Search PubMed⌕ Search

SEARCH · Search PubMed

Results for “Ensemble methods”

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.

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

At least 613 records · Page 34Linked to original sources
PubMed2003

Spatiotemporal tuning of motor cortical neurons for hand position and velocity.

A pursuit-tracking task (PTT) and multielectrode recordings were used to investigate the spatiotemporal encoding of hand position and velocity in primate primary motor cortex (MI). Continuous tracking of a randomly moving visual stimulus provided a broad sample of velocity and position space, reduced statistical dependencies between kinematic variables, and minimized the nonstationarities that are found in typical "step-tracking" tasks. These statistical features permitted the application of signal-processing and information-theoretic tools for the analysis of neural encoding. The multielectrode method allowed for the comparison of tuning functions among simultaneously recorded cells. During tracking, MI neurons showed heterogeneity of position and velocity coding, with markedly different temporal dynamics for each. Velocity-tuned neurons were approximately sinusoidally tuned for direction, with linear speed scaling; other cells showed sinusoidal tuning for position, with linear scaling by distance. Velocity encoding led behavior by about 100 ms for most cells, whereas position tuning was more broadly distributed, with leads and lags suggestive of both feedforward and feedback coding. Individual cells encoded velocity and position weakly, with comparable amounts of information about each. Linear regression methods confirmed that random, 2-D hand trajectories can be reconstructed from the firing of small ensembles of randomly selected neurons (3-19 cells) within the MI arm area. These findings demonstrate that MI carries information about evolving hand trajectory during visually guided pursuit tracking, including information about arm position both during and after its specification. However, the reconstruction methods used here capture only the low-frequency components of movement during the PTT. Hand motion signals appear to be represented as a distributed code in which diverse information about position and velocity is available within small regions of MI.

Action Potentials↗
PubMed2006

Kinetic definition of protein folding transition state ensembles and reaction coordinates.

Using distributed molecular dynamics simulations we located four distinct folding transitions for a 39-residue betabetaalphabeta protein fold. To characterize the nature of each room temperature transition, we calculated the probability of transmission for 500 points along each free energy barrier. We introduced a method for determining transition states by employing the transmission probability, Ptrans, and determined which conformations were transition state ensemble members (Ptrans approximately 0.5). The transmission probability may be used to characterize the barrier in several ways. For example, we ran simulations at 82 degrees C, determined the change in Ptrans with temperature for all 2,000 conformations, and quantified Hammond behavior directly using Ptrans correlation. Additionally, we propose that diffusion along Ptrans may provide the configurational diffusion rate at the top of the barrier. Specifically, given a transition state conformation x0 with estimated Ptrans=0.5, we selected a large set of subsequent conformations from independent trajectories, each exactly a small time deltat after x0 (250 ps). Calculating Ptrans for the new trial conformations, we generated the P(Ptrans|deltat=250 ps) distribution that reflected diffusion. This approach provides a novel perspective on the diffusive nature of a protein folding transition and provides a framework for a quantitative study of activated relaxation kinetics.

Computer Simulation↗
PubMed2002

[Use of Ensemble tissue harmonic imaging to improve the resolution in ultrasound investigations of the head and neck area].

BACKGROUND: Using ultrasound diagnostic, deeper areas of tissue cannot be examined as easily as superficial areas. Therefore it was necessary to develop a new image processing technique for ultrasound platforms to improve the quality of sonographical resolution in deeper areas. Tissue Harmonic Imaging is a modern technique that uses the non-linear, "harmonic" parts of ultrasound waves. Ensemble Tissue Harmonic Imaging is a new technique that uses a "Wide Band Harmonic Imaging", based on a patented phase-inversion-technique, and improves imaging quality. AIM: Aim of the study is to show if Ensemble Harmonic Imaging can improve imaging quality even in superficial areas of tissue in comparison to fundamental B-Mode-technique. METHODS: A Sonoline Elegra(R) high-end-scanner with 7.5 MHz linear array was used for this study. Differences of techniques ("fundamental"-sonographic-mode versus Ensemble Tissue Harmonic Imaging(R)-mode) are shown by investigation of six patients with various lesions of the head and neck area. CONCLUSION: In all cases there was a gain of resolution by using Ensemble Tissue Harmonic Imaging even in superficial areas. Ensemble Tissue Harmonic Imaging improves the sonographical resolution and reduces the artifacts.

