SEARCH · Search PubMed

Results for “Generative models”

Search indexed PubMed citations on genomics, clinical trials, systematic reviews and public health. Explore titles, authors and supplied subject terms, then open the PubMed record.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 523 records · Page 29Linked to original sources

PubMed2006

Comparison of models to identify lame cows based on gait and lesion scores, and limb movement variables.

Bovine lameness results in pain and suffering in cattle and economic loss for producers. A system for automatically detecting lame cows was developed recently that measures vertical force components attributable to individual limbs. These measurements can be used to calculate a number of limb movement variables. The objective of this investigation was to explore whether gait scores, lesion scores, or combined gait and lesion scores were more effectively captured by a set of 5 limb movement variables. A set of 700 hind limb examinations was used to create gait-based, lesion-based, and combined (gait- and lesion-based) models. Logistic regression models were constructed using 1, 2, or 3 d of measurements. Resulting models were tested on cows not used in modeling. The accuracy of lesion-score models was superior to that of gait-score models; lesion-based models generated greater values of areas under the receiving operating characteristic curves (range 0.75 to 0.84) and lower mean-squared errors (0.13 to 0.16) compared with corresponding values for the gait-based models (0.63 to 0.73 and 0.26 to 0.31 for receiving operating characteristic and mean-squared errors, respectively). These results indicate that further model development and investigation could generate automated and objective methods of lameness detection in dairy cattle.

Animals↗

PubMed2003

Progress toward generating a ferret model of cystic fibrosis by somatic cell nuclear transfer.

Mammalian cloning by nuclear transfer from somatic cells has created new opportunities to generate animal models of genetic diseases in species other than mice. Although genetic mouse models play a critical role in basic and applied research for numerous diseases, often mouse models do not adequately reproduce the human disease phenotype. Cystic fibrosis (CF) is one such disease. Targeted ablation of the cystic fibrosis transmembrane conductance regulator (CFTR) gene in mice does not adequately replicate spontaneous bacterial infections observed in the human CF lung. Hence, several laboratories are pursuing alternative animal models of CF in larger species such as the pig, sheep, rabbits, and ferrets. Our laboratory has focused on developing the ferret as a CF animal model. Over the past few years, we have investigated several experimental parameters required for gene targeting and nuclear transfer (NT) cloning in the ferret using somatic cells. In this review, we will discuss our progress and the hurdles to NT cloning and gene-targeting that accompany efforts to generate animal models of genetic diseases in species such as the ferret.

Animals↗

PubMed1999

A computer generated interactive transurethral prostatic resection simulator.

PURPOSE: We developed a computer generated model of the prostate gland and an interactive simulator for use in training urologists in transurethral resection of the prostate. MATERIALS AND METHODS: Software was developed on a standard personal computer which allowed images of the lumen of the prostatic urethra and resectoscope loop to be generated and interacted with using a magnetic position sensor input device attached to a dummy resectoscope. RESULTS: An anatomically accurate computer model of the prostate was generated at low cost which permitted user interaction and which simulated key elements of transurethral prostatic resection. CONCLUSIONS: Although not a substitute for learning transurethral prostatic resection on patients, the simulator enabled the user to become familiar with the technique of transurethral prostatic resection in the absence of time constraints and without risk to patients. The simulator may become an important tool in training and assessing surgeon competency, and may reduce the costs of training. Further development is needed to refine the transurethral prostatic resection simulator and expand its surgical range.

Computer Simulation↗

PubMedDate not supplied

A phenomenological model of visually evoked spike trains in cat geniculate nonlagged X-cells.

