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Results for “multiscale clustering”

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PubMed2002

Docking of flexible molecules using multiscale ligand representations.

Structural genomics will yield an immense number of protein three-dimensional structures in the near future. Automated theoretical methodologies are needed to exploit this information and are likely to play a pivotal role in drug discovery. Here, we present a fully automated, efficient docking methodology that does not require any a priori knowledge about the location of the binding site or function of the protein. The method relies on a multiscale concept where we deal with a hierarchy of models generated for the potential ligand. The models are created using the k-means clustering algorithm. The method was tested on seven protein-ligand complexes. In the largest complex, human immunodeficiency virus reverse transcriptase/nevirapin, the root mean square deviation value when comparing our results to the crystal structure was 0.29 A. We demonstrate on an additional 25 protein-ligand complexes that the methodology may be applicable to high throughput docking. This work reveals three striking results. First, a ligand can be docked using a very small number of feature points. Second, when using a multiscale concept, the number of conformers that require to be generated can be significantly reduced. Third, fully flexible ligands can be treated as a small set of rigid k-means clusters.

Algorithms↗

PubMed2002

Multiscale modeling of precipitate microstructure evolution.

We demonstrate how three "state-of-the-art" techniques may be combined to build a bridge between atomistics and microstructure: (1) first-principles calculations, (2) a mixed-space cluster expansion approach, and (3) the diffuse-interface phase-field model. The first two methods are used to construct the driving forces for a phase-field microstructural model of theta'- Al2Cu precipitates in Al: bulk, interfacial, and elastic energies. This multiscale approach allows one to isolate the physical effects responsible for precipitate microstructure evolution.

Journal Article↗

PubMed2006

Pvclust: an R package for assessing the uncertainty in hierarchical clustering.

SUMMARY: Pvclust is an add-on package for a statistical software R to assess the uncertainty in hierarchical cluster analysis. Pvclust can be used easily for general statistical problems, such as DNA microarray analysis, to perform the bootstrap analysis of clustering, which has been popular in phylogenetic analysis. Pvclust calculates probability values (p-values) for each cluster using bootstrap resampling techniques. Two types of p-values are available: approximately unbiased (AU) p-value and bootstrap probability (BP) value. Multiscale bootstrap resampling is used for the calculation of AU p-value, which has superiority in bias over BP value calculated by the ordinary bootstrap resampling. In addition the computation time can be enormously decreased with parallel computing option.

Algorithms↗

PubMed2000

Multiscale modelling of plastic flow localization in irradiated materials

The irradiation of metals by energetic particles causes significant degradation of the mechanical properties, most notably an increased yield stress and decreased ductility, often accompanied by plastic flow localization. Such effects limit the lifetime of pressure vessels in nuclear power plants, and constrain the choice of materials for fusion-based alternative energy sources. Although these phenomena have been known for many years, the underlying fundamental mechanisms and their relation to the irradiation field have not been clearly demonstrated. Here we use three-dimensional multiscale simulations of irradiated metals to reveal the mechanisms underlying plastic flow localization in defect-free channels. We observe dislocation pinning by irradiation-induced clusters of defects, subsequent unpinning as defects are absorbed by the dislocations, and cross-slip of the latter as the stress is increased. The width of the plastic flow channels is limited by the interaction among opposing dislocation dipole segments and the remaining defect clusters.

Journal Article↗

PubMed2006

Multiscale Monte Carlo algorithm for simple fluids.

We introduce a multiscale Monte Carlo algorithm to simulate dense simple fluids. The probability of an update follows a power law distribution in its length scale. The collective motion of clusters of particles requires generalization of the Metropolis update rule to impose detailed balance. We apply the method to the simulation of a Lennard-Jones fluid and show improvements in efficiency over conventional Monte Carlo and molecular dynamics simulations, eliminating hydrodynamic slowing down.

Colloids↗

PubMed2003

The contact mechanics of fractal surfaces.