Artifacts↗
PubMed1995

Computational methods for improving estimates of motor unit twitch contraction properties.

Estimates of mechanical properties of human motor units have usually been made indirectly, using the technique of "spike-triggered averaging" (STA). In this method, a single motor unit action potential is used to synchronize the accumulation of an ensemble average of correlated force transients. However, under most realizable conditions, these transients are recorded during periods of sustained motor unit discharge, in which each motor unit is producing a partially fused tetanus. Therefore, the STA technique extracts the characteristics of the unfused force transient, instead of the desired single motor unit twitch. Although the STA method has been widely used, there is as yet no well-established relation between the force transient in the unfused tetanus, and the twitch contraction properties of the motor unit. To evaluate the accuracy of the STA as a measure of the motor unit mechanical properties, we applied two types of muscle models to the force transients recorded in an unfused tetanus, using data derived from experiments in which the response to a single twitch was also recorded. Our objective was to see whether accurate predictions of single motor unit mechanical characteristics are possible, working backward from the STA. The models chosen for this task were a linear second order model, and the distribution-moment (DM) model. These model predictions were then compared with the STA response, and with the twitch properties of the individual motor units. We also evaluated the utility of extrapolating the initial slope of the STA backward to improve the accuracy of the mechanical estimates. The results of our simulation suggest that there is no straightforward relation between the characteristics of the unfused tetanus and the mechanical properties of the single twitch. Although our attempts to predict the properties of the single twitch from the STA were only partly successful, the results of the simulations were far more accurate than those derived from the STA alone. Because the errors in the use of the STA method were so substantial, we would urge that the STA technique be used with great caution as a measure of twitch contraction properties, unless accompanied by appropriate simulations of muscle mechanical behavior.

Animals↗
PubMed2001

How to guarantee optimal stability for most representative structures in the Protein Data Bank.

We proposed recently an optimization method to derive energy parameters for simplified models of protein folding. The method is based on the maximization of the thermodynamic average of the overlap between protein native structures and a Boltzmann ensemble of alternative structures. Such a condition enforces protein models whose ground states are most similar to the corresponding native states. We present here an extensive testing of the method for a simple residue-residue contact energy function and for alternative structures generated by threading. The optimized energy function guarantees high stability and a well-correlated energy landscape to most representative structures in the PDB database. Failures in the recognition of the native structure can be attributed to the neglect of interactions between different chains in oligomeric proteins or with cofactors. When these are taken into account, only very few X-ray structures are not recognized. Most of them are short inhibitors or fragments and one is a structure that presents serious inconsistencies. Finally, we discuss the reasons that make NMR structures more difficult to recognizeCopyright 2001 Wiley-Liss, Inc.

Computational Biology↗
PubMed2005

Analysis of worldwide earthquake mortality using multivariate demographic and seismic data.

In this paper, mortality in the immediate aftermath of an earthquake is studied on a worldwide scale using multivariate analysis. A statistical method is presented that analyzes reported earthquake fatalities as a function of a heterogeneous set of parameters selected on the basis of their presumed influence on earthquake mortality. The ensemble was compiled from demographic, seismic, and reported fatality data culled from available records of past earthquakes organized in a geographic information system. The authors consider the statistical relation between earthquake mortality and the available data ensemble, analyze the validity of the results in view of the parametric uncertainties, and propose a multivariate mortality analysis prediction method. The analysis reveals that, although the highest mortality rates are expected in poorly developed rural areas, high fatality counts can result from a wide range of mortality ratios that depend on the effective population size.

