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PubMed2003

An improved trilinear decomposition algorithm based on a Lagrange operator.

An improved trilinear decomposition algorithm based on a Lagrange operator (LO) is developed in this paper, which introduces a Lagrange operator and penalty terms in the loss function to improve the performance of the algorithm. Compared to the traditional parallel factor (PARAFAC) algorithm, the algorithm not only may converge much faster, but also overcome the sensibility to estimate the number of components. A set of simulated and measured excitation/emission fluorescence data were treated by both the proposed and traditional PARAFAC algorithm to compare their efficiencies. The analytical results obtained with real chemical system containing aspirin and its metabolic products show that the trilinear decomposition methodology is a promising tool to obtain spectral and composition information from mixtures without chemical separation.

Journal Article↗

PubMed2002

Local energy landscape flattening: parallel hyperbolic Monte Carlo sampling of protein folding.

Among the major difficulties in protein structure prediction is the roughness of the energy landscape that must be searched for the global energy minimum. To address this issue, we have developed a novel Monte Carlo algorithm called parallel hyperbolic sampling (PHS) that logarithmically flattens local high-energy barriers and, therefore, allows the simulation to tunnel more efficiently through energetically inaccessible regions to low-energy valleys. Here, we show the utility of this approach by applying it to the SICHO (SIde-CHain-Only) protein model. For the same CPU time, the parallel hyperbolic sampling method can identify much lower energy states and explore a larger region phase space than the commonly used replica sampling (RS) Monte Carlo method. By clustering the simulated structures obtained in the PHS implementation of the SICHO model, we can successfully predict, among a representative benchmark 65 proteins set, 50 cases in which one of the top 5 clusters have a root-mean-square deviation (RMSD) from the native structure below 6.5 A. Compared with our previous calculations that used RS as the conformational search procedure, the number of successful predictions increased by four and the CPU cost is reduced. By comparing the structure clusters produced by both PHS and RS, we find a strong correlation between the quality of predicted structures and the minimum relative RMSD (mrRMSD) of structures clusters identified by using different search engines. This mrRMSD correlation may be useful in blind prediction as an indicator of the likelihood of successful folds.

Models, Molecular↗

PubMed2006

DNA computing of solutions to knapsack problems.

One line of DNA computing research focuses on parallel search algorithms, which can be used to solve many optimization problems. DNA in solution can provide an enormous molecular library, which can be searched by molecular biological techniques. We have implemented such a parallel search for solutions to knapsack problems, which ask for the best way to pack a knapsack of limited volume. Several instances of knapsack problems were solved using DNA. We demonstrate how the computations can be extended by in vivo translation of the DNA library into protein. This combination of DNA and protein allows for multi-criterion optimization. The knapsack computations performed can then be seen as protein optimizations, one of the most complex computations performed by natural systems.

Algorithms↗

PubMed2001

A multithreaded parallel implementation of a dynamic programming algorithm for sequence comparison.

This paper discusses the issues involved in implementing a dynamic programming algorithm for biological sequence comparison on a general-purpose parallel computing platform based on a fine-grain event-driven multithreaded program execution model. Fine-grain multithreading permits efficient parallelism exploitation in this application both by taking advantage of asynchronous point-to-point synchronizations and communication with low overheads and by effectively tolerating latency through the overlapping of computation and communication. We have implemented our scheme on EARTH, a fine-grain event-driven multithreaded execution and architecture model which has been ported to a number of parallel machines with off-the-shelf processors. Our experimental results show that the dynamic programming algorithm can be efficiently implemented on EARTH systems with high performance (e.g., speedup of 90 on 120 nodes), good programmability and reasonable cost.

Algorithms↗

PubMed2005

Energy landscape of amyloidogenic peptide oligomerization by parallel-tempering molecular dynamics simulation: significant role of Asn ladder.

