Search PubMed⌕ Search

SEARCH · Search PubMed

Results for “Computing Methodologies”

Search indexed PubMed citations on genomics, clinical trials, systematic reviews and public health. Explore titles, authors and supplied subject terms, then open the PubMed record.

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

At least 883 records · Page 49Linked to original sources

Molecular and epidemiological characterization of vaginal Saccharomyces cerevisiae isolates.

Although vaginitis caused by Saccharomyces cerevisiae is extremely rare, in recent years we have experienced an increasing frequency of S. cerevisiae isolation from the vaginas of fertile-age women. In order to investigate the epidemiology of these vaginal infections, a total of 40 isolates of S. cerevisiae derived from symptomatic and asymptomatic women were characterized by two DNA typing approaches, named ribosomal DNA (rDNA) hybridization and Ty917 hybridization, based on the Southern blotting technique. After transfer, the polymorphic DNA restriction fragments were hybridized with the entire repeat of S. cerevisiae rDNA for one method and with the entire sequence of the Ty917 retrotransposon for the other. After elaboration with computer-assisted analysis, the results of each method showed that Ty917 hybridization is endowed with a discriminatory power higher than that of rDNA hybridization. With the Ty917 hybridization method, all of the S. cerevisiae isolates tested appeared very heterogeneous, with the exception of those collected from individual patients with recurrent vaginitis. This allowed us to exclude a possible common source of infection while the high relatedness among S. cerevisiae sequential isolates from recurrent-vaginitis patients could suggest a pattern of relapse rather than frequent reinfection.

Adult↗

Location of repetitive regions in sequences by optimizing a compression method.

Suppose that a biologist wishes to study some local property P of genetic sequences. If he can design (with a computer scientist) an algorithm C which efficiently compresses parts of the sequence which satisfy P, then our algorithm TurboOptLift locates very quickly where property P occurs by chance on a sequence, and where it occurs as a result of a significant process. Under some conditions, the time complexity of TurboOptLift is O(n log n). We illustrate its use on the practical problem of locating approximate tandem repeats in DNA sequences.

Algorithms↗

Binary QSAR: a new method for the determination of quantitative structure activity relationships.

A new method (particularly suited to the analysis of High Throughput Screening data) is presented for the determination of quantitative structure activity relationships. The method, termed "Binary QSAR," accepts binary activity measurements (e.g., pass/fail or active/inactive) and molecular descriptor vectors as input. A Bayesian inference technique is used to predict whether or not a new compound will be active or inactive. Experiments were conducted on a data set of 1947 molecules. The results show that the method exhibits high accuracy and is robust to measurement errors.

Bayes Theorem↗

A function-based framework for understanding biological systems.

Systems biology research is currently dominated by integrative, multidisciplinary approaches. Although important, these strategies lack an overarching systems perspective such as those used in engineering. We describe here the Axiomatic Design approach to system analysis and illustrate its utility in the study of biological systems. Axiomatic Design relates functions at all levels to the behavior of biological molecules and uses a Design Matrix to understand these relationships. Such an analysis reveals that robustness in many biological systems is achieved through the maintenance of functional independence of numerous subsystems. When the interlinking (coupling) of systems is required, biological systems impose a functional period in order to maximize successful operation of the system. Ultimately, the application of Axiomatic Design methods to the study of biological systems will aid in handling cross-scale models, identifying control points, and predicting system-wide effects of pharmacological agents.

Algorithms↗

Embedded landscapes.

In this paper we introduce embedded landscapes as an extension of NK landscapes and MAXSAT problems. This extension is valid for problems where the representation can be expressed as a simple sum of subfunctions over subsets of the representation domain. This encompasses many additive constraint problems and problems expressed as the interaction of subcomponents, where the critical features of the subcomponents are represented by subsets of bits in the domain. We show that embedded landscapes of fixed maximum epistasis K are exponentially sparse in epistatic space with respect to all possible functions. We show we can compute many important statistical features of these functions in polynomial time including all the epistatic interactions and the statistical moments of hyperplanes about the function mean and hyperplane mean. We also show that embedded landscapes of even small fixed K can be NP-complete. We can conclude that knowing the epistasis and many of the hyperplane statistics is not enough to solve the exponentially difficult part of these general problems and that the difficulty of the problem lies not in the epistasis itself but in the interaction of the epistatic parts.

Algorithms↗

A computationally efficient evolutionary algorithm for real-parameter optimization.