The role of surface roughness in contact mechanics is relevant to processes ranging from adhesion to friction, wear and lubrication. It also promises to have a deep impact on applied science, including coatings technology and design of microelectromechanical systems. Despite the considerable results achieved by indentation experiments, particularly in the measurement of bulk hardness on nanometre scales, the contact behaviour of realistic surfaces, showing random multiscale roughness, remains largely unknown. Here we report experimental results concerning the mechanical response of self-affine thin films indented by a micrometric flat probe. The specimens, made of cluster-assembled carbon or of sexithienyl, an organic molecular material, were chosen as prototype systems for the broad class of self-affine fractal interfaces, today including surfaces grown under non-equilibrium conditions, fractures, manufactured metal surfaces and solidified liquid fronts. We observe that a regime exists in which roughness drives the contact mechanics: in this range surface stiffness varies by a few orders of magnitude on small but significant changes of fractal parameters. As a consequence, we demonstrate that soft solid interfaces can be appreciably strengthened by reducing both fractal dimension and surface roughness. This indicates a general route for tailoring the mechanical properties of solid bodies.

Carbon↗

PubMed2006

Multiscale modeling of macromolecular conformational changes combining concepts from rigidity and elastic network theory.

The development of a two-step approach for multiscale modeling of macromolecular conformational changes is based on recent developments in rigidity and elastic network theory. In the first step, static properties of the macromolecule are determined by decomposing the molecule into rigid clusters by using the graph-theoretical approach FIRST and an all-atom representation of the protein. In this way, rigid clusters are not limited to consist of residues adjacent in sequence or secondary structure elements as in previous studies. Furthermore, flexible links between rigid clusters are identified and can be modeled as such subsequently. In the second step, dynamical properties of the molecule are revealed by the rotations-translations of blocks approach (RTB) using an elastic network model representation of the coarse-grained protein. In this step, only rigid body motions are allowed for rigid clusters, whereas links between them are treated as fully flexible. The approach was tested on a data set of 10 proteins that showed conformational changes on ligand binding. For efficiency, coarse-graining the protein results in a remarkable reduction of memory requirements and computational times by factors of 9 and 27 on average and up to 25 and 125, respectively. For accuracy, directions and magnitudes of motions predicted by our approach agree well with experimentally determined ones, despite embracing in extreme cases >50% of the protein into one rigid cluster. In fact, the results of our method are in general comparable with when no or a uniform coarse-graining is applied; and the results are superior if the movement is dominated by loop or fragment motions. This finding indicates that explicitly distinguishing between flexible and rigid regions is advantageous when using a simplified protein representation in the second step. Finally, motions of atoms in rigid clusters are also well predicted by our approach, which points to the need to consider mobile protein regions in addition to flexible ones when modeling correlated motions.

Elasticity↗

PubMed2006

Longitudinal course of depression symptoms in multiple sclerosis.

BACKGROUND: Despite the high lifetime prevalence of depression in multiple sclerosis (MS), its longitudinal course is poorly understood. OBJECTIVE: To examine the longitudinal course of and reliable change in different depression symptom clusters in MS, and the longitudinal association of interferon beta treatment and coping with depression symptoms. METHODS: 53 MS patients were examined at two time points three years apart on the Beck Depression Inventory (BDI) and the Chicago Multiscale Depression Inventory (CMDI). RESULTS: Correlations from time 1 to time 2 for BDI, CMDI-total, CMDI-evaluative scale, and CMDI-vegetative scale were all highly significant, and reliable change indices reflected little change over time. In contrast, the correlation over time for the CMDI-mood scale was significantly lower (p<0.05) than the CMDI-evaluative and CMDI-vegetative scale correlations, and over 40% of patients showed reliable change. Patients who improved in their mood showed increased use of active coping, while patients who worsened showed decreased active coping strategies; the latter were also significantly more likely to have been taking interferon beta drugs at both time points than patients who did not change in their mood functioning. CONCLUSIONS: Mood symptoms of depression are significantly more variable over time than neurovegetative or negative evaluative symptoms in MS patients. Decreased use of active coping strategies may put patients at risk of increased depressed mood, whereas increased use of active coping may result in decreased depressed mood longitudinally. Interferon beta use may put patients at risk of increases in depressed mood.

Adaptation, Psychological↗

PubMed2004

Multiscale simulations of carbon nanotube nucleation and growth: electronic structure calculations.