Disaster Planning↗
PubMed2001

The pair-functional method for direct solution of molecular structures. I. Statistical principles.

The pair-functional principle shows how to construct a unique statistical ensemble of strongly interacting atoms that corresponds to any feasible measured set of X-ray intensities. The ensemble and all its distribution functions are strictly periodic in the crystal lattice, so that each unit cell has exactly the same arrangement of atoms at all times. The mean particle density in the cell is uniform because the ensemble has undefined phases and the origin is not fixed. The atoms in this maximum-entropy ensemble interact through pairwise additive periodic statistical forces within the unit cell. The ensemble average pair-correlation function is matched to the observed originless Patterson function of the crystal. The derived pairing force then becomes approximately proportional to the Ornstein-Zernicke direct correlation function of the ensemble. The atoms have a many-body Boltzmann distribution and the logarithm of the likelihood of any particular conformation is related to its total pairing potential. The pairing potential of a group of atoms acts like a local field in the cell. This property is used in the pair-functional method. Molecular structures can be solved by a direct search in real space for clusters of atoms with high pair potentials. During a successful search, the atoms move from their original random positions to form larger and larger clusters of correctly formed fragments. Finally, every atom belongs to a single cluster, which is the correct solution.

Journal Article↗
PubMed2005

Nonlinear response of ozone to emissions: source apportionment and sensitivity analysis.

For secondary air pollutants, precursor emissions may impact concentrations in nonlinear and interdependent manners. We explore the nonlinear responses of one such pollutant, ozone, to emissions of its precursors, nitrogen oxides (NOx) and volatile organic compounds. Modeling is conducted for a high ozone episode in the southeastern United States, applying a second-order direct sensitivity method in a regional air quality model. As applied here, the sensitivity method neglects most aerosol and aqueous chemistry processes. Inclusion of second-order sensitivities is shown to enable accurate characterization of response to large perturbations in emissions. An index is introduced to characterize the nonlinearity of ozone response to NOx emitted from each source region. Nonlinearity is found to increase with the tonnage and emission density of the source region. Interactions among the impacts of emission sources are shown to lead to discrepancies between source contribution attributed to an ensemble of emitters and the sum of the contributions attributed to each component. A method is introduced for applying these "cross-sensitivity" interactions to assess the uncertainty of sensitivity and source apportionment estimates arising from uncertainty in an emissions inventory. For ozone response to NOx, underestimates in emission rates lead to underprediction of total source contribution but overprediction of per-ton sensitivity.

Air Pollutants↗
PubMed2003

Computing the transition state populations in simple protein models.

We describe the master equation method for computing the kinetics of protein folding. We illustrate the method using a simple Go model. Presently most models of two-state fast-folding protein folding kinetics invoke the classical idea of a transition state to explain why there is a single exponential decay in time. However, if proteins fold via funnel-shaped energy landscapes, as predicted by many theoretical studies, then it raises the question of what is the transition state. Is it a specific structure, or a small ensemble of structures, as is expected from classical transition state theory? Or is it more like the denatured states of proteins, a very broad ensemble? The answer that is usually obtained depends on the assumptions made about the transition state. The present method is a rigorous way to find transition states, without assumptions or approximations, even for very nonclassical shapes of energy landscapes. We illustrate the method here, showing how the transition states in two-state protein folding can be very broad ensembles.

Kinetics↗
PubMed2005

A study on several machine-learning methods for classification of malignant and benign clustered microcalcifications.