Due to increasing interest in solving real-world optimization problems using evolutionary algorithms (EAs), researchers have recently developed a number of real-parameter genetic algorithms (GAs). In these studies, the main research effort is spent on developing an efficient recombination operator. Such recombination operators use probability distributions around the parent solutions to create an offspring. Some operators emphasize solutions at the center of mass of parents and some around the parents. In this paper, we propose a generic parent-centric recombination operator (PCX) and a steady-state, elite-preserving, scalable, and computationally fast population-alteration model (we call the G3 model). The performance of the G3 model with the PCX operator is investigated on three commonly used test problems and is compared with a number of evolutionary and classical optimization algorithms including other real-parameter GAs with the unimodal normal distribution crossover (UNDX) and the simplex crossover (SPX) operators, the correlated self-adaptive evolution strategy, the covariance matrix adaptation evolution strategy (CMA-ES), the differential evolution technique, and the quasi-Newton method. The proposed approach is found to consistently and reliably perform better than all other methods used in the study. A scale-up study with problem sizes up to 500 variables shows a polynomial computational complexity of the proposed approach. This extensive study clearly demonstrates the power of the proposed technique in tackling real-parameter optimization problems.

Algorithms↗

Calculating the expected loss of diversity of selection schemes.

This paper concerns a measure of selective pressure, called "loss of diversity," that denotes the proportion of unselected individuals during the selection phase. We probabilistically calculate the expected value and variance of loss of diversity in tournament selection, truncation selection, linear ranking selection, and exponential ranking selection. From numerical results, we observe that in tournament selection, many more individuals are expected to be lost than with Blickle and Thiele's static estimate. We also observe that tournament and exponential ranking schemes potentially bring about nearly equivalent selection behaviors but have different types of control parameters.

Algorithms↗

Genetic Parallel Programming: design and implementation.

This paper presents a novel Genetic Parallel Programming (GPP) paradigm for evolving parallel programs running on a Multi-Arithmetic-Logic-Unit (Multi-ALU) Processor (MAP). The MAP is a Multiple Instruction-streams, Multiple Data-streams (MIMD), general-purpose register machine that can be implemented on modern Very Large-Scale Integrated Circuits (VLSIs) in order to evaluate genetic programs at high speed. For human programmers, writing parallel programs is more difficult than writing sequential programs. However, experimental results show that GPP evolves parallel programs with less computational effort than that of their sequential counterparts. It creates a new approach to evolving a feasible problem solution in parallel program form and then serializes it into a sequential program if required. The effectiveness and efficiency of GPP are investigated using a suite of 14 well-studied benchmark problems. Experimental results show that GPP speeds up evolution substantially.

Algorithms↗

The application of computerized content analysis of natural language in psychotherapy research now and in the future.

For many years the author and his colleagues have been involved in studying the roots and processes of the conveyance of semantic messages via spoken language and verbal texts. After establishing that reliable and valid measurements of highly relevant neuropsychiatric categories, such as anxiety, depression, and cognitive impairment, can be made by identifying and counting the occurrence per grammatical clause of language content and form categories typifying specific content-analysis scales, the research focus has turned towards computerizing this process of content analysis. This report summarizes the achievements and applications of the current empirical status of this method of computerized content analysis of natural language to psychotherapy research, and it speculates on possible future applications in the millennium.

Computing Methodologies↗

Mobile medical computing driven by the complexity of neurologic diagnosis.

Medical computing has been split between palm-sized computers optimized for mobility and desktop computers optimized for capability. This split was due to technology too immature to deliver both mobility and capability in the same computer and the lack of medical software that demanded both mobility and capability. Advances in hardware and software are ushering in an era in which fully capable computers will be available ubiquitously. As a result, medical practice, education and publishing will change. Medical practice will be improved by the use of software that not only assists with diagnosis but can do so at the bedside, where the doctor can act immediately upon suggestions such as useful findings to check. Medical education will shift away from a focus on details of unusual diseases and toward a focus on skills of physical examination and using computerized tools. Medical publishing, in contrast, will shift toward greater detail: it will be increasingly important to quantitate the frequency of findings in diseases and their time course since such information can have a major impact clinically when added to decision support software.

Child↗

Multiple sequence alignment accuracy and evolutionary distance estimation.

BACKGROUND: Sequence alignment is a common tool in bioinformatics and comparative genomics. It is generally assumed that multiple sequence alignment yields better results than pair wise sequence alignment, but this assumption has rarely been tested, and never with the control provided by simulation analysis. This study used sequence simulation to examine the gain in accuracy of adding a third sequence to a pair wise alignment, particularly concentrating on how the phylogenetic position of the additional sequence relative to the first pair changes the accuracy of the initial pair's alignment as well as their estimated evolutionary distance. RESULTS: The maximal gain in alignment accuracy was found not when the third sequence is directly intermediate between the initial two sequences, but rather when it perfectly subdivides the branch leading from the root of the tree to one of the original sequences (making it half as close to one sequence as the other). Evolutionary distance estimation in the multiple alignment framework, however, is largely unrelated to alignment accuracy and rather is dependent on the position of the third sequence; the closer the branch leading to the third sequence is to the root of the tree, the larger the estimated distance between the first two sequences. CONCLUSION: The bias in distance estimation appears to be a direct result of the standard greedy progressive algorithm used by many multiple alignment methods. These results have implications for choosing new taxa and genomes to sequence when resources are limited.