Several first-principles surface and bulk electronic structure calculations relating to the nucleation and growth of single-wall carbon nanotubes are described. Density-functional theory in various forms is used throughout. In the surface-related calculations, a 38-atom Ni cluster and several low-index Ni surfaces are investigated using pseudopotentials and plane-wave expansions. The energetic ordering of the sites for C atom adsorption is found to be the same, with the Ni(100) facet favored. The bulk diffusion coefficient of C in Ni as a function of cluster size and temperature is calculated from various molecular dynamics approaches. In another group of bulk-related calculations, Gaussian orbital basis sets are used to study a cluster or "flake" containing 14 C atoms. The flake is a segment of three hexagons from an "unrolled" carbon nanotube, with an armchair termination. The binding energies of C, Ni, Co, Fe, Cu, and Au atoms to it were calculated in an effort to gain insight into the mechanism for the high catalytic activity of Ni, Co, and Fe and the lack of it in Cu and Au. The binding energies of Cu and Au are about 1 eV less than those of the three catalytic elements. Similar methods are used to study the initial stages of nanotube growth within the context of classical nucleation theory. Finally, issues relating to the establishment of a fundamental catalytic mechanism are addressed.

Adsorption↗

PubMed2007

Direct curvature scale space: theory and corner detection.

The Curvature Scale Space (CSS) technique is considered to be a modern tool in image processing and computer vision. Direct Curvature Scale Space (DCSS) is defined as the CSS that results from convolving the curvature of a planar curve with a Gaussian kernel directly. In this paper we present a theoretical analysis of DCSS in detecting corners on planar curves. The scale space behavior of isolated single and double corner models is investigated and a number of model properties are specified which enable us to transform a DCSS image into a tree organization and, so that corners can be detected in a multiscale sense. To overcome the sensitivity of DCSS to noise, a hybrid strategy to apply CSS and DCSS is suggested.

Algorithms↗

PubMed2005

Decentralized formation flying control in a multiple-team hierarchy.

In recent years, formation flying has been recognized as an enabling technology for a variety of mission concepts in both the scientific and defense arenas. Examples of developing missions at NASA include magnetospheric multiscale (MMS), solar imaging radio array (SIRA), and terrestrial planet finder (TPF). For each of these missions, a multiple satellite approach is required in order to accomplish the large-scale geometries imposed by the science objectives. In addition, the paradigm shift of using a multiple satellite cluster rather than a large, monolithic spacecraft has also been motivated by the expected benefits of increased robustness, greater flexibility, and reduced cost. However, the operational costs of monitoring and commanding a fleet of close-orbiting satellites is likely to be unreasonable unless the onboard software is sufficiently autonomous, robust, and scalable to large clusters. This paper presents the prototype of a system that addresses these objectives-a decentralized guidance and control system that is distributed across spacecraft using a multiple team framework. The objective is to divide large clusters into teams of "manageable" size, so that the communication and computation demands driven by N decentralized units are related to the number of satellites in a team rather than the entire cluster. The system is designed to provide a high level of autonomy, to support clusters with large numbers of satellites, to enable the number of spacecraft in the cluster to change post-launch, and to provide for on-orbit software modification. The distributed guidance and control system will be implemented in an object-oriented style using a messaging architecture for networking and threaded applications (MANTA). In this architecture, tasks may be remotely added, removed, or replaced post launch to increase mission flexibility and robustness. This built-in adaptability will allow software modifications to be made on-orbit in a robust manner. The prototype system, which is implemented in Matlab, emulates the object-oriented and message-passing features of the MANTA software. In this paper, the multiple team organization of the cluster is described, and the modular software architecture is presented. The relative dynamics in eccentric reference orbits is reviewed, and families of periodic, relative trajectories are identified, expressed as sets of static geometric parameters. The guidance law design is presented, and an example reconfiguration scenario is used to illustrate the distributed process of assigning geometric goals to the cluster. Next, a decentralized maneuver planning approach is presented that utilizes linear-programming methods to enact reconfiguration and coarse formation keeping maneuvers. Finally, a method for performing online collision avoidance is discussed, and an example is provided to gauge its performance.

Journal Article↗

PubMed2003

Morphology and microstructure at different scales of porous silicon prepared by a nonconventional technique.

In this work we present first results concerning the detailed structure of porous silicon (PS) layers prepared by a new method using a vapour-etching (VE)-based technique. Studies of the photoluminescence properties of VE-based PS show that the visible emission occurs at high energies as compared with PS prepared by conventional techniques. To understand the VE-based PS features, we need to point out the PS microstructure throughout its general morphology. For this purpose a microscopy multiscale study was done. Scanning, conventional transmission, and high-resolution transmission electron microscopes were employed. The investigations were made on PS films prepared from moderately and heavily doped n- and p-type silicon. SEM images show that VE-based PS layers are essentially formed of clusters like interconnected structures. TEM studies show that these clusters are composed of nanocrystallites with different shapes. The effect of the doping type of the starting Si substrate on the characteristics of the PS layers was examined (thickness, porosity, behavior). Pore propagation was found to depend on doping type. The crystallinity of the PS layers was also locally studied in depth.