The visual information that first-order cortical cells receive is contained in the visually evoked spike trains of geniculate relay cells. To address functional issues such as the ON/OFF structure of visual cortical receptive fields with modelling studies, a geniculate cell model is needed where the spatial and temporal characteristics of the visual response are described quantitatively. We propose a model simulating the spike trains produced by cat geniculate nonlagged X-cells, based on a review of the electrophysiological literature. The level of description chosen is phenomenological, fitting the dynamics and amplitude of phasic and tonic responses, center/surround antagonism, surround excitatory responses, and the statistical properties of both spontaneous and visually evoked spike trains. The model, which has been constrained so as to reproduce the responses to centered light spots of expanding size and optimal light and dark annuli, predicts responses to thin and large bars flashed in various positions of the receptive field. The switching gamma renewal process method has been introduced for modelling spontaneous and visually evoked spike trains within the same mathematical framework. The statistical structure of the spike process is assumed to be more regular during phasic than tonic visual responses. On the whole, this model generates more realistic geniculate input to cortex than the currently used retinal models.

Animals↗

PubMed2003

The correlation between ion beam/material interactions and practical FIB specimen preparation.

The focused ion beam (FIB) tool has been successfully used as both a stand alone analytical instrument and a means to prepare specimens for subsequent analysis by SEM, TEM, SIMS, XPS, and AUGER. In this work, special emphasis is given to TEM specimen preparation by the FIB lift-out technique. The fundamental ion/solid interactions that govern the FIB milling process are examined and discussed with respect to the preparation of electron transparent membranes. TRIM, a Monte Carlo simulation code, is used to physically model variables that influence FIB sputtering behavior. The results of such computer generated models are compared with empirical observations in a number of materials processed with an FEI 611 FIB workstation. The roles of incident ion attack angle, beam current, trench geometry, raster pattern, and target-material-dependent removal rates are considered. These interrelationships are used to explain observed phenomena and predict expected milling behaviors, thus increasing the potential for the FIB to be used more efficiently with reproducible results.

Computer Simulation↗

PubMed2003

From annotated genomes to metabolic flux models and kinetic parameter fitting.

Significant advances in system-level modeling of cellular behavior can be achieved based on constraints derived from genomic information and on optimality hypotheses. For steady-state models of metabolic networks, mass conservation and reaction stoichiometry impose linear constraints on metabolic fluxes. Different objectives, such as maximization of growth rate or minimization of flux distance from a reference state, can be tested in different organisms and conditions. In particular, we have suggested that the metabolic properties of mutant bacterial strains are best described by an algorithm that performs a minimization of metabolic adjustment (MOMA) upon gene deletion. The increasing availability of many annotated genomes paves the way for a systematic application of these flux balance methods to a large variety of organisms. However, such a high throughput goal crucially depends on our capacity to build metabolic flux models in a fully automated fashion. Here we describe a pipeline for generating models from annotated genomes and discuss the current obstacles to full automation. In addition, we propose a framework for the integration of flux modeling results and high throughput proteomic data, which can potentially help in the inference of whole-cell kinetic parameters.

Algorithms↗

PubMed2003

A multivariate approach applied to microarray data for identification of genes with cell cycle-coupled transcription.

We have analyzed microarray data using a modeling approach based on the multivariate statistical method partial least squares (PLS) regression to identify genes with periodic fluctuations in expression levels coupled to the cell cycle in the budding yeast, Saccharomyces cerevisiae. PLS has major advantages for analyzing microarray data since it can model data sets with large numbers of variables and with few observations. A response model was derived describing the expression profile over time expected for periodically transcribed genes, and was used to identify budding yeast transcripts with similar profiles. PLS was then used to interpret the importance of the variables (genes) for the model, yielding a ranking list of how well the genes fitted the generated model. Application of an appropriate cutoff value, calculated from randomized data, allows the identification of genes whose expression appears to be synchronized with cell cycling. Our approach also provides information about the stage in the cell cycle where their transcription peaks. Three synchronized yeast cell microarray data sets were analyzed, both separately and combined. Cell cycle-coupled periodicity was suggested for 455 of the 6,178 transcripts monitored in the combined data set, at a significance level of 0.5%. Among the candidates, 85% of the known periodic transcripts were included. Analysis of the three data sets separately yielded similar ranking lists, showing that the method is robust.

Algorithms↗

PubMed2005

Improving sequence-based fold recognition by using 3D model quality assessment.