Algorithms↗

Multiscale Hy3S: hybrid stochastic simulation for supercomputers.

BACKGROUND: Stochastic simulation has become a useful tool to both study natural biological systems and design new synthetic ones. By capturing the intrinsic molecular fluctuations of "small" systems, these simulations produce a more accurate picture of single cell dynamics, including interesting phenomena missed by deterministic methods, such as noise-induced oscillations and transitions between stable states. However, the computational cost of the original stochastic simulation algorithm can be high, motivating the use of hybrid stochastic methods. Hybrid stochastic methods partition the system into multiple subsets and describe each subset as a different representation, such as a jump Markov, Poisson, continuous Markov, or deterministic process. By applying valid approximations and self-consistently merging disparate descriptions, a method can be considerably faster, while retaining accuracy. In this paper, we describe Hy3S, a collection of multiscale simulation programs. RESULTS: Building on our previous work on developing novel hybrid stochastic algorithms, we have created the Hy3S software package to enable scientists and engineers to both study and design extremely large well-mixed biological systems with many thousands of reactions and chemical species. We have added adaptive stochastic numerical integrators to permit the robust simulation of dynamically stiff biological systems. In addition, Hy3S has many useful features, including embarrassingly parallelized simulations with MPI; special discrete events, such as transcriptional and translation elongation and cell division; mid-simulation perturbations in both the number of molecules of species and reaction kinetic parameters; combinatorial variation of both initial conditions and kinetic parameters to enable sensitivity analysis; use of NetCDF optimized binary format to quickly read and write large datasets; and a simple graphical user interface, written in Matlab, to help users create biological systems and analyze data. We demonstrate the accuracy and efficiency of Hy3S with examples, including a large-scale system benchmark and a complex bistable biochemical network with positive feedback. The software itself is open-sourced under the GPL license and is modular, allowing users to modify it for their own purposes. CONCLUSION: Hy3S is a powerful suite of simulation programs for simulating the stochastic dynamics of networks of biochemical reactions. Its first public version enables computational biologists to more efficiently investigate the dynamics of realistic biological systems.

Cell Physiological Phenomena↗

A fast parallel algorithm for finding the longest common sequence of multiple biosequences.

BACKGROUND: Searching for the longest common sequence (LCS) of multiple biosequences is one of the most fundamental tasks in bioinformatics. In this paper, we present a parallel algorithm named FAST_LCS to speedup the computation for finding LCS. RESULTS: A fast parallel algorithm for LCS is presented. The algorithm first constructs a novel successor table to obtain all the identical pairs and their levels. It then obtains the LCS by tracing back from the identical character pairs at the last level. Effective pruning techniques are developed to significantly reduce the computational complexity. Experimental results on gene sequences in the tigr database show that our algorithm is optimal and much more efficient than other leading LCS algorithms. CONCLUSION: We have developed one of the fastest parallel LCS algorithms on an MPP parallel computing model. For two sequences X and Y with lengths n and m, respectively, the memory required is max{4*(n+1)+4*(m+1), L}, where L is the number of identical character pairs. The time complexity is O(L) for sequential execution, and O(|LCS(X, Y)|) for parallel execution, where |LCS(X, Y)| is the length of the LCS of X and Y. For n sequences X1, X2, ..., Xn, the time complexity is O(L) for sequential execution, and O(|LCS(X1, X2, ..., Xn)|) for parallel execution. Experimental results support our analysis by showing significant improvement of the proposed method over other leading LCS algorithms.

Algorithms↗

Fine structure of the low-frequency spectra of heart rate and blood pressure.

BACKGROUND: The aim of this study was to explore the principal frequency components of the heart rate and blood pressure variability in the low frequency (LF) and very low frequency (VLF) band. The spectral composition of the R-R interval (RRI) and systolic arterial blood pressure (SAP) in the frequency range below 0.15 Hz were carefully analyzed using three different spectral methods: Fast Fourier transform (FFT), Wigner-Ville distribution (WVD), and autoregression (AR). All spectral methods were used to create time-frequency plots to uncover the principal spectral components that are least dependent on time. The accurate frequencies of these components were calculated from the pole decomposition of the AR spectral density after determining the optimal model order--the most crucial factor when using this method--with the help of FFT and WVD methods. RESULTS: Spectral analysis of the RRI and SAP of 12 healthy subjects revealed that there are always at least three spectral components below 0.15 Hz. The three principal frequency components are 0.026 +/- 0.003 (mean +/- SD) Hz, 0.076 +/- 0.012 Hz, and 0.117 +/- 0.016 Hz. These principal components vary only slightly over time. FFT-based coherence and phase-function analysis suggests that the second and third components are related to the baroreflex control of blood pressure, since the phase difference between SAP and RRI was negative and almost constant, whereas the origin of the first component is different since no clear SAP-RRI