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PubMed1998

Colloidal Particles at Water-Glass Interface: Analyzing Videomicroscopic Data.

Direct videomicroscopic observations provide a powerful tool for investigations on the deposition of colloidal particles at liquid-solid interfaces. However, the technique is also capable of producing artefacts caused mainly by limited resolution. In the present contribution we discuss the possibilities and limitations of videomicroscopic observations, focussing thereby on an application example, namely particle deposition from flow in a parallel plate channel in the presence of a repulsive barrier. We outline algorithms for the determination of the relevant quantities, indicate the pitfalls, and provide correction formulas. Special attention is paid to the kinetics of particle release, namely to the accurate determination of the distribution of the times the particles spend adhering to the surface. In our example the kinetics of the release is found to be highly nonexponential, but an adequate fit of the measured distribution of adhesion times is obtained with a stretched exponential exp[-(betatau)nu], where nu approximately 0.5 and beta approximately 3 x 10(-5) s-1. Copyright 1998 Academic Press.

Journal Article↗

PubMed1990

Generalized gradient schemes for the measurement of two-dimensional image motion.

This paper describes a procedure for recovering the global velocity of an image by incorporating spatial filtering, and optionally, temporal filtering, into a scheme that employs a generalized version of the gradient algorithm of motion detection. Motion within a patch is analysed by six parallel channels, each incorporating a different spatiotemporal filter. Advantageous features of this scheme are: (a) global velocity is derived directly, without first computing local velocity at a number of image locations; (b) the filters compute first derivatives rather than second derivatives, making the scheme potentially more resistant to noise than certain other schemes; (c) two of the six filters can be chosen almost completely arbitrarily, and can therefore be tailored to maximize signal reliability, and (d) the measurement of velocity can be made as local or as global as desired by altering the size of the patch that is viewed by the filters. An analogous scheme is derived for the measurement of rotation as well as expansion or contraction of the image.

Animals↗

PubMed2003

Biopipe: a flexible framework for protocol-based bioinformatics analysis.

We identify several challenges facing bioinformatics analysis today. Firstly, to fulfill the promise of comparative studies, bioinformatics analysis will need to accommodate different sources of data residing in a federation of databases that, in turn, come in different formats and modes of accessibility. Secondly, the tsunami of data to be handled will require robust systems that enable bioinformatics analysis to be carried out in a parallel fashion. Thirdly, the ever-evolving state of bioinformatics presents new algorithms and paradigms in conducting analysis. This means that any bioinformatics framework must be flexible and generic enough to accommodate such changes. In addition, we identify the need for introducing an explicit protocol-based approach to bioinformatics analysis that will lend rigorousness to the analysis. This makes it easier for experimentation and replication of results by external parties. Biopipe is designed in an effort to meet these goals. It aims to allow researchers to focus on protocol design. At the same time, it is designed to work over a compute farm and thus provides high-throughput performance. A common exchange format that encapsulates the entire protocol in terms of the analysis modules, parameters, and data versions has been developed to provide a powerful way in which to distribute and reproduce results. This will enable researchers to discuss and interpret the data better as the once implicit assumptions are now explicitly defined within the Biopipe framework.

Amino Acid Sequence↗

PubMed2003

Update statistics in conservative parallel-discrete-event simulations of asynchronous systems.

We model the performance of an ideal closed chain of L processing elements that work in parallel in an asynchronous manner. Their state updates follow a generic conservative algorithm. The conservative update rule determines the growth of a virtual time surface. The physics of this growth is reflected in the utilization (the fraction of working processors) and in the interface width. We show that it is possible to make an explicit connection between the utilization and the microscopic structure of the virtual time interface. We exploit this connection to derive the theoretical probability distribution of updates in the system within an approximate model. It follows that the theoretical lower bound for the computational speedup is s=(L+1)/4 for L> or =4. Our approach uses simple statistics to count distinct surface-configuration classes consistent with the model growth rule. It enables one to compute analytically microscopic properties of an interface, which are unavailable by continuum methods.

Journal Article↗

PubMed2006

High-performance medical image registration using new optimization techniques.

Optimization of a similarity metric is an essential component in intensity-based medical image registration. The increasing availability of parallel computers makes parallelizing some registration tasks an attractive option to increase speed. In this paper, two new deterministic, derivative-free, and intrinsically parallel optimization methods are adapted for image registration. DIviding RECTangles (DIRECT) is a global technique for linearly bounded problems, and multidirectional search (MDS) is a recent local method. The performance of DIRECT, MDS, and hybrid methods using a parallel implementation of Powell's method for local refinement, are compared. Experimental results demonstrate that DIRECT and MDS are robust, accurate, and substantially reduce computation time in parallel implementations.

