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At least 487 records · Page 27Linked to original sources
PubMed2004

Feature selection in MLPs and SVMs based on maximum output information.

This paper presents feature selection algorithms for multilayer perceptrons (MLPs) and multiclass support vector machines (SVMs), using mutual information between class labels and classifier outputs, as an objective function. This objective function involves inexpensive computation of information measures only on discrete variables; provides immunity to prior class probabilities; and brackets the probability of error of the classifier. The maximum output information (MOI) algorithms employ this function for feature subset selection by greedy elimination and directed search. The output of the MOI algorithms is a feature subset of user-defined size and an associated trained classifier (MLP/SVM). These algorithms compare favorably with a number of other methods in terms of performance on various artificial and real-world data sets.

Algorithms↗
PubMed2005

Theoretical study on the body form and swimming pattern of Anomalocaris based on hydrodynamic simulation.

Anomalocarid arthropod is the largest known predatory animal of middle Cambrian. Studies on Anomalocaris have been piled up in the past two decades since the first reasonable reconstruction had achieved in 1980s. Recent finding of legs beneath lobes on Parapeytoia Yunnanensis shows arthropod affinities, however, many researchers believe that it must be a powerful swimmer by the use of developed lobes. In this work, we investigate swimming behaviour of Anomalocaris in water by performing hydrodynamical calculation. As a result of simulation using moving particle method possible swimming motion of Anomalocaris is obtained. In the computer we can change the morphology from known bauplan of Anomalocaris found as fossil record. It makes us possible to discuss on the variants of Anomalocaris at the intermediate state of evolution process. Such new methodology using computer reveals how and from where Anomalocaris evolved.

Animals↗
PubMed1991

Conditional power for arbitrary survival curves to decide whether to extend a clinical trial.

This article describes a computer simulation methodology to calculate conditional power for comparing two arbitrary survival curves as an aid in deciding whether or not to extend a clinical trial. The method is a modification of that by Halpern and Brown, which computes unconditional power for comparing arbitrary survival curves at the beginning of a study. The advantage of this method is that it permits conditional power calculations for comparisons of distribution-free survival curves. Power is computed for two commonly used statistical tests, the log-rank test and Gehan's generalization of the Wilcoxon test, and for a modified Kolmogorov-Smirnov test, which is particularly sensitive to crossing survival curves. This method for estimating conditional power should be useful in the situation in which a decision must be made regarding the benefit of continuing a clinical trial. The application of this method is shown using VA Cooperative Study No. 90, "Prognosis and Outcome Following Heart Valve Replacement."

Aortic Valve↗
PubMed2004

An experimental method for measuring the mean length of cerebellar parallel fibers: validation and derivation of a correction factor by computational simulation and probability analysis.

The length of cerebellar parallel fibers is important for information integration by the Purkinje cells. Based on the Copernican principle for analyzing the length of stochastic events, we have recently devised a stochastic method to estimate the mean length of parallel fibers within a given cerebellar region. The purpose of the present report is to provide validation of this methodology via computational simulations. We create virtual parallel fibers with known lengths and program each step of our stochastic method for computational simulation. We then compare the observed mean length obtained from our computational simulation with the known mean length of the virtual parallel fibers. In particular, we investigate the effect of cutting parallel fibers into segments during histological sectioning. Our computational results reveal an over-estimation factor ranging from 1.0 (no correction is necessary) to 2.0 as the parallel fiber segmentation becomes increasingly severe. Based on probability theory considerations, we have confirmed the existence of this over-estimation. We have further determined the cause of this over-estimation to be an artificial consequence of one of the sampling steps in our stochastic method. These results provide validation of our methodology, as well as a correction factor, which can be derived directly from the experimentally measured parameters and used to obtain the true mean length of parallel fibers. Potential applications of the stochastic method include a comparative analysis of the length of parallel fibers as an approach to gain clues about cerebellar circuit principles and function. In addition, the stochastic method may also find promising applications in other functionally important axonal systems in the brain.

Cerebellar Cortex↗
PubMed2004

ClusterControl: a web interface for distributing and monitoring bioinformatics applications on a Linux cluster.

UNLABELLED: ClusterControl is a web interface to simplify distributing and monitoring bioinformatics applications on Linux cluster systems. We have developed a modular concept that enables integration of command line oriented program into the application framework of ClusterControl. The systems facilitate integration of different applications accessed through one interface and executed on a distributed cluster system. The package is based on freely available technologies like Apache as web server, PHP as server-side scripting language and OpenPBS as queuing system and is available free of charge for academic and non-profit institutions. AVAILABILITY: http://genome.tugraz.at/Software/ClusterControl

Computational Biology↗
PubMed2006

GenePro: a Cytoscape plug-in for advanced visualization and analysis of interaction networks.