In this paper, we investigate several state-of-the-art machine-learning methods for automated classification of clustered microcalcifications (MCs). The classifier is part of a computer-aided diagnosis (CADx) scheme that is aimed to assisting radiologists in making more accurate diagnoses of breast cancer on mammograms. The methods we considered were: support vector machine (SVM), kernel Fisher discriminant (KFD), relevance vector machine (RVM), and committee machines (ensemble averaging and AdaBoost), of which most have been developed recently in statistical learning theory. We formulated differentiation of malignant from benign MCs as a supervised learning problem, and applied these learning methods to develop the classification algorithm. As input, these methods used image features automatically extracted from clustered MCs. We tested these methods using a database of 697 clinical mammograms from 386 cases, which included a wide spectrum of difficult-to-classify cases. We analyzed the distribution of the cases in this database using the multidimensional scaling technique, which reveals that in the feature space the malignant cases are not trivially separable from the benign ones. We used receiver operating characteristic (ROC) analysis to evaluate and to compare classification performance by the different methods. In addition, we also investigated how to combine information from multiple-view mammograms of the same case so that the best decision can be made by a classifier. In our experiments, the kernel-based methods (i.e., SVM, KFD, and RVM) yielded the best performance (Az = 0.85, SVM), significantly outperforming a well-established, clinically-proven CADx approach that is based on neural network (Az = 0.80).

Algorithms↗
PubMed2006

Automated QSPR through Competitive Workflow.

This paper describes a novel software architecture, Competitive Workflow, which implements workflow as a distributed and competitive multi-agent system. The implementation of a competitive workflow architecture designed to model important computer-aided molecular design workflows, the Discovery Bus, is described. QSPR modelling results for three example ADME datasets, for solubility, human plasma protein binding and P-glycoprotein substrates using an autonomous QSPR modelling workflow implemented on the Discovery Bus are presented. The autonomous QSPR system allows exhaustive exploration of descriptor and model space, automated model validation and continuous updating as new data and methods are made available. Prediction of properties of novel structures by an ensemble of models is also a feature of the system.

ATP Binding Cassette Transporter, Subfamily B, Mem↗
PubMed1993

Distribution of the iron-heme displacement as resulting from myoglobin conformational substrates: an AOM approach to the interpretation of the EPR spectra.

The electron paramagnetic resonance (EPR) low-temperature spectra of high spin ferric myoglobin samples in different solvent composition have been analyzed in terms of a distribution of the energy differences delta 1 and delta 2 for the iron low-lying electronic states. The widths of these distributions, which are found to be dependent on the solvent composition, have been correlated to the presence of a frozen ensemble of conformational substrates. A dedicated analysis based on the angular overlap method (AOM) has allowed us to work out a quantitative relationship between the delta 1 and delta 2 distributions and the spread of the iron-heme displacement; this being a structural parameter relevant for the biological functionality of the protein. The observed dependence of the iron-heme displacement distribution on the solvent composition is discussed.

Animals↗
PubMed1993

Monte Carlo simulation of lipid mixtures: finding phase separation.

The nonideal mixing of phosphatidylserine (PS) and phosphatidylcholine (PC) binary lipid mixtures was studied by computer simulation based on a model wherein the excess energy of mixing is divided between an electrostatic term and one adjustable term delta Em that includes all other nonideal interactions. The lateral distribution of the lipids and the energy of the mixtures were obtained by using Kawasaki relaxation in a canonical ensemble. The Gibbs free energies were calculated by Kirkwood's coupling parameter method. The simulation results are strongly dependent on simulation size for sizes smaller than about 1000 lipids. Nonideal interaction between lipids can result in large scale separation of lipid phases of different composition at reasonable delta Em values as well as clustering of like lipids. In plots of total Gibbs free energy of mixing versus PS mole fraction in PS/PC, the boundaries of the two phase region could be accurately determined. The electrostatic interaction influences cluster size and shape, and also the composition of phases in the two-phase region.

Biophysical Phenomena↗
PubMed2005

Unmixing of polymer blends confined in ultrathin films: crossover between two-dimensional and three-dimensional behavior.