Algorithms↗

PubMed2005

Terahertz wide aperture reflection tomography.

We describe a powerful imaging modality for terahertz (THz) radiation, THz wide aperture reflection tomography (WART). Edge maps of an object's cross section are reconstructed from a series of time-domain reflection measurements at different viewing angles. Each measurement corresponds to a parallel line projection of the object's cross section. The filtered backprojection algorithm is applied to recover the image from the projection data. To our knowledge, this is the first demonstration of a reflection computed tomography technique using electromagnetic waves. We demonstrate the capabilities of THz WART by imaging the cross sections of two test objects.

Journal Article↗

PubMed1993

Protein structure prediction: selecting salient features from large candidate pools.

We introduce a parallel approach, "DT-SELECT," for selecting features used by inductive learning algorithms to predict protein secondary structure. DT-SELECT is able to rapidly choose small, nonredundant feature sets from pools containing hundreds of thousands of potentially useful features. It does this by building a decision tree, using features from the pool, that classifies a set of training examples. The features included in the tree provide a compact description of the training data and are thus suitable for use as inputs to other inductive learning algorithms. Empirical experiments in the protein secondary-structure task, in which sets of complex features chosen by DT-SELECT are used to augment a standard artificial neural network representation, yield surprisingly little performance gain, even though features are selected from very large feature pools. We discuss some possible reasons for this result.

Algorithms↗

PubMed2005

Calibration of stereo cameras from two perpendicular planes.

We present a novel linear algorithm with which to calibrate stereo cameras from two perpendicular planes. Stereo cameras are two cameras aligned in a special configuration with coplanar image planes and parallel axes that are increasingly more widely used in computer vision tasks. Our objective is to present a more practical and simplified linear algorithm for these special configuration cameras, as traditional linear algorithms usually require too-strong constraints either on three-dimensional scenes or on the camera's motion. We developed the proposed algorithm from a new constraint by exploiting the orthogonality of two planes. The algorithm has much weaker constraints on three-dimensional scenes because two perpendicular planes are commonly found in daily life. We tested the algorithm with synthetic data and real image data. Experimental results show that it is both accurate and practical.

Algorithms↗

PubMed1993

Photon beam compensation design: dose optimization in 3D volume for parallel opposed beams.

Most existing methods for photon beam compensation design is based on the dose optimization in a 2D plane through the treatment volume for each individual beam. These approaches do not, however, optimize the dose uniformity in the dimension along the beam path (hence not in the 3D volume). In this work, the author presents a practical compensation design algorithm for 3D dose optimization. In contrast to existing methods, the present algorithm simultaneously calculates the desired cross-beam transmission factor map of the compensation device for each pair of parallel opposed beams. By using computed tomography scans, the patient's external shape and the internal inhomogeneous tissue density are also taken into account. The result is used to construct beam-attenuating compensators or to program a dynamic beam delivery scheme. The algorithm is presented in a form easily adaptable to different dose calculation systems. Compared to other methods, superior dose uniformity is achieved via the present approach.

Humans↗

PubMed2003

Design and assessment of a fast algorithm for identifying specific probes for human and mouse genes.

MOTIVATION: Mammalian genomes are highly complex. To identify the unique sequences of each gene in a mammalian gene database containing tens of thousands of DNA sequences is a computation intensive task. With the advent of parallel genetic analysis methods such as microarrays and the availability of more and more whole genome sequences of organisms, an algorithm allowing speedy identification of the unique gene probes for functional studies of individual genes will be a very useful tool. RESULTS: We have developed a fast algorithm as well as a software program based on the algorithm for identifying gene specific probes of complex organisms. The algorithm was applied to the assemblies of gene sequences and was highly efficient for large databases such as the TIGR human THC and mouse TC databases. The results were assessed with the BLAST sequence alignment software. Two probe data sets have been compiled to contain specific probes for around 100 000 putative human gene transcripts and 70 000 putative mouse gene transcripts. AVAILABILITY: The gene specific probes for the putative human and mouse genes referenced in the TIGR gene indices are available at: ftp://genestamp.ibms.sinica.edu.tw/pub/SpecificP/. The software program and the source codes are available upon request.