MOTIVATION: The ability of a simple method (MODCHECK) to determine the sequence-structure compatibility of a set of structural models generated by fold recognition is tested in a thorough benchmark analysis. Four Model Quality Assessment Programs (MQAPs) were tested on 188 targets from the latest LiveBench-9 automated structure evaluation experiment. We systematically test and evaluate whether the MQAP methods can successfully detect native-like models. RESULTS: We show that compared with the other three methods tested MODCHECK is the most reliable method for consistently performing the best top model selection and for ranking the models. In addition, we show that the choice of model similarity score used to assess a model's similarity to the experimental structure can influence the overall performance of these tools. Although these MQAP methods fail to improve the model selection performance for methods that already incorporate protein three dimension (3D) structural information, an improvement is observed for methods that are purely sequence-based, including the best profile-profile methods. This suggests that even the best sequence-based fold recognition methods can still be improved by taking into account the 3D structural information. CONTACT: d.jones@cs.ucl.ac.uk

Algorithms↗

PubMed2005

Technology dependence and health-related quality of life: a model.

AIM: This paper presents a new theoretical model to explain people's diverse responses to therapeutic health technology by characterizing the relationship between technology dependence and health-related quality of life (HRQL). INTRODUCTION: Technology dependence has been defined as reliance on a variety of devices, drugs and procedures to alleviate or remedy acute or chronic health problems. Health professionals must ensure that these technologies result in positive outcomes for those who must rely on them, while minimizing the potential for unintended consequences. Little research exists to inform health professionals about how dependency on therapeutic technology may affect patient-reported outcomes such as HRQL. Organizing frameworks to focus such research are also limited. MODEL: Generated from the synthesis of three theoretical frameworks and empirical research, the model proposes that attitudes towards technology dependence affect HRQL through a person's illness representations or commonsense beliefs about their illness. Symptom distress, illness history, age and gender also influence the technology dependence and HRQL relationship. Five concepts form the major components of the model: a) attitudes towards technology dependence, b) illness representation, c) symptom distress, d) HRQL and e) illness history. CONCLUSION: The model is proposed as a guide for clinical nursing research into the impact of a wide variety of therapeutic health care interventions on HRQL. Empirical validation of the model is needed to test its generality.

Adolescent↗

PubMed2001

A constrained EM algorithm for independent component analysis.

We introduce a novel way of performing independent component analysis using a constrained version of the expectation-maximization (EM) algorithm. The source distributions are modeled as D one-dimensional mixtures of gaussians. The observed data are modeled as linear mixtures of the sources with additive, isotropic noise. This generative model is fit to the data using constrained EM. The simpler "soft-switching" approach is introduced, which uses only one parameter to decide on the sub- or supergaussian nature of the sources. We explain how our approach relates to independent factor analysis.

Algorithms↗

PubMed2000

Estimation of youth smoking behaviours in Canada.

This study estimated the prevalence of current smoking and smoking initiation among Canadian youth. Logistic regression was used to relate socio-demographic predictors to the occurrence of the smoking indicators among youth (15-24 years) in the 1994/95 National Population Health Survey (NPHS). Models were then applied to provincial youth populations in the 1996/97 NPHS and the 1996 census of Canada. Model-generated estimates were compared with direct estimates obtained from NPHS data. The models accurately predicted provincial rates of current youth smoking for 1994/95. When applied to the 1996/97 NPHS, the current smoking models performed reasonably well, but were less predictive when applied to 1996 census data. Modelling of youth smoking initiation was not successful. This suggests that although simple estimation models of youth smoking can be derived, these models may not be portable across different populations or time periods.

Adolescent↗

PubMed1991

Analysis of longitudinal data with unmeasured confounders.

