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Matthew Poole

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

Papers
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Journal ArticleDOI
TL;DR: 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.
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.

59 citations

Proceedings ArticleDOI
08 Jul 2009
TL;DR: 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.
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.

54 citations

Journal ArticleDOI
01 Jul 1992-Chaos
TL;DR: 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.
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.

38 citations

Journal ArticleDOI
TL;DR: 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.
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.

37 citations

Proceedings ArticleDOI
18 Dec 2019
TL;DR: The report of an ITiCSE working group that gathered information on pass rates from several institutions to determine whether prior results can be confirmed, and conducted a detailed comparison of pass rates in introductory programming courses with passes in introductory courses in other STEM disciplines found that pass rates appear to average about 75; that there is some evidence that they sit at the low end of the range of pass rate in introductory STEM courses.
Abstract: Vast numbers of publications in computing education begin with the premise that programming is hard to learn and hard to teach. Many papers note that failure rates in computing courses, and particularly in introductory programming courses, are higher than their institutions would like. Two distinct research projects in 2007 and 2014 concluded that average success rates in introductory programming courses world-wide were in the region of 67%, and a recent replication of the first project found an average pass rate of about 72%. The authors of those studies concluded that there was little evidence that failure rates in introductory programming were concerningly high.However, there is no absolute scale by which pass or failure rates are measured, so whether a failure rate is concerningly high will depend on what that rate is compared against. As computing is typically considered to be a STEM subject, this paper considers how pass rates for introductory programming courses compare with those for other introductory STEM courses. A comparison of this sort could prove useful in demonstrating whether the pass rates are comparatively low, and if so, how widespread such findings are.This paper is the report of an ITiCSE working group that gathered information on pass rates from several institutions to determine whether prior results can be confirmed, and conducted a detailed comparison of pass rates in introductory programming courses with pass rates in introductory courses in other STEM disciplines.The group found that pass rates in introductory programming courses appear to average about 75%; that there is some evidence that they sit at the low end of the range of pass rates in introductory STEM courses; and that pass rates both in introductory programming and in other introductory STEM courses appear to have remained fairly stable over the past five years. All of these findings must be regarded with some caution, for reasons that are explained in the paper. Despite the lack of evidence that pass rates are substantially lower than in other STEM courses, there is still scope to improve the pass rates of introductory programming courses, and future research should continue to investigate ways of improving student learning in introductory programming courses.

36 citations


Cited by
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Proceedings ArticleDOI
01 Dec 2011
TL;DR: 15 relatively recent and popular Inertia Weight strategies are studied and their performance on 05 optimization test problems is compared to show which are more efficient than others.
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.

482 citations

Journal ArticleDOI
TL;DR: An analysis of the development of each of these specialized topics to determine if a general theory of stream processing has emerged is presented, including a comparison of the semantic models that are used to formalize stream based computation.
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.

334 citations

Journal ArticleDOI
TL;DR: 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.
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.

326 citations

Proceedings ArticleDOI
02 Jul 2018
TL;DR: An ITiCSE working group conducted a systematic review of the introductory programming literature to explore trends, highlight advances in knowledge over the past 15 years, and indicate possible directions for future research.
Abstract: As computing becomes a mainstream discipline embedded in the school curriculum and acts as an enabler for an increasing range of academic disciplines in higher education, the literature on introductory programming is growing. Although there have been several reviews that focus on specific aspects of introductory programming, there has been no broad overview of the literature exploring recent trends across the breadth of introductory programming. This paper is the report of an ITiCSE working group that conducted a systematic review in order to gain an overview of the introductory programming literature. Partitioning the literature into papers addressing the student, teaching, the curriculum, and assessment, we explore trends, highlight advances in knowledge over the past 15 years, and indicate possible directions for future research.

282 citations

Journal ArticleDOI
TL;DR: 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.
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.

271 citations