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Results for “model selection”

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PubMed2002

Multicollinearity in prognostic factor analyses using the EORTC QLQ-C30: identification and impact on model selection.

Clinical and quality of life (QL) variables from an EORTC clinical trial of first line chemotherapy in advanced breast cancer were used in a prognostic factor analysis of survival and response to chemotherapy. For response, different final multivariate models were obtained from forward and backward selection methods, suggesting a disconcerting instability. Quality of life was measured using the EORTC QLQ-C30 questionnaire completed by patients. Subscales on the questionnaire are known to be highly correlated, and therefore it was hypothesized that multicollinearity contributed to model instability. A correlation matrix indicated that global QL was highly correlated with 7 out of 11 variables. In a first attempt to explore multicollinearity, we used global QL as dependent variable in a regression model with other QL subscales as predictors. Afterwards, standard diagnostic tests for multicollinearity were performed. An exploratory principal components analysis and factor analysis of the QL subscales identified at most three important components and indicated that inclusion of global QL made minimal difference to the loadings on each component, suggesting that it is redundant in the model. In a second approach, we advocate a bootstrap technique to assess the stability of the models. Based on these analyses and since global QL exacerbates problems of multicollinearity, we therefore recommend that global QL be excluded from prognostic factor analyses using the QLQ-C30. The prognostic factor analysis was rerun without global QL in the model, and selected the same significant prognostic factors as before.

Antineoplastic Agents↗
PubMed1983

Antigen-presenting cells from nonresponder strain 2 guinea pigs are fully competent to present bovine insulin B chain to responder strain 13 T cells. Evidence against a determinant selection model and in favor of a clonal deletion model of immune response gene function.

To test directly the determinant selection hypothesis of immune response gene function, we primed strain 13 T lymphocytes in vitro with allogeneic bovine insulin pulsed strain 2 macrophages. Strain 2 macrophages were found to be fully competent to present bovine insulin B chain to strain 13 T cells despite the fact that strain 2 guinea pigs are normally totally unresponsive to this antigen. These results are incompatible with a strict interpretation of the determinant selection hypothesis, which would have predicted that strain 2 macrophages would have been restricted to the presentation of A chain loop determinants. In addition, a comparison of the reactivity profiles of self-Ia- and allo-Ia-restricted strain 13 T cells to a series of synthetic B chain peptide fragments revealed that the allo-Ia-restricted populations could be activated by autologous guinea pig insulin. Taken together, these observations strongly suggest that the clonal deletion of self-reactive cells is likely to be I region restricted and that nonresponsiveness to any protein antigen may result from a restriction in the T cell repertoire that is generated during ontogeny by a clonal deletion mechanism of tolerance to self.

Animals↗
PubMed2000

Modeling selective attention using a neuromorphic analog VLSI device.

Attentional mechanisms are required to overcome the problem of flooding a limited processing capacity system with information. They are present in biological sensory systems and can be a useful engineering tool for artificial visual systems. In this article we present a hardware model of a selective attention mechanism implemented on a very large-scale integration (VLSI) chip, using analog neuromorphic circuits. The chip exploits a spike-based representation to receive, process, and transmit signals. It can be used as a transceiver module for building multichip neuromorphic vision systems. We describe the circuits that carry out the main processing stages of the selective attention mechanism and provide experimental data for each circuit. We demonstrate the expected behavior of the model at the system level by stimulating the chip with both artificially generated control signals and signals obtained from a saliency map, computed from an image containing several salient features.

Attention↗
PubMedDate not supplied

Bayesian model selection for mining mass spectrometry data.

A procedure for learning a probabilistic model from mass spectrometry data that accounts for domain specific noise and mitigates the complexity of Bayesian structure learning is presented. We evaluate the algorithm by applying the learned probabilistic model to microorganism detection from mass spectrometry data.

Algorithms↗
PubMed1995

The pattern of neutral molecular variation under the background selection model.

Stochastic simulations of the infinite sites model were used to study the behavior of genetic diversity at a neutral locus in a genomic region without recombination, but subject to selection against deleterious alleles maintained by recurrent mutation (background selection). In large populations, the effect of background selection on the number of segregating sites approaches the effect on nucleotide site diversity, i.e., the reduction in genetic variability caused by background selection resembles that caused by a simple reduction in effective population size. We examined, by coalescence-based methods, the power of several tests for the departure from neutral expectation of the frequency spectra of alleles in samples from randomly mating populations (Tajima's, Fu and Li's, and Watterson's tests). All of the tests have low power unless the selection against mutant alleles is extremely weak. In Drosophila, significant Tajima's tests are usually not obtained with empirical data sets from loci in genomic regions with restricted recombination frequencies and that exhibit low genetic diversity. This is consistent with the operation of background selection as opposed to selective sweeps. It remains to be decided whether background selection is sufficient to explain the observed extent of reduction in diversity in regions of restricted recombination.

Animals↗
PubMed1975

Best linear unbiased estimation and prediction under a selection model.