Recent evidence suggests that amyloidogenic oligomers may be the toxic species in cell cultures. Thus, it is crucial to understand their structure and oligomerization mechanism in atomistic detail. By employing tens of fast central processing units and an advanced phase-space sampling algorithm, parallel-tempering molecular dynamics, we have explored the energy landscape of amyloidogenic peptide oligomerization in explicit water. A pentapeptide, DFNKF, derived from human calcitonin and its mutant, DFAKF, was simulated with a total simulation time of approximately 500 ns. The detailed oligomerization process of a DFNKF parallel beta-sheet formation at 300 K has been characterized. The assembly of a parallel beta-sheet from the amorphous state mainly occurs via a "bottleneck" channel where the interstrand Asn-Asn stacking is the major interaction. The interactions of Asn-Asn stacking include both backbone and side-chain hydrogen bonds. The Asn-Asn interactions work like "glue" by sticking the DFNKF strands together and assist the "on-pathway" oligomerization. The Asn-Asn stacking observed here is similar to the Asn ladder commonly found in globular beta-helix proteins. A control run shows that when Asn is mutated to Ala, the stability and population of the DFAKF parallel beta-sheet is decreased. Furthermore, our in vitro mutagenesis experiments show that the ability of DFAKF peptides to form amyloid fibrils is significantly reduced, in agreement with the simulations. Knowledge of the energy landscape of oligomerization may provide hints for rational drug design, preventing amyloid-associated diseases.

Algorithms↗

PubMed2006

Cardiac CINE MR imaging with a 32-channel cardiac coil and parallel imaging: impact of acceleration factors on image quality and volumetric accuracy.

PURPOSE: To assess the impact of parallel imaging algorithms on image quality and volumetric accuracy of CINE magnetic resonance imaging (MRI) with high temporal and spatial resolution using a new 32-channel dedicated cardiac phased array coil. MATERIALS AND METHODS: Fourteen individuals underwent steady-state free precession (SSFP) CINE MRI using a 32-element phased-array coil and parallel imaging acceleration using spatiotemporal sensitivity encoding (TSENSE). Acquisition acceleration ranged from R = 2 to 7. In conjunction with data extracted from phantom measurements, contrast-to-noise ratio (CNR) performance was evaluated for each acceleration factor and subjective image quality was evaluated by two independent readers. In addition, volumetric assessment was performed for each acceleration factor based on a single breath-hold multi-slice data acquisition. Results were compared to nonTSENSE measurements. RESULTS: CNR for non-accelerated CINE (R = 1) was 45.7 +/- 12.8 and showed a constant decrease with increase in acceleration of 51% at R = 4 and 86% at R = 7. CNR losses accompanied reductions in subjective image quality. Volumetric evaluation was accurate for R <or= 4, with significant underestimation of ejection fraction (EF) at higher accelerations. CONCLUSION: This study shows that one-dimensional acceleration factors up to R = 4 allow accurate SSFP CINE MRI even though CNR is significantly reduced. This allows for a marked reduction in scan time and allows for multi-slice CINE imaging with high spatial and temporal resolution.

Adult↗

PubMed1995

LGANN: a parallel system combining a local genetic algorithm and neural networks for the prediction of secondary structure of proteins.

In this work we describe a parallel system consisting of feed-forward neural networks supervised by a local genetic algorithm. The system is implemented in a transputer architecture and is used to predict the secondary structures of globular proteins. This method allows a wide search in the parameter space of the neural networks and the determination of their optimal topology for the predictive task. Different neural network topologies are selected by the genetic algorithm on the basis of minimal values of mean square errors on the testing set. When the alpha-helix, beta-strand and random coil motifs of secondary structures are discriminated, the maximal efficiency obtained is 0.62, with correlation coefficients of 0.35, 0.31 and 0.37 respectively. This level of accuracy is similar to that previously attained by means of neural networks without hidden layers and using single protein sequences as input. The results validate the neural network topologies used for the prediction of protein secondary structures and highlight the relevance of the input information in determining the limit of their performance.

Algorithms↗

PubMed2024

GRable Version 1.0: A Software Tool for Site-Specific Glycoform Analysis With Improved MS1-Based Glycopeptide Detection With Parallel Clustering and Confidence Evaluation With MS2 Information.

