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PubMed2004

Quantum Monte Carlo method for the ground state of many-boson systems.

We formulate a quantum Monte Carlo (QMC) method for calculating the ground state of many-boson systems. The method is based on a field-theoretical approach, and is closely related to existing fermion auxiliary-field QMC methods which are applied in several fields of physics. The ground-state projection is implemented as a branching random walk in the space of permanents consisting of identical single-particle orbitals. Any single-particle basis can be used, and the method is in principle exact. We illustrate this method with a trapped atomic boson gas, where the atoms interact via an attractive or repulsive contact two-body potential. We choose as the single-particle basis a real-space grid. We compare with exact results in small systems and arbitrarily sized systems of untrapped bosons with attractive interactions in one dimension, where analytical solutions exist. We also compare with the corresponding Gross-Pitaevskii (GP) mean-field calculations for trapped atoms, and discuss the close formal relation between our method and the GP approach. Our method provides a way to systematically improve upon GP while using the same framework, capturing interaction and correlation effects with a stochastic, coherent ensemble of noninteracting solutions. We discuss various algorithmic issues, including importance sampling and the back-propagation technique for computing observables, and illustrate them with numerical studies. We show results for systems with up to N approximately 400 bosons.

Journal Article↗
PubMed2005

Entropy and density of states from isoenergetic nonequilibrium processes.

Two identities in statistical mechanics involving entropy differences (or ratios of densities of states) at constant energy are derived. The first provides a nontrivial extension of the Jarzynski equality to the microcanonical ensemble [C. Jarzynski, Phys. Rev. Lett. 78, 2690 (1997)], which can be seen as a "fast-switching" version of the adiabatic switching method for computing entropies [M. Watanabe and W. P. Reinhardt, Phys. Rev. Lett. 65, 3301 (1990)]. The second is a thermodynamic integration formula analogous to a well-known expression for free energies, and follows after taking the quasistatic limit of the first. Both identities can be conveniently used in conjunction with a scaling relation (herein derived) that allows one to extrapolate measurements taken at a single energy to a wide range of energy values. Practical aspects of these identities in the context of numerical simulations are discussed.

Journal Article↗
PubMed2002

Parametric classification of multichannel averaged event-related potentials.

This paper focuses on the systematic development of a parametric approach for classifying averaged event-related potentials (ERPs) recorded from multiple channels. It is shown that the parameters of the averaged ERP ensemble can be estimated directly from the parameters of the single-trial ensemble, thus, making it possible to design a class of parametric classifiers without having to collect a prohibitively large number of single-trial ERPs. An approach based on random sampling without replacement is developed to generate a large number of averaged ERP ensembles in order to evaluate the performance of a classifier. A two-class ERP classification problem is considered and the parameter estimation methods are applied to independently design a Gaussian likelihood ratio classifier for each channel. A fusion rule is formulated to classify an ERP using the classification results from all the channels. Experiments using real and simulated ERPs are designed to show that, through the approach developed, parametric classifiers can be designed and evaluated even when the number of averaged ERPs does not exceed the dimension of the ERP vector. Additionally, it is shown that the performance of a majority rule fusion classifier is consistently superior to the rule that selects a single best channel.

Computer Simulation↗
PubMed2025

A SuperLearner-based pipeline for the development of DNA methylation-derived predictors of phenotypic traits.

BACKGROUND: DNA methylation (DNAm) provides a window to characterize the impacts of environmental exposures and the biological aging process. Epigenetic clocks are often trained on DNAm using penalized regression of CpG sites, but recent evidence suggests potential benefits of training epigenetic predictors on principal components. METHODOLOGY/FINDINGS: We developed a pipeline to simultaneously train three epigenetic predictors; a traditional CpG Clock, a PCA Clock, and a SuperLearner PCA Clock (SL PCA). We gathered publicly available DNAm datasets to generate i) a novel childhood epigenetic clock, ii) a reconstructed Hannum adult blood clock, and iii) as a proof of concept, a predictor of polybrominated biphenyl exposure using the three developmental methodologies. We used correlation coefficients and median absolute error to assess fit between predicted and observed measures, as well as agreement between duplicates. The SL PCA clocks improved fit with observed phenotypes relative to the PCA clocks or CpG clocks across several datasets. We found evidence for higher agreement between duplicate samples run on alternate DNAm arrays when using SL PCA clocks relative to traditional methods. Analyses examining associations between relevant exposures and epigenetic age acceleration (EAA) produced more precise effect estimates when using predictions derived from SL PCA clocks. CONCLUSIONS: We introduce a novel method for the development of DNAm-based predictors that combines the improved reliability conferred by training on principal components with advanced ensemble-based machine learning. Coupling SuperLearner with PCA in the predictor development process may be especially relevant for studies with longitudinal designs utilizing multiple array types, as well as for the development of predictors of more complex phenotypic traits.