Confounding in longitudinal or clustered data creates special problems and opportunities because the relationship between the confounder and covariate of interest may differ across and within individuals or clusters. A well-known example of such confounding in longitudinal data is the presence of cohort and period effects in models of aging in epidemiologic research. We first formulate a data-generating model with confounding and derive the distribution of the response variable unconditional on the confounder. We then examine the properties of the regression coefficient for some analytic approaches when the confounder is omitted from the fitted model. The expected value of the regression coefficient differs in across- and within-individual regression. In the multivariate case, within- and between-individual information is combined and weighted according to the assumed covariance structure. We assume compound symmetry in the fitted covariance matrix and derive the variance, bias, and mean squared error of the slope estimate as a function of the fitted within-individual correlation. We find that even in this simplest multivariate case, the trade-off between bias and variance depends on a large number of parameters. It is generally preferable to fit correlations somewhat above the true correlation to minimize the effect of between-individual confounders or cohort effects. Period effects can lead to situations where it is advantageous to fit correlations that are below the true correlation. The results highlight the trade-offs inherent in the choice of method for analysis of longitudinal data, and show that an appropriate choice can be made only after determining whether within- or between-individual confounding is the major concern.

Analysis of Variance↗

PubMed2001

Computer modeling of small heat-shock metalloprotease of the human malaria parasite Plasmodium vivax.

We present here computer generated model of N-terminal fragment, amino acids (aa) 36-245, of a Plasmodium vivax heat shock metalloprotease called PVHSP28, whose gene was cloned and characterised earlier. The fragment showed homology with HSPs from many organisms, including Escherichia coli and Haemophilus influenzae. PVHSP28 had the signature sequence 'HEXXH' and 'EXXXD' of Zinc metalloproteases. Being the first malarial HSP possessing metalloprotease activity, PVHSP28 is an ideal target for the design of new anti-malarial drugs. However, except for a small region (aa 62-132) which had 24.6% sequence similarity with 1TAQ (a DNA polymerase), it did not show sequence similarity with any published structures in protein data bank. Hence it could not be modelled using any automated modeling programs. We modelled 36-245 aa of PVHSP28 using predicted secondary structure as well as experimentally determined and predicted properties of the protein on the basis of its amino acid sequence, using various Internet tools and in-house package MODEL. The model was energy minimised using Sander's module of AMBER 5.0, working on a Silicon Graphics machine, with all atom force field.

Amino Acid Sequence↗

PubMed1993

The brainstem esophagomotor network pattern generator: a rodent model.

The evidence reviewed in this essay supports the following working model of the central function generator for esophageal peristalsis in the rat: solitarial subnucleus centralis (NTSc) neurons operate in a dual capacity as esophagomotor reflex interneurons and as command neurons programming respective outputs from nucleus ambiguus compact formation (AMBc) motoneurons during secondary and primary peristalsis. In both conditions, there is a critical requirement for cholinergic input which enables NTSc neurons to generate the timed sequence of AMBc motoneuronal activity. In primary peristalsis, the cholinergic coupling mechanism is activated centrally, probably via projections from deglutitive premotor neurons to the parvicellular reticular formation and thence to the NTS. In reflex (or secondary) peristalsis, the cholinergic input could in part be generated by cholinergic vagal viscerosensory fibers innervating the esophagus. Postulated connections between NTS deglutitive neurons and the parvicellular cholinergic neurons of the intermediate reticular formation have yet to be demonstrated. Premotor input from NTSc to AMBc is generated by somatostatinergic and excitatory aminoacidergic neurons. Coactivation of both inputs by cholinergic afferents is necessary to generate esophagomotor output from AMBc neurons. The model under study is derived from investigations into central mechanisms governing striated muscle peristaltic activity. Whether the basic operational principles revealed thus far apply to peristaltic pattern generation in species with a smooth muscle esophagus, requires further investigation.

Animals↗

PubMedDate not supplied

Inhibition of the tyrosine kinase, Syk, analyzed by stepwise nonparametric regression.