High-throughput intact glycopeptide analysis is crucial for elucidating the physiological and pathological status of the glycans attached to each glycoprotein. Mass spectrometry-based glycoproteomic methods are challenging because of the diversity and heterogeneity of glycan structures. Therefore, we developed an MS1-based site-specific glycoform analysis method named "Glycan heterogeneity-based Relational IDentification of Glycopeptide signals on Elution profile (Glyco-RIDGE)" for a more comprehensive analysis. This method detects glycopeptide signals as a cluster based on the mass and chromatographic properties of glycopeptides and then searches for each combination of core peptides and glycan compositions by matching their mass and retention time differences. Here, we developed a novel browser-based software named GRable for semi-automated Glyco-RIDGE analysis with significant improvements in glycopeptide detection algorithms, including "parallel clustering." This unique function improved the comprehensiveness of glycopeptide detection and allowed the analysis to focus on specific glycan structures, such as pauci-mannose. The other notable improvement is evaluating the "confidence level" of the GRable results, especially using MS2 information. This function facilitated reduced misassignment of the core peptide and glycan composition and improved the interpretation of the results. Additional improved points of the algorithms are "correction function" for accurate monoisotopic peak picking; one-to-one correspondence of clusters and core peptides even for multiply sialylated glycopeptides; and "inter-cluster analysis" function for understanding the reason for detected but unmatched clusters. The significance of these improvements was demonstrated using purified and crude glycoprotein samples, showing that GRable allowed site-specific glycoform analysis of intact sialylated glycoproteins on a large-scale and in-depth. Therefore, this software will help us analyze the status and changes in glycans to obtain biological and clinical insights into protein glycosylation by complementing the comprehensiveness of MS2-based glycoproteomics. GRable can be freely run online using a web browser via the GlyCosmos Portal (https://glycosmos.org/grable).

Glycopeptides↗

PubMed2002

Favorable noise uniformity properties of Fourier-based interpolation and reconstruction approaches in single-slice helical computed tomography.

Volumes reconstructed by standard methods from single-slice helical computed tomography (CT) data have been shown to have noise levels that are highly nonuniform relative to those in conventional CT. These noise nonuniformities can affect low-contrast object detectability and have also been identified as the cause of the zebra artifacts that plague maximum intensity projection (MIP) images of such volumes. While these spatially variant noise levels have their root in the peculiarities of the helical scan geometry, there is also a strong dependence on the interpolation and reconstruction algorithms employed. In this paper, we seek to develop image reconstruction strategies that eliminate or reduce, at its source, the nonuniformity of noise levels in helical CT relative to that in conventional CT. We pursue two approaches, independently and in concert. We argue, and verify, that Fourier-based longitudinal interpolation approaches lead to more uniform noise ratios than do the standard 360LI and 180LI approaches. We also demonstrate that a Fourier-based fan-to-parallel rebinning algorithm, used as an alternative to fanbeam filtered backprojection for slice reconstruction, also leads to more uniform noise ratios, even when making use of the 180LI and 360LI interpolation approaches.

Algorithms↗

PubMed2001

Parameter optimisation of real-time control strategies for urban wastewater systems.

Real-time control (RTC) of wastewater systems has been a topic of research and application for over two decades. Attempts so far have mainly focused on one of the parts of the urban wastewater system: either the sewer system, or the treatment plant or the river. Approaches to integrate these subsystems and considering them jointly for control purposes have been pursued only recently. Control of the systems aims at pursuing one (or several concomitant) objectives, which are expressed, for example, in terms of overflow volumes, loads, effluent concentrations, receiving water quality or monetary costs, to name just a few. This paper provides a general and formal definition of the problem to define a real time control algorithm for a given urban wastewater system. A general mathematical optimization problem is formulated, which describes the task of finding an (in some sense) optimum control algorithm. Since this optimization problem is, in the general case, highly non-linear with only limited information available about the objective function itself, optimization methods appropriate for this type of problem are identified. Here, the similarity of the problem to find a control algorithm and of the parameter estimation problem common in mathematical modelling becomes apparent. Hence, methods (and problems encountered) in parameter estimation can be transferred to the problem of determining optimum RTC algorithms. This parallelism is outlined in the paper. As an application of the parameterisation and optimization of control strategies, integrated control of an urban wastewater system is discussed. Since the analysis of integrated control as just described poses certain requirements on a simulation engine, a novel modelling tool, called SYNOPSIS, is utilized here. This simulation tool, comprising of modules simulating water quantity and quality processes in all parts of the urban wastewater system, is embedded into a suite of optimization procedures. An integrated RTC algorithm for the urban wastewater system is formulated, the parameters of which are optimized using various global optimization routines. Comparison of their efficiency indicates good performance for the Controlled Random Search and for the genetic algorithms. The findings suggest that integrated control can indeed lead to an increase in performance of the urban wastewater system. These results appear to be encouraging and justify further work. Areas for further development are identified in the final section of the paper.

Algorithms↗

PubMed2000

Nonlinear identification of NMR spin systems by adaptive filtering.