DNA Methylation↗
PubMed2005

Accurate FRET measurements within single diffusing biomolecules using alternating-laser excitation.

Fluorescence resonance energy transfer (FRET) between a donor (D) and an acceptor (A) at the single-molecule level currently provides qualitative information about distance, and quantitative information about kinetics of distance changes. Here, we used the sorting ability of confocal microscopy equipped with alternating-laser excitation (ALEX) to measure accurate FRET efficiencies and distances from single molecules, using corrections that account for cross-talk terms that contaminate the FRET-induced signal, and for differences in the detection efficiency and quantum yield of the probes. ALEX yields accurate FRET independent of instrumental factors, such as excitation intensity or detector alignment. Using DNA fragments, we showed that ALEX-based distances agree well with predictions from a cylindrical model of DNA; ALEX-based distances fit better to theory than distances obtained at the ensemble level. Distance measurements within transcription complexes agreed well with ensemble-FRET measurements, and with structural models based on ensemble-FRET and x-ray crystallography. ALEX can benefit structural analysis of biomolecules, especially when such molecules are inaccessible to conventional structural methods due to heterogeneity or transient nature.

Biophysics↗
PubMed1999

Heat balance when wearing protective clothing.

This issue of the Annals of Occupational Hygiene is dedicated to the topic of heat stress evaluation. For this evaluation, several evaluation programs and international standards are available. In order to understand the reasoning and underlying theory behind these programs and standards, a basic knowledge of heat exchange processes between workers and their environment is needed. This paper provides an overview of the relevant heat exchange processes, and defines the relevant parameters (air and radiant temperature, humidity, wind speed, metabolic heat production and clothing insulation). Further it presents in more detail the relation between clothing material properties and properties of clothing ensembles made from those materials. The effects of clothing design, clothing fit, and clothing air permeability are discussed, and finally an overview of methods for the determination of clothing heat and vapour resistance is given.

Body Temperature Regulation↗
PubMed2003

A de novo redesign of the WW domain.

We have used a sequence prediction algorithm and a novel sampling method to design protein sequences for the WW domain, a small beta-sheet motif. The procedure, referred to as SPANS, designs sequences to be compatible with an ensemble of closely related polypeptide backbones, mimicking the inherent flexibility of proteins. Two designed sequences (termed SPANS-WW1 and SPANS-WW2), using only naturally occurring L-amino acids, were selected for study and the corresponding polypeptides were prepared in Escherichia coli. Circular dichroism data suggested that both purified polypeptides adopted secondary structure features related to those of the target without the aid of disulfide bridges or bound cofactors. The structure exhibited by SPANS-WW2 melted cooperatively by raising the temperature of the solution. Further analysis of this polypeptide by proton nuclear magnetic resonance spectroscopy demonstrated that at 5 degrees C, it folds into a structure closely resembling a natural WW domain. This achievement constitutes one of a small number of successful de novo protein designs through fully automated computational methods and highlights the feasibility of including backbone flexibility in the design strategy.

Algorithms↗
PubMed2005

High-resolution protein folding with a transferable potential.

A generalized computational method for folding proteins with a fully transferable potential and geometrically realistic all-atom model is presented and tested on seven helix bundle proteins. The protocol, which includes graph-theoretical analysis of the ensemble of resulting folded conformations, was systematically applied and consistently produced structure predictions of approximately 3 A without any knowledge of the native state. To measure and understand the significance of the results, extensive control simulations were conducted. Graph theoretic analysis provides a means for systematically identifying the native fold and provides physical insight, conceptually linking the results to modern theoretical views of protein folding. In addition to presenting a method for prediction of structure and folding mechanism, our model suggests that an accurate all-atom amino acid representation coupled with a physically reasonable atomic interaction potential and hydrogen bonding are essential features for a realistic protein model.

Animals↗
PubMed2004

Alteration of neuronal firing properties after in vivo experience in a FosGFP transgenic mouse.

Identifying the cells and circuits that underlie perception, behavior, and learning is a central goal of contemporary neuroscience. Although techniques such as lesion analysis, functional magnetic resonance imaging, 2-deoxyglucose studies, and induction of gene expression have been helpful in determining the brain areas responsible for particular functions, these methods are technically limited. Currently, there is no method that allows for the identification and electrophysiological characterization of individual neurons that are associated with a particular function in living tissue. We developed a strain of transgenic mice in which the expression of the green fluorescent protein (GFP) is controlled by the promoter of the activity-dependent gene c-fos. These mice enable an in vivo or ex vivo characterization of the cells and synapses that are activated by particular pharmacological and behavioral manipulations. Cortical and subcortical fosGFP expression could be induced in a regionally restricted manner after specific activation of neuronal ensembles. Using the fosGFP mice to identify discrete cortical areas, we found that neurons in sensory-spared areas rapidly regulate action potential threshold and spike frequency to decrease excitability. This method will enhance our ability to study the way neuronal networks are activated and changed by both experience and pharmacological manipulations. In addition, because activated neurons can be functionally characterized, this tool may enable the development of better pharmaceuticals that directly affect the neurons involved in disease states.