Mixed linear models are assumed in most animal breeding applications. Convenient methods for computing BLUE of the estimable linear functions of the fixed elements of the model and for computing best linear unbiased predictions of the random elements of the model have been available. Most data available to animal breeders, however, do not meet the usual requirements of random sampling, the problem being that the data arise either from selection experiments or from breeders' herds which are undergoing selection. Consequently, the usual methods are likely to yield biased estimates and predictions. Methods for dealing with such data are presented in this paper.

Animals↗
PubMed2000

Group selection models in prebiotic evolution.

The evolution of enzyme production is studied analytically using ideas of the group selection theory for the evolution of altruistic behavior. In particular, we argue that the mathematical formulation of Wilson's structured deme model [The Evolution of Populations and Communities (Benjamin-Cumings, Menlo Park, 1980)] is a mean-field approach in which the actual environment that a particular individual experiences is replaced by an average environment. That formalism is further developed so as to avoid the mean-field approximation and then applied to the problem of enzyme production in the prebiotic context, where the enzyme producer molecules play the altruists role while the molecules that benefit from the catalyst without paying its production cost play the nonaltruists role. The effects of synergism (i.e., division of labor) as well as of mutations are also considered and the results of the equilibrium analysis are summarized in phase diagrams showing the regions of the space of parameters where the altruistic, nonaltruistic, and the coexistence regimes are stable. In general, those regions are delimitated by discontinuous transition lines which end at critical points.

Enzymes↗
PubMed2003

Generation of the natural killer cell repertoire: the sequential vs. the two-step selection model.

Natural killer (NK) cells are lymphocytes which can kill tumor and virus-infected cells, and mediate acute rejection of bone marrow grafts. NK-cell killing is directed primarily at target cells which do not express sufficient levels of self-major histocompatibility complex (MHC) class-I molecules. Inhibition of lysis of self-MHC-expressing target cells is mediated via inhibitory receptors on the NK cell, which bind to MHC molecules. Each NK cell expresses only a subset of all its inhibitory receptor gene repertoire, which may bind to only a subset of the self-MHC molecules expressed by other cells of the organism. Two conceptual models have been proposed to explain the process of NK cell 'education' in which these cells adapt, during their development, to the self-MHC environment: the two-step selection and the sequential models. In this manuscript we develop mathematical and computational models of the process of NK cell development and education, which implement the two conceptual models. We use this theoretical framework to examine the available data on NK cell repertoire compositions, and evaluate the degree these data support either of the two conceptual models. We show that the data published so far on NK cell receptor expression patterns is insufficient to refute either model, since data on NK cell receptor binding affinities to MHC is also needed. However, the models allow us to make predictions on these binding affinities, which can later be tested experimentally.

Animals↗
PubMed2003

Model selection for the interpretation of protein side chain methyl dynamics.

A number of different dynamics models are considered for fitting (13)C and (2)H side chain methyl relaxation rates. It is shown that in cases where nanosecond time scale dynamics are present the extended Lipari-Szabo model which is explicitly parameterized to include the effects of slow motions can produce wide distributions of fitting parameters even in cases where the errors are relatively small and large numbers of relaxation rates are considered. In contrast, fits of (15)N backbone dynamics using this model are far more robust. The origin of this difference is analyzed and can be explained by the different functional forms of the spectral density in these two cases. The utility of a number of models for the analysis of methyl side chain dynamics is presented.

Amino Acids↗
PubMed1986

Computer analysis of enzyme-substrate-inhibitor kinetic data with automatic model selection using IBM-PC compatible microcomputers.

A weighted nonlinear least-squares curve-fitting program, implemented in compiled BASIC for the IBM-PC is described to estimate the parameters of enzyme kinetics obeying Michaelis-Menten kinetics and seven inhibition models. The effects of the inhibitor on the maximal velocity (Vm) and the Michaelis-Menten constant (Km) are used to select automatically the most plausible model of inhibition and to calculate initial estimates of parameters. The program is used to demonstrate that the inhibition of carbamyl-phenylalanine hydrolase by the product phenylalanine is consistent with the pure mixed noncompetitive model.

Binding, Competitive↗
PubMed1979

Representation of Nonepistatic selection models and analysis of multilocus Hardy-Weinberg Equilibrium configurations.

The paper develops conditions for the existence and the stability of central equilibria emanating from selection recombination interaction with generalized nonepistatic selection forms operating in multilocus multiallele systems. The selection structure admits a natural representation as simple sums of Kronecker products based on a common set of marginal selection components. A flexible parametrization of the recombination process is introduced leading to a canonical derivation of the transformation equations connecting gamete frequency states over successive generations. Conditions for the existence and stability of multilocus Hardy-Weinberg (H.W.) type equilibria are elaborated for the classical nonepistatic models (multiplicative and additive viability effects across loci) as well as for generalized nonepistatic selection expressions. It is established that the range of recombination distributions maintaining a stable H.W. polymorphic equilibrium is confined to loose linkage in the pure multiplicative case, but is not restricted in the additive model. In the bisexual case we ascertain for the generalized nonepistatic model the stability conditions of a common H.W polymorphism.

Alleles↗