In this paper, we present two new methods for identifying NMR spin systems. These methods are based on nonlinear adaptive filtering. The spin system is assumed to be time-invariant with memory. The first method uses a truncated discrete Volterra series to describe the nonlinear relationship between excitation (input) and system response (output). First-, second-, and third-order kernels of this series are estimated employing the least mean square (LMS) algorithm. Three parallel filters can then model the NMR spin system so that its output is no more than simple sum of three convolution products between combinations of the input signal and filters coefficients. It is also shown that the contribution of the Volterra second-order term to the total system response is neglected compared with the contributions of the first- and the third-order terms. In the second identification method, the output signal is related to the input signal through a recursive nonlinear difference equation with constant coefficients. The LMS algorithm is used again to estimate the equation coefficients. The two methods are validated with a simulated NMR system model based on Bloch equations. The results and the performances of these methods are analyzed and compared. It is shown that our methods permit a simple identification of NMR spin systems. The field of applications of this study is promising in the optimization of NMR signal detection, especially in the cases of low signal-to-noise ratios where optimum signal filtering and analysis must be performed.

Algorithms↗

PubMed1992

BIO-SPEAD: a parallel computing environment to accelerate development of biologic signal processing algorithms.

We have created BIO-SPEAD (pronounced speed), a BIOlogical Signal Processing Environment for Algorithm Development. BIO-SPEAD is designed to accelerate development of complex algorithms which integrate information derived from single or multiple physiologic waveforms. BIO-SPEAD currently performs all of the basic analyses of several arterial blood pressure waveforms, and allows the user to utilize the results of those low-level analyses for development of more complex algorithms. We utilized a parallel programming architecture called the Process Trellis which keeps the different tasks, or processes, within BIO-SPEAD independent of each other. Additionally, we have developed a graphics interface to enable the user to visualize the waveform under analysis, the low-level system analysis, and the internal workings of the algorithm under development. The system has been used for several algorithm development projects and has demonstrated its utility.

Algorithms↗

PubMed2005

Association between erectile dysfunction and coronary artery disease: a case report study.

Evidence is accumulating in favor of classifying erectile dysfunction (ED) as a vascular disorder. There are three main clinical scenarios in which ED and coronary artery disease (CAD) may coexist: the patient with ED who later develops CAD, the patient with overt CAD who is casually found to have ED, and the patient with acute coronary syndrome who has normal sexual function. This study presents three cases and discusses a "putative" pathophysiological mechanism underlying all these clinical presentations. Further studies, coupling functional and structural changes of coronary circulation with those of penile (i.e., dynamic penile test) circulation in each of these situations are mandatory to support this hypothesis.

Aged↗

PubMed1991

Predicting human immunodeficiency virus type 1-positive sera by using two enzyme immunoassay kits in a parallel testing format.

Two algorithms for screening sera for antibody to human immunodeficiency virus type 1 were compared for their efficiency in identifying a true-positive sample in a population with heterogeneous risk factors, using the criteria of specificity and positive predictive value (PPV). In the first algorithm, all sera were screened by using a single enzyme immunoassay (EIA) kit, and a specificity of 98.6% and a PPV of 69.3% was calculated for true-positive sera. The second algorithm employed two different EIA kits in parallel to screen each sample. In the first instance, a specificity and a PPV of 100% was calculated if a positive sample was defined as reactive by both EIA kits; in the second, a specificity of 99.97% and a PPV of 99.4% was obtained if this criterion was extended to include a combination of one reactive and one equivocal result obtained with the two EIA kits.

Algorithms↗

PubMedDate not supplied

Genealogy data design appropriate for family relationship retrieving.

Data structure representing a genealogy or genealogies as a stand-alone date structure is presented. Genealogy is considered as a finite, connected graph with nodes ni representing individuals, arcs (ni, nj), ordered pairs of nodes as parent-offspring relationships and edges (ni, nj), unordered pairs of nodes as twinships. Such structure enables storage of the minimum of family relationships and recognition of them and others like 'ancestor-descendant', 'sibs', 'twins', 'cousins', 'uncle/aunt-nephew/niece' or 'spouses'. Algorithms for genealogy retrieval are classified as vertical, lateral and parallel. In certain combinations, vertical and lateral algorithms become capable of finding any relatives, no matter if they are in a direct 'ancestor-descendant' relationship or if they have only the same ancestor(s). A parallel algorithm is designed in order to search for twins, triplets etc.