Algorithms↗

PubMed2002

An automatic block and spot indexing with k-nearest neighbors graph for microarray image analysis.

MOTIVATION: In this paper, we propose a fully automatic block and spot indexing algorithm for microarray image analysis. A microarray is a device which enables a parallel experiment of ten to hundreds of thousands of test genes in order to measure gene expression. Due to this huge size of experimental data, automated image analysis is gaining importance in microarray image processing systems. Currently, most of the automated microarray image processing systems require manual block indexing and, in some cases, spot indexing. If the microarray image is large and contains a lot of noise, it is very troublesome work. In this paper, we show it is possible to locate the addresses of blocks and spots by applying the Nearest Neighbors Graph Model. Also, we propose an analytic model for the feasibility of block addressing. Our analytic model is validated by a large body of experimental results. RESULTS: We demonstrate the features of automatic block detection, automatic spot addressing, and correction of the distortion and skewedness of each microarray image.

Algorithms↗

PubMed2006

Impact of active versus usual algorithmic titration of basal insulin and point-of-care versus laboratory measurement of HbA1c on glycemic control in patients with type 2 diabetes: the Glycemic Optimization with Algorithms and Labs at Point of Care (GOAL A1C) trial.

OBJECTIVE: The objective of this study was to assess the impact of active versus usual monitoring of algorithmic insulin titration and point-of-care (POC) versus laboratory HbA1c (A1C) measurement on glycemic control in primary care. RESEARCH DESIGN AND METHODS: The Glycemic Optimization with Algorithms and Labs at Point of Care (GOAL A1C) study was a 24-week, randomized, parallel-group, four-arm, open-label study of 7,893 adults with type 2 diabetes uncontrolled by oral antidiabetic agents and requiring insulin. Patients were randomly assigned by investigators from 2,164 sites in the U.S. to insulin glargine with either 1) usual (no unsolicited contact between visits) insulin titration using a simple algorithm with laboratory A1C testing, 2) usual titration with POC A1C testing, 3) active (weekly monitored) titration with laboratory A1C testing, or 4) active titration with POC A1C testing. Outcome measures included a change in A1C and fasting self-monitoring of blood glucose (SMBG) levels, percentage of patients achieving A1C <7.0%, and hypoglycemia frequency. RESULTS: Significant A1C and SMBG reductions were observed in all arms (P < 0.0001). Compared with usual insulin titration, active titration achieved greater A1C reduction (1.5 vs. 1.3%; P < 0.0001), SMBG reduction (88 vs. 79 mg/dl; P < 0.0001), and proportion of patients achieving A1C <7.0% (38 vs. 30%; P < 0.0001). Among patients receiving active titration, POC A1C testing was associated with an increase in the proportion achieving an A1C <7.0% (41% for POC vs. 36% for laboratory; P < 0.0001). Hypoglycemia rates were low (usual vs. active groups: 3.7 vs. 6.0 all confirmed episodes/patient-year [P < 0.001]; 0.09 vs. 0.14 severe episodes/patient-year [NS]). CONCLUSIONS: In a predominantly primary care setting, addition of insulin glargine using a simple algorithm achieved significant improvements in glycemic control in patients with type 2 diabetes in all four study arms. Active titration resulted in significant incremental improvements in glycemic control, and, among patients receiving active titration, POC A1C testing resulted in a greater portion achieving A1C <7.0%.

Administration, Oral↗

PubMed2006

Efficient algorithms and software for detection of full-length LTR retrotransposons.

LTR retrotransposons constitute one of the most abundant classes of repetitive elements in eukaryotic genomes. In this paper, we present a new algorithm for detection of full-length LTR retrotransposons in genomic sequences. The algorithm identifies regions in a genomic sequence that show structural characteristics of LTR retrotransposons. Three key components distinguish our algorithm from that of current software--(i) a novel method that preprocesses the entire genomic sequence in linear time and produces high quality pairs of LTR candidates in run-time that is constant per pair, (ii) a thorough alignment-based evaluation of candidate pairs to ensure high quality prediction, and (iii) a robust parameter set encompassing both structural constraints and quality controls providing users with a high degree of flexibility. We implemented our algorithm into a software program called LTR_par, which can be run on both serial and parallel computers. Validation of our software against the yeast genome indicates superior results in both quality and performance when compared to existing software. Additional validations are presented on rice BACs and chimpanzee genome.