MOTIVATION: Analyzing the networks of interactions between genes and proteins has become a central theme in systems biology. Versatile software tools for interactively displaying and analyzing these networks are therefore very much in demand. The public-domain open software environment Cytoscape has been developed with the goal of facilitating the design and development of such software tools by the scientific community. RESULTS: We present GenePro, a plugin to Cytoscape featuring a set of versatile tools that greatly facilitates the visualization and analysis of protein networks derived from high-throughput interactions data and the validation of various methods for parsing these networks into meaningful functional modules. AVAILABILITY: The GenePro plugin is available at the website http://genepro.ccb.sickkids.ca.

Algorithms↗
PubMed2006

Parallelized Bayesian inversion for three-dimensional dental X-ray imaging.

Diagnostic and operational tasks based on dental radiology often require three-dimensional (3-D) information that is not available in a single X-ray projection image. Comprehensive 3-D information about tissues can be obtained by computerized tomography (CT) imaging. However, in dental imaging a conventional CT scan may not be available or practical because of high radiation dose, low-resolution or the cost of the CT scanner equipment. In this paper, we consider a novel type of 3-D imaging modality for dental radiology. We consider situations in which projection images of the teeth are taken from a few sparsely distributed projection directions using the dentist's regular (digital) X-ray equipment and the 3-D X-ray attenuation function is reconstructed. A complication in these experiments is that the reconstruction of the 3-D structure based on a few projection images becomes an ill-posed inverse problem. Bayesian inversion is a well suited framework for reconstruction from such incomplete data. In Bayesian inversion, the ill-posed reconstruction problem is formulated in a well-posed probabilistic form in which a priori information is used to compensate for the incomplete information of the projection data. In this paper we propose a Bayesian method for 3-D reconstruction in dental radiology. The method is partially based on Kolehmainen et al. 2003. The prior model for dental structures consist of a weighted l1 and total variation (TV)-prior together with the positivity prior. The inverse problem is stated as finding the maximum a posteriori (MAP) estimate. To make the 3-D reconstruction computationally feasible, a parallelized version of an optimization algorithm is implemented for a Beowulf cluster computer. The method is tested with projection data from dental specimens and patient data. Tomosynthetic reconstructions are given as reference for the proposed method.

Algorithms↗
PubMed2006

Computational analysis of CFSE proliferation assay.

CFSE based tracking of the lymphocyte proliferation using flow cytometry is a powerful experimental technique in immunology allowing for the tracing of labelled cell populations over time in terms of the number of divisions cells undergone. Interpretation and understanding of such population data can be greatly improved through the use of mathematical modelling. We apply a heterogenous linear compartmental model, described by a system of ordinary differential equations similar to those proposed by Kendall. This model allows division number-dependent rates of cell proliferation and death and describes the rate of changes in the numbers of cells having undergone j divisions. The experimental data set that we specifically analyze specifies the following characteristics of the kinetics of PHA-induced human T lymphocyte proliferation assay in vitro: (1) the total number of live cells, (2) the total number of dead but not disintegrated cells and (3) the number of cells divided j times. Following the maximum likelihood approach for data fitting, we estimate the model parameters which, in particular, present the CTL birth- and death rate "functions". It is the first study of CFSE labelling data which convincingly shows that the lymphocyte proliferation and death both in vitro and in vivo are division number dependent. For the first time, the confidence in the estimated parameter values is analyzed by comparing three major methods: the technique based on the variance-covariance matrix, the profile-likelihood-based approach and the bootstrap technique. We compare results and performance of these methods with respect to their robustness and computational cost. We show that for evaluating mathematical models of differing complexity the information-theoretic approach, based upon indicators measuring the information loss for a particular model (Kullback-Leibler information), provides a consistent basis. We specifically discuss methodological and computational difficulties in parameter identification with CFSE data, e.g. the loss of confidence in the parameter estimates starting around the sixth division. Overall, our study suggests that the heterogeneity inherent in cell kinetics should be explicitly incorporated into the structure of mathematical models.

Cell Growth Processes↗
PubMed1992

Making information accessible and useful to practicing clinicians. Problem-knowledge coupling.

Assessments of health care technology will lead to improvements in patient services only if this information is actually used by clinicians. Traditional methods of planning treatment that rely solely on memory limit the clinician's access to and use of the full available body of knowledge in the field. An alternative approach using a computer-assisted methodology is presented as a way to overcome traditional limitations and promote the development and diffusion of knowledge.

Ambulatory Care↗
PubMed2003

Exploratory data analysis using set operations and ordinal mapping.

Exploratory data analysis requires the ability to issue ad hoc queries to filter and summarise data sets. As the sizes of health data sets grow, traditional methods of processing data have difficulty in providing acceptable response times for such queries. An alternative method is described which combines complete vertical partitioning of data with set operations on ordinal mappings (SOOM). An initial implementation of the technique provides significantly better performance than a conventional SQL database on typical exploratory data analysis queries. The use of parallel, distributed computation to further increase the performance of the technique appears to be feasible.

Algorithms↗