Algorithms↗

PubMed1990

Ab initio self-consistent field and potential-dependent partial equalization of orbital electronegativity calculations of hydration properties of N-acetyl-N'-methyl-alanineamide.

Using a recently developed parallel computation algorithm, ab initio self-consistent field (SCF) calculations were carried out to estimate the relative hydration energies for 12 low-energy conformations of N-acetyl-N'-methyl-alanineamide. The requisite SCF calculations were carried out using 6-31G and 6-31G* basis sets, both in the absence and presence of a perturbing potential arising from a model solvent. The alpha R, alpha L, polyproline II (PII), and pi helical conformations were preferentially stabilized by the solvent potential, whereas conformations with intramolecular hydrogen-bonding C5 and C7 were preferred in the gas phase. Average vicinal nmr coupling constants (JNH-C alpha H), calculated using the total energies of the various solvated conformations, were consistent with observed coupling constants for this peptide in aqueous solution. Substantial alteration of the solute charge density occurred upon equilibration with the reaction field, as was exemplified in changes both in the molecular dipole moments and in atom-centered multipoles, when the molecule was transferred from a medium of low dielectric constant to one of high dielectric constant. In order to model these changes in charge density with an empirical scheme, we have implemented a novel monopolar representation of the solute charge density based on a potential-dependent form of partial equalization of orbital electronegativities (PDPEOE). In the atom-centered point charge PDPEOE representation, charge flows from one region of the solute to another in response to external fields. Hydration energies calculated using the PDPEOE representation are similar to those calculated by the SCF procedure. Also, the PDPEOE calculations yielded changes in molecular dipole moments upon solvation that agreed closely with the changes in the calculated ab initio SCF dipole moments.

Alanine↗

PubMed2006

High-spin- and low-spin-state structures of [Fe(chloroethyltetrazole)6](ClO4)2 from synchrotron powder diffraction data.

The spin-crossover complex [Fe(teec)(6)](ClO(4))(2) (teec = chloroethyltetrazole) exhibits a 50 % incomplete spin crossover in the temperature range 300-30 K. Time-resolved synchrotron powder diffraction experiments have been carried out to elucidate its structural behavior. We report crystal structure models of this material at 300 K (high spin) and 90 K (low spin), as solved from synchrotron powder diffraction data by using Genetic Algorithm and Parallel Tempering techniques and refined with Rietveld refinement. During short synchrotron powder diffraction experiments (five minutes duration) two distinguishable lattices were observed the quantities of which vary with temperature. The implication of this phenomenon, that is interpreted as a structural phase transition associated with the high-to-low spin crossover, and the structural characteristics of the high-spin and low-spin models are discussed in relation to other compounds showing a similar type of spin-crossover behavior.

Journal Article↗

PubMed2000

Geometric and Topological Analysis of Three-Dimensional Porous Media: Pore Space Partitioning Based on Morphological Skeletonization.

This article presents a versatile, rigorous, and efficient methodology for extracting various geometric and topological parameters of 3D discrete porous media. The new approach takes advantage of the morphological skeleton of the pore structure-a lower dimensional representation of the pore space akin to the topological "deformation retract". The skeleton is derived by a fully parallel thinning algorithm that fulfils two essential requirements: it generates a medial axis and preserves the connectivity of the pore space. Topological analysis is accomplished by classifying all skeleton points as node or link (branch) points according to the concept of lambda-adjacency in 3D discrete space. In this manner, node coordination number and link length distributions are directly obtained from the skeleton. Pore necks (throats) are identified through a search for minima in the hydraulic radius of individual pore space channels outlined by skeleton links. In addition to the determination of the size distribution of the constrictions (pore necks) that control nonwetting phase invasion, improved estimates of the distributions of effective hydraulic and electric conductivity of individual pore space channels are obtained. Furthermore, erection of planes at the location of pore necks results in partitioning of the pore space into its constituent pores. This enables the characterization of the pore space in terms of a pore volume distribution. The new methodology is illustrated by application to a regular cubic pore network and irregularly shaped 2D and 3D pore networks generated by stochastic simulation. In the latter case, important new results are obtained concerning the sensitivity of geometric and topological properties of the microstructure to the parameters of stochastic simulation, namely, the porosity and correlation function. It is found that model porous media reconstructed from the same porosity and correlation function can exhibit marked differences in geometry and connectivity, which correlate with differences in specific surface area. Copyright 2000 Academic Press.

Journal Article↗