Crystallization↗

PubMed2026

Mixing chromatin fibers with different nucleosome repeat lengths changes dynamics of chromatin phase separation.

The eukaryotic genome is organized into chromatin at multiple lengths and timescales. Liquid-liquid phase separation has recently emerged as a mechanism for the dynamic compartmentalization of chromatin. However, it remains unclear how cells can locally alter phase separation behavior to condense, decondense, and segregate specific regions of their genome. Selective interactions between chromatin fibers with different nucleosome repeat lengths (NRLs), as well as their incorporation into existing condensates composed of different NRL chromatin fibers, may provide a pathway for such processes. Using fluorescence microscopy, we investigated how these mechanisms influence the formation, coalescence, and maturation of chromatin condensates. Our results show distinct NRL-dependent mixing behaviors of chromatin before and after condensate formation. 167 and 197 NRL fibers, known to fold into compact fibers by strong nucleosome stacking interactions, formed amorphous condensates. In contrast, 172 and 202 NRL fibers, which only allow for weak stacking, formed spherical condensates. When NRLs were mixed, amorphous condensates exhibited localized clustering of identical NRLs. In spherical condensates, however, both NRLs were homogeneously distributed, with a varying NRL ratio per condensate. In addition, incorporation of 167 NRLs into preexisting 172 NRL condensates resulted in a multiphase structure where 167 NRL fibers formed an outer layer. These findings present an intrinsic link between DNA sequence, nucleosome positioning, local chromatin configuration and multiscale phase separation behavior. More broadly, they contribute to a deeper understanding of the dynamic methods of genome organization employed by eukaryotic organisms.

chromatin↗

PubMed2004

A hierarchical approach to all-atom protein loop prediction.

The application of all-atom force fields (and explicit or implicit solvent models) to protein homology-modeling tasks such as side-chain and loop prediction remains challenging both because of the expense of the individual energy calculations and because of the difficulty of sampling the rugged all-atom energy surface. Here we address this challenge for the problem of loop prediction through the development of numerous new algorithms, with an emphasis on multiscale and hierarchical techniques. As a first step in evaluating the performance of our loop prediction algorithm, we have applied it to the problem of reconstructing loops in native structures; we also explicitly include crystal packing to provide a fair comparison with crystal structures. In brief, large numbers of loops are generated by using a dihedral angle-based buildup procedure followed by iterative cycles of clustering, side-chain optimization, and complete energy minimization of selected loop structures. We evaluate this method by using the largest test set yet used for validation of a loop prediction method, with a total of 833 loops ranging from 4 to 12 residues in length. Average/median backbone root-mean-square deviations (RMSDs) to the native structures (superimposing the body of the protein, not the loop itself) are 0.42/0.24 A for 5 residue loops, 1.00/0.44 A for 8 residue loops, and 2.47/1.83 A for 11 residue loops. Median RMSDs are substantially lower than the averages because of a small number of outliers; the causes of these failures are examined in some detail, and many can be attributed to errors in assignment of protonation states of titratable residues, omission of ligands from the simulation, and, in a few cases, probable errors in the experimentally determined structures. When these obvious problems in the data sets are filtered out, average RMSDs to the native structures improve to 0.43 A for 5 residue loops, 0.84 A for 8 residue loops, and 1.63 A for 11 residue loops. In the vast majority of cases, the method locates energy minima that are lower than or equal to that of the minimized native loop, thus indicating that sampling rarely limits prediction accuracy. The overall results are, to our knowledge, the best reported to date, and we attribute this success to the combination of an accurate all-atom energy function, efficient methods for loop buildup and side-chain optimization, and, especially for the longer loops, the hierarchical refinement protocol.

Algorithms↗

PubMed2004

Spatiotemporal wavelet analysis for functional MRI.