Action Potentials↗
PubMed1996

Intensity resolution and subjective magnitude in psychophysical scaling.

Several successful theories of psychophysical judgment imply that exponents of power functions in scaling tasks should covary with measures of intensity resolution such as d' in the same tasks, whereas the prevailing metatheory of ideal psychophysical scaling asserts the independence of the two. In a direct test of this relationship, three prominent psychophysical scaling paradigms were studied: category judgment without an identification function, absolute magnitude estimation, and cross-modality matching with light intensity as the response continuum. Separate groups of subjects for each scaling paradigm made repeated judgments of the loudnesses of the pure tones that constituted each of two stimulus ensembles. The narrow- and wide-range ensembles shared six identical stimulus intensities in the middle of each set. Intensity resolution, as measured by d'-like distances, of these physically identical stimuli was significantly worse for the wide-range set for all three methods. Exponents of power functions fitted to geometric mean responses, and in magnitude estimation and cross-modality matching the geometric mean responses themselves, were also significantly smaller in the wide-range condition. The variation of power function exponents, and of psychophysical scale values, for stimulus intensities that were identical in the two stimulus sets with the intensities of other members of the ensembles is inconsistent with the metatheory on which modern psychophysical scaling practice is based, although it is consistent with other useful approaches to measurement of psychological magnitudes.

Adult↗
PubMed2005

The effect of contraction intensity on motor unit number estimates of the tibialis anterior.

OBJECTIVE: To examine the effect of contractile level on motor unit number estimates (MUNEs) and establish the contraction intensity that will yield the most representative MUNE for the tibialis anterior (TA) muscle. METHODS: Surface and intramuscular electromyographic (EMG) signals were collected during a range of submaximal (threshold, 10, 20, 30 and 40% MVC) isometric dorsiflexion contractions using decomposition-enhanced spike-triggered averaging (DE-STA). Six MUNEs were calculated, one for each of the five intensities, and an ensemble sixth MUNE that had equal MU contributions from all intensities. RESULTS: Mean surface-motor unit potential sizes increased significantly (26-69 microV) and MUNEs decreased accordingly (226-91) as contraction intensity increased from threshold to 40% MVC, respectively (P<0.05). The ensemble MUNE was 153, and extrapolated to approximately 25% MVC. CONCLUSIONS: There was a significant and progressive decline in the MUNE as contraction intensity increased, confirming the importance of monitoring torque during data collection. The ensemble MUNE suggests that collecting EMG signals at a contraction intensity of approximately 25% MVC provides the most representative sample of the actual number and sizes of MUs in the TA. SIGNIFICANCE: Establishing appropriate contraction intensities improves the utility of DE-STA as a useful method for tracking changes to the MU pool in disease states and healthy aging.

Action Potentials↗
PubMed2006

Accounting for loop flexibility during protein-protein docking.

Although reliable docking can now be achieved for systems that do not undergo important induced conformational change upon association, the presence of flexible surface loops, which must adapt to the steric and electrostatic properties of a partner, generally presents a major obstacle. We report here the first docking method that allows large loop movements during a systematic exploration of the possible arrangements of the two partners in terms of position and rotation. Our strategy consists in taking into account an ensemble of possible loop conformations by a multi-copy representation within a reduced protein model. The docking process starts from regularly distributed positions and orientations of the ligand around the whole receptor. Each starting configuration is submitted to energy minimization during which the best-fitting loop conformation is selected based on the mean-field theory. Trials were carried out on proteins with significant differences in the main-chain conformation of the binding loop between isolated form and complexed form, which were docked to their partner considered in their bound form. The method is able to predict complexes very close to the crystal complex both in terms of relative position of the two partners and of the geometry of the flexible loop. We also show that introducing loop flexibility on the isolated protein form during systematic docking largely improves the predictions of relative position of the partners in comparison with rigid-body docking.

Binding Sites↗
PubMed2005

Exploring the free-energy landscape of a short peptide using an average force.