A set of 538 inhibitors of the tyrosine kinase, Syk, including purines, pyrimidines, indoles, imidazoles, pyrazoles, and quinazolines, has been analyzed using a stepwise nonparametric regression (SNPR) algorithm, which has been developed for QSAR studies of pharmacological data. The algorithm couples stepwise descriptor selection with flexible, nonparametric, kernel regression, to generate structure-activity relationships. A further 371 molecules have been used as a test set to evaluate the models generated. Descriptors were selected using an internal monitoring set, and models were assessed using 10% of the principal (538-compound) data set, selected randomly, as an external validation set. The best model had a Q(2) of 0.46 for the external validation set. Test set predictions were significantly less accurate, partly due to the higher mean activity of the test molecules. However at a more coarse-grain level the SNPR models classified active molecules accurately, giving good enrichments. The data sets are difficult to model accurately and SNPR performs better than multilinear regression and a neural network analysis. In the additive implementation of SNPR multidimensional models are considered as a sum of single dimensional regressions. This makes the resultant models easily interpretable. For example, in the most predictive SNPR models, there is a clear nonlinear relationship between hydrophobicity (AlogP98) and inhibitory activity.

Enzyme Inhibitors↗

PubMed1986

Maximum likelihood estimations in a nonlinear self-exciting point process model.

A nonlinear model generating a self-exciting point process is formulated and identification of the model using maximum likelihood estimations is discussed. Simulations have been performed and parameters are estimated numerically. (Dis)advantages with respect to identification approaches based on correlation densities are outlined. This method may function as a basis to interpret simultaneous recordings of single units in terms of underlying wiring diagrams.

Animals↗

PubMed2005

Behavioral assessment in mouse models of neuronal ceroid lipofuscinosis using a light-cued T-maze.

Learning impairment is a common feature of the neuronal ceroid lipofuscinoses (NCL), a family of lysosomal storage disorders associated with progressive neurodegeneration. Murine models for the neuronal ceroid lipofuscinoses include the well-characterized motor neuron degeneration (mnd/mnd) model for one variant of late infantile NCL (CLN8), and the more recently generated models for the infantile (CLN1) and juvenile (CLN3) forms of NCL. To determine whether these mouse models exhibit behavioral deficits analogous to the learning impairment characteristic of the human disorders, the performance of these animals on an associative learning task was assessed. The abilities of affected and normal control mice to associate a light stimulus with a food reward were evaluated in 14-16-week-old animals using a T-maze. Normal mice were able to reach a criterion for having learned to make the association within a mean of 9.4 trials. The CLN8 and CLN3 mice, on the other hand, required means of 26.2 and 27.5 trials, respectively, to reach the same performance criterion (p<0.05), whereas none of the CLN1 mice were able to reach the criterion within a limit of 30 trials. The poor performance of the mutant mice did not appear to result from impaired retinal function; mice of all three strains exhibited retinal electrophysiological responses to dim light flashes and displayed robust pupillary light reflexes. Associative learning deficits appear to be an early disease phenotype in the NCL mouse models that will be useful for assessing the efficacy of therapeutic interventions such as gene or stem cell therapies.

Analysis of Variance↗

PubMed2005

Reliability of electromagnetic filters of cardiac pacemakers tested by cellular telephone ringing.

BACKGROUND: State-of-the art cardiac pacemakers are protected against radiofrequency signals. Although there have been earlier clinical and in vitro reports of cellular phone interference with implantable devices, only a few studies have been performed in recent years. The ringing phase of digital GSM or PCS cellular phones includes a brief period of peak radiated power. OBJECTIVES: This study tested the protection offered by electromagnetic filters of cardiac pacemakers against cellular phone ringing. METHODS: We performed 330 consecutive tests in 158 patients at the time of routine examination in our pacemaker follow-up clinic. The programmed parameters remained unchanged before testing. During electrocardiographic monitoring, 2 single-band digital cellular phones consecutively placed over the pacemaker pocket each received a call. The phone systems tested were 1) GSM at a maximal power output of 2 W, operating on a 900 MHz carrier frequency, and 2) PCS at a maximal output of 1 W, operating on a 1800 MHz carrier frequency. RESULTS: Interference was noted in only 5 tests, due to interaction by the GSM system with 4 unprotected pacemaker models. The GSM test was negative in 12 other tests of identical pulse generator models. The overall incidence of interference was 1.5% of tests. CONCLUSIONS: Interference by cellular phone ringing occurred only with unprotected pacemaker models. Standard programming of these unprotected models was associated with a low incidence of interference.

Adult↗