Algorithms↗

PubMed2006

Genetic test bed for feature selection.

MOTIVATION: Given a large set of potential features, such as the set of all gene-expression values from a microarray, it is necessary to find a small subset with which to classify. The task of finding an optimal feature set of a given size is inherently combinatoric because to assure optimality all feature sets of a given size must be checked. Thus, numerous suboptimal feature-selection algorithms have been proposed. There are strong impediments to evaluate feature-selection algorithms using real data when data are limited, a common situation in genetic classification. The difficulty is compound. First, there are no class-conditional distributions from which to draw data points, only a single small labeled sample. Second, there are no test data with which to estimate the feature-set errors, and one must depend on a training-data-based error estimator. Finally, there is no optimal feature set with which to compare the feature sets found by the algorithms. RESULTS: This paper describes a genetic test bed for the evaluation of feature-selection algorithms. It begins with a large biological feature-label dataset that is used as an empirical distribution and, using massively parallel computation, finds the top feature sets of various sizes based on a given sample size and classification rule. The user can draw random samples from the data, apply a proposed algorithm, and evaluate the proficiency of the proposed algorithm via three different measures (code provided). A key feature of the test bed is that, once a dataset is input, a single command creates the entire test bed relative to the dataset. The particular dataset used for the first version of the test bed comes from a microarray-based classification study that analyzes a large number of microarrays, prepared with RNA from breast tumor samples from each of 295 patients. AVAILABILITY: The software and supplementary material are available at http://public.tgen.org/tgen-cb/support/testbed/ CONTACT: edward@ece.tamu.edu.

Algorithms↗

PubMed2002

Optimal network topologies for local search with congestion.

The problem of searchability in decentralized complex networks is of great importance in computer science, economy, and sociology. We present a formalism that is able to cope simultaneously with the problem of search and the congestion effects that arise when parallel searches are performed, and we obtain expressions for the average search cost both in the presence and the absence of congestion. This formalism is used to obtain optimal network structures for a system using a local search algorithm. It is found that only two classes of networks can be optimal: starlike configurations, when the number of parallel searches is small, and homogeneous-isotropic configurations, when it is large.

Journal Article↗

PubMed1995

Dynamic modelling of a helical peptide in solution using NMR data: multiple conformations and multi-spin effects.

Nuclear Overhauser effect (NOE) measurements on molecules in solution provide information about only the ensemble-averaged properties of these molecules. An algorithm is presented that uses a list of NOEs to produce an ensemble of molecules that on average agrees with these NOEs, taking into account the effect of surrounding spins on the buildup of each NOE ('spin diffusion'). A simplified molecular dynamics simulation on several copies of the molecule in parallel is restrained by forces that are derived directly from differences between calculated and measured NOEs. The algorithm is tested on experimental NOE data of a helical peptide derived from bovine pancreatic trypsin inhibitor.

Algorithms↗

PubMed1993

The use of magnetic resonance imaging data and the inclusion of anisotropic regions in electrical impedance tomography.

Electrical Impedance Tomography (EIT) involves determining the electrical conductivity inside a biological body, given electrical impedance measurements on the surface of the body. This paper will discuss the use of Magnetic Resonance Imaging (MRI) data and the inclusion of anisotropic regions in EIT algorithms to reconstruct a more accurate conductivity profile for a canine torso. MRI data is used to determine the boundaries between regions of different conductivities with greater precision than is presently available using EIT alone. The inclusion of anisotropic regions allows better modeling of the muscle regions (e.g. skeletal muscle) which exhibit a greater conductivity in the direction parallel to the muscle fiber.

Algorithms↗

PubMed1993

A real time system for quantifying and displaying two-dimensional velocities using ultrasound.

This paper describes a system that has been developed for measuring two-dimensional velocities in real time using ultrasound. The instrument tracks interframe speckle pattern motion using a Sum-Absolute-Difference (SAD) algorithm in order to produce a vector map of 2D velocities. The system's parallel architecture allows calculation of approximately 20,000 vectors per second using the current tracking geometry. A programmable graphics processor encodes individual velocity vectors with color and displays them superimposed on the B-mode image in real time. In vitro tests indicate that the system can track velocities well over the Doppler aliasing limit in any direction in the scan plane with greater than 94% accuracy. A color encoded image obtained from a flow phantom highlights the system's ability to display lateral motion with uniform coloration, in contrast to the two-color display of current ultrasonic Doppler instruments.

Algorithms↗