School of Mathematics and Statistics - Research Publications
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ItemA Bayesian method for comparing and combining binary classifiers in the absence of a gold standard.(Springer Science and Business Media LLC, 2012-07-27)BACKGROUND: Many problems in bioinformatics involve classification based on features such as sequence, structure or morphology. Given multiple classifiers, two crucial questions arise: how does their performance compare, and how can they best be combined to produce a better classifier? A classifier can be evaluated in terms of sensitivity and specificity using benchmark, or gold standard, data, that is, data for which the true classification is known. However, a gold standard is not always available. Here we demonstrate that a Bayesian model for comparing medical diagnostics without a gold standard can be successfully applied in the bioinformatics domain, to genomic scale data sets. We present a new implementation, which unlike previous implementations is applicable to any number of classifiers. We apply this model, for the first time, to the problem of finding the globally optimal logical combination of classifiers. RESULTS: We compared three classifiers of protein subcellular localisation, and evaluated our estimates of sensitivity and specificity against estimates obtained using a gold standard. The method overestimated sensitivity and specificity with only a small discrepancy, and correctly ranked the classifiers. Diagnostic tests for swine flu were then compared on a small data set. Lastly, classifiers for a genome-wide association study of macular degeneration with 541094 SNPs were analysed. In all cases, run times were feasible, and results precise. The optimal logical combination of classifiers was also determined for all three data sets. Code and data are available from http://bioinformatics.monash.edu.au/downloads/. CONCLUSIONS: The examples demonstrate the methods are suitable for both small and large data sets, applicable to the wide range of bioinformatics classification problems, and robust to dependence between classifiers. In all three test cases, the globally optimal logical combination of the classifiers was found to be their union, according to three out of four ranking criteria. We propose as a general rule of thumb that the union of classifiers will be close to optimal.
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ItemSemiglobal Practical Stability of a Class of Parameterized Networked Control Systems(IEEE, 2012-01-01)This paper studies a class of parameterized networked control systems that are designed via an emulation procedure. In the first step, a controller is designed ignoring network so that semiglobal practical stability is achieved for the closed-loop. In the second step, it is shown that if the same controller is emulated and implemented over a large class of networks, then the networked control system is also semiglobally practically asymptotically stable; in this case, the controller parameter needs to be sufficiently small and communication bandwidth sufficiently high.
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ItemCurvature-constrained directional-cost paths in the plane(SPRINGER, 2012-08-01)
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ItemExpanded Vandermonde Powers and Sum Rules for the Two-Dimensional One-Component Plasma(SPRINGER, 2012-09-01)
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ItemGradient-Constrained Minimum Networks. III. Fixed Topology(SPRINGER/PLENUM PUBLISHERS, 2012-10-01)
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ItemLinear Programming with Uncertain Data: Some Extensions to Robust Optimization(SPRINGER/PLENUM PUBLISHERS, 2012-11-01)
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ItemOn the Connectivity of Visibility Graphs(SPRINGER, 2012-10-01)The visibility graph of a finite set of points in the plane has the points as vertices and an edge between two vertices if the line segment between them contains no other points. This paper establishes bounds on the edge- and vertex-connectivity of visibility graphs. Unless all its vertices are collinear, a visibility graph has diameter at most 2, and so it follows by a result of Plesn\'ik (1975) that its edge-connectivity equals its minimum degree. We strengthen the result of Plesn\'ik by showing that for any two vertices v and w in a graph of diameter 2, if deg(v) <= deg(w) then there exist deg(v) edge-disjoint vw-paths of length at most 4. Furthermore, we find that in visibility graphs every minimum edge cut is the set of edges incident to a vertex of minimum degree. For vertex-connectivity, we prove that every visibility graph with n vertices and at most l collinear vertices has connectivity at least (n-1)/(l-1), which is tight. We also prove the qualitatively stronger result that the vertex-connectivity is at least half the minimum degree. Finally, in the case that l=4 we improve this bound to two thirds of the minimum degree.
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ItemProjective deformations of hyperbolic Coxeter 3-orbifolds(SPRINGER, 2012-08-01)
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ItemUnit nonresponse errors in income surveys: A case study(Springer Science and Business Media LLC, 2012-10-01)
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ItemNo Preview AvailableImpaired thermogenesis and adipose tissue development in mice with fat-specific disruption of insulin and IGF-1 signalling(NATURE PUBLISHING GROUP, 2012-06-01)Insulin and insulin-like growth factor 1 (IGF-1) have important roles in adipocyte differentiation, glucose tolerance and insulin sensitivity. Here to assess how these pathways can compensate for each other, we created mice with a double tissue-specific knockout of insulin and IGF-1 receptors to eliminate all insulin/IGF-1 signalling in fat. These FIGIRKO mice had markedly decreased white and brown fat mass and were completely resistant to high fat diet-induced obesity and age- and high fat diet-induced glucose intolerance. Energy expenditure was increased in FIGIRKO mice despite a >85% reduction in brown fat mass. However, FIGIRKO mice were unable to maintain body temperature when placed at 4 °C. Brown fat activity was markedly decreased in FIGIRKO mice but was responsive to β3-receptor stimulation. Thus, insulin/IGF-1 signalling has a crucial role in the control of brown and white fat development, and, when disrupted, leads to defective thermogenesis and a paradoxical increase in basal metabolic rate.
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