (M. Boyett, et al.). Modelling Propagation in Excitable Media (A. Holden & A. Panfilov). Rotors, Fibrillation and Dimensionality (A. Winfree). A Mathematical Model of Cardiac Anatomy (P. Hunter, et al.). Finite Element Methods for Modelling Impulse Propagation in the Heart (J. Rogers, et al.). The Effects of Geometry and Fibre Orientation on Propagation and Extracellular Potentials in Myocardium (J. Keener & A. Panfilov). Forward and Inverse Problems in Electrocardiography (A. van Oosterom). Computational Electromechanics of the Heart (P. Hunter, et al.). Index.