The reversible folding of deca-alanine is chosen as a test case for characterizing a method that uses an adaptive biasing force (ABF) to escape from the minima and overcome the barriers of the free-energy landscape. This approach relies on the continuous estimation of a biasing force that yields a Hamiltonian in which no average force is exerted along the ordering parameter xi. Optimizing the parameters that control how the ABF is applied, the method is shown to be extremely effective when a nonequivocal ordering parameter can be defined to explore the folding pathway of the peptide. Starting from a beta-turn motif and restraining xi to a region of the conformational space that extends from the alpha-helical state to an ensemble of extended structures, the ABF scheme is successful in folding the peptide chain into a compact alpha helix. Sampling of this conformation is, however, marginal when the range of xi values embraces arrangements of greater compactness, hence demonstrating the inherent limitations of free-energy methods when ambiguous ordering parameters are utilized.

Alanine↗
PubMed2005

Ensemble dependence model for classification and prediction of cancer and normal gene expression data.

MOTIVATION: DNA microarray technologies make it possible to simultaneously monitor thousands of genes' expression levels. A topic of great interest is to study the different expression profiles between microarray samples from cancer patients and normal subjects, by classifying them at gene expression levels. Currently, various clustering methods have been proposed in the literature to classify cancer and normal samples based on microarray data, and they are predominantly data-driven approaches. In this paper, we propose an alternative approach, a model-driven approach, which can reveal the relationship between the global gene expression profile and the subject's health status, and thus is promising in predicting the early development of cancer. RESULTS: In this work, we propose an ensemble dependence model, aimed at exploring the group dependence relationship of gene clusters. Under the framework of hypothesis-testing, we employ genes' dependence relationship as a feature to model and classify cancer and normal samples. The proposed classification scheme is applied to several real cancer datasets, including cDNA, Affymetrix microarray and proteomic data. It is noted that the proposed method yields very promising performance. We further investigate the eigenvalue pattern of the proposed method, and we discover different patterns between cancer and normal samples. Moreover, the transition between cancer and normal patterns suggests that the eigenvalue pattern of the proposed models may have potential to predict the early stage of cancer development. In addition, we examine the effects of possible model mismatch on the proposed scheme.

Algorithms↗
PubMed2003

Optically induced multispin entanglement in a semiconductor quantum well.

According to quantum mechanics, a many-particle system is allowed to exhibit non-local behaviour, in that measurements performed on one of the particles can affect a second one that is far away. These so-called entangled states are crucial for the implementation of most quantum information protocols and, in particular, gates for quantum computation. Here we use ultrafast optical pulses and coherent techniques to create and control spin-entangled states in an ensemble of non-interacting electrons bound to donors (at least three) and at least two Mn2+ ions in a CdTe quantum well. Our method, relying on the exchange interaction between localized excitons and paramagnetic impurities, can in principle be applied to entangle an arbitrarily large number of spins.

Cadmium↗
PubMed2006

Min-map bias Monte Carlo for chain molecules: biased Monte Carlo sampling based on bijective minimum-to-minimum mapping.

A novel Monte Carlo (MC) simulation scheme based on Theodorou's bijective mapping strategy [D. N. Theodorou, J. Chem. Phys. 124, 034109 (2006)] is introduced. This min-map bias Monte Carlo acts in combination with any other proper, bare MC. It carries over the bare MC move from the original configuration space Omega(0), where trial move acceptance may be low, to a different configuration space, Omega(1), where acceptance is higher. The bare MC move is then performed in Omega(1) and the resulting configuration is finally mapped back to Omega(0). Mappings between Omega(0) and Omega(1) entail weighted selection of trial configurations, the bias of which is subsequently removed in the overall acceptance criterion. The new method is applied, in conjunction with continuum configurational bias as bare MC scheme, to the simulation of explicit hydrogen linear alkanes in the canonical ensemble. Min-map bias MC is found to alleviate the pervasive problem of very low acceptance rates encountered when using an explicit molecular description.

Journal Article↗
PubMed2001

Tighter decoding reliability bound for Gallager's error-correcting code.

Statistical physics is employed to evaluate the performance of error-correcting codes in the case of finite message length for an ensemble of Gallager's error correcting codes. We follow Gallager's approach of upper bounding the average decoding error rate, but invoke the replica method to reproduce the tightest general bound to date, and to improve on the most accurate zero-error noise level threshold reported in the literature. The relation between the methods used and those presented in the information theory literature are explored.

Journal Article↗
PubMed2002

Ensemble-based control of evolutionary optimization algorithms.

This paper presents a study on how the intrinsic search parameters of an evolutionary optimization algorithm can be automatically controlled. It will be shown that only a small search parameter window ensures good optimization results. This evolutionary window, enclosing effective values for the mutation rate and temperature, can be adapted to by carefully steering the ensemble's fitness dispersion. A control sensor based on an entropy measure is introduced to achieve this goal. The efficiency of the proposed control method will be tested by optimizing artificial sequences such as the well-known low autocorrelated binary strings and natural sequences including RNA.

Algorithms↗