Characterizing the spatiotemporal behavior of the BOLD signal in functional Magnetic Resonance Imaging (fMRI) is a central issue in understanding brain function. While the nature of functional activation clusters is fundamentally heterogeneous, many current analysis approaches use spatially invariant models that can degrade anatomic boundaries and distort the underlying spatiotemporal signal. Furthermore, few analysis approaches use true spatiotemporal continuity in their statistical formulations. To address these issues, we present a novel spatiotemporal wavelet procedure that uses a stimulus-convolved hemodynamic signal plus correlated noise model. The wavelet fits, computed by spatially constrained maximum-likelihood estimation, provide efficient multiscale representations of heterogeneous brain structures and give well-identified, parsimonious spatial activation estimates that are modulated by the temporal fMRI dynamics. In a study of both simulated data and actual fMRI memory task experiments, our new method gave lower mean-squared error and seemed to result in more localized fMRI activation maps compared to models using standard wavelet or smoothing techniques. Our spatiotemporal wavelet framework suggests a useful tool for the analysis of fMRI studies.

Algorithms↗

PubMed2005

Is dissociation a multidimensional construct? Data from the Multiscale Dissociation Inventory.

The dimensionality of dissociation was examined in a combined sample of 1,326 general population, clinical, and university participants who completed the Multiscale Dissociation Inventory (MDI). Principal components analysis identified five moderately intercorrelated factors (mean r = .39): Disengagement, Identity Dissociation, Emotional Constriction, Memory Disturbance, and Depersonalization/Derealization. Differential relationships were found between individual MDI factors and demographics, trauma history, clinical status, posttraumatic stress, and scores on other dissociation measures. Surprisingly, after controlling for sex and age, trauma exposure accounted for only 3 to 7% of the variance in MDI factors. The notion of dissociation as a general trait was not supported. Instead, dissociation may represent a variety of phenomenologically distinct and only moderately related symptom clusters whose ultimate commonality is more theoretical than empirical.

Adolescent↗

PubMed2006

Monocular precrash vehicle detection: features and classifiers.

Robust and reliable vehicle detection from images acquired by a moving vehicle (i.e., on-road vehicle detection) is an important problem with applications to driver assistance systems and autonomous, self-guided vehicles. The focus of this work is on the issues of feature extraction and classification for rear-view vehicle detection. Specifically, by treating the problem of vehicle detection as a two-class classification problem, we have investigated several different feature extraction methods such as principal component analysis, wavelets, and Gabor filters. To evaluate the extracted features, we have experimented with two popular classifiers, neural networks and support vector machines (SVMs). Based on our evaluation results, we have developed an on-board real-time monocular vehicle detection system that is capable of acquiring grey-scale images, using Ford's proprietary low-light camera, achieving an average detection rate of 10 Hz. Our vehicle detection algorithm consists of two main steps: a multiscale driven hypothesis generation step and an appearance-based hypothesis verification step. During the hypothesis generation step, image locations where vehicles might be present are extracted. This step uses multiscale techniques not only to speed up detection, but also to improve system robustness. The appearance-based hypothesis verification step verifies the hypotheses using Gabor features and SVMs. The system has been tested in Ford's concept vehicle under different traffic conditions (e.g., structured highway, complex urban streets, and varying weather conditions), illustrating good performance.

Accidents, Traffic↗

PubMed2026

Integrative quantum and systems biology of cancer: From molecular fluctuations to ecological outcomes.

This review treats cancer as a multiscale adaptive system, asks what the framework must predict to be worth adopting, and separates at each scale what the evidence establishes from what is proposed. It is an expert narrative synthesis, not a systematic review, and states the limits of that design. Proton transfer and tautomeric shifts contribute to spontaneous mispairing but do not license claims of directed or non-random mutation: replication timing, three-dimensional chromatin organization, sequence context and known mutagenic processes explain most mutational heterogeneity, leaving any quantum contribution as a residual against that baseline. The Waddington quasi-potential is bounded: outside detailed balance the dynamics are not gradient-derivable and require a probability-flux term. Hysteresis, rate-limited bimodality and return to state after perturbation distinguish an attractor from a transcriptomic cluster. Single-cell karyotype and live-imaging evidence supports whole-genome doubling as an unstable intermediate of heterogeneous origin and context-dependent consequence, not a uniform adaptive strategy. Systems and synthetic biology, virtual cells and digital twins are assessed against benchmarks, not promise. Tissue-scale ecology is reported with the spatial measurements now quantifying it, including evidence that stromal niche construction is not uniformly tumor-supporting. RNA modification is a layer in its own right, showing that the interpretation of a regulatory signal, not its magnitude, is biologically decisive. A dedicated section states the framework's commitments, the observable and evidence at each scale, and what would falsify them, asking what this adds to somatic mutation theory with clonal evolution and plasticity.

Neoplasms↗