The interplay between chain conformations and phase separation in binary symmetric polymer mixtures confined into thin films by "neutral" hard walls (i.e., walls that do not preferentially attract or repel one of the two components of the mixture) is studied by Monte Carlo simulations. Using the bond fluctuation model on a simple cubic lattice in the semi grand canonical ensemble, we locate the critical temperature of demixing via finite size scaling methods for a wide range of chain lengths (16 </= N </= 256 effective monomers per chain) and film thicknesses (2 </= D </= 19 lattice spacings). Simultaneously, we investigate the geometrical structure of the chains, showing that despite using melt densities there are pronounced "correlation hole effects", in particular for the smaller values of D. Also the components of the radius of gyration and end-to-end distance parallel and perpendicular to the confining walls are analyzed and their scaling behavior is studied. Evidence is presented that for strictly two-dimensional polymers (as occur for D = 2) the average number of intermolecular contacts scales with chain length N as z(c) proportional, variant N(-3/8) and therefore the critical temperature scales as T(c) proportional, variant N(5/8), whereas for values of D that exceed the excluded volume screening length, z(c) remains nonzero for N --> infinity, and hence T(c) proportional, variant N. However, strong deviations from the Flory-Huggins theory occur as long as the unperturbed chain dimension exceeds D, and the critical behavior falls in the universality class of the two-dimensional Ising model for any finite value of D.

Journal Article↗
PubMed2004

Nanoelectrodes, nanoelectrode arrays and their applications.

This review deals with the topic of ultrasmall electrodes, namely nanoelectrodes, arrays of these and discusses possible applications, including to analytical science. It deals exclusively with the use of nanoelectrodes in an electrochemical context. Benefits that accrue from use of very small working electrodes within electrochemical cells are discussed, followed by a review of methods for the preparation of such electrodes. Individual nanoelectrodes and arrays or ensembles of these are addressed, as are nanopore systems which seek to emulate biological transmembrane ion transport processes. Applications within physical electrochemistry, imaging science and analytical science are summarised.

Electrochemistry↗
PubMed2004

Spatially adaptive lattice coarse-grained Monte Carlo simulations for diffusion of interacting molecules.

While lattice kinetic Monte Carlo (KMC) methods provide insight into numerous complex physical systems governed by interatomic interactions, they are limited to relatively short length and time scales. Recently introduced coarse-grained Monte Carlo (CGMC) simulations can reach much larger length and time scales at considerably lower computational cost. In this paper we extend the CGMC methods to spatially adaptive meshes for the case of surface diffusion (canonical ensemble). We introduce a systematic methodology to derive the transition probabilities for the coarse-grained diffusion process that ensure the correct dynamics and noise, give the correct continuum mesoscopic equations, and satisfy detailed balance. Substantial savings in CPU time are demonstrated compared to microscopic KMC while retaining high accuracy.

Journal Article↗
PubMed1975

Matrix method for fluctuations and noise in kinetic systems.

In a series of papers we were concerned with the question of how to calculate the concentration noise power spectra of an ensemble of multi-state linear kinetic systems when the rate constants of the systems are assumed to be known. We have used a standard eigenvalue-eigenfunction method to solve the differential equations which govern the regression of the means and derived the noise power spectrum as a function of the eigenvalues and eigenfunctions of the relaxation matrix of the system. In this paper, we have obtained an equation which relates the noise spectrum matrix of the fluctuations directly to the relaxation matrix of the means. As a result, the noise power spectrum can be calculated through matrix operations without the necessity of an eigenvalue-eigenfunction calculation. The present formalism is particularly useful in the evaluation of kinetic rate constants when the noise spectrum data of concentration fluctuations are given. Possible applications to biochemical systems are briefly discussed.

Kinetics↗
PubMed2005

Thermodynamic theory of incompressible hydrodynamics.

The grand potential for open systems describes thermodynamics of fluid flows at low Mach numbers. A new system of reduced equations for the grand potential and the fluid momentum is derived from the compressible Navier-Stokes equations. The incompressible Navier-Stokes equations are the quasistationary solution to the new system. It is argued that the grand canonical ensemble is the unifying concept for the derivation of models and numerical methods for incompressible fluids, illustrated here with a simulation of a minimal Boltzmann model in a microflow setup.

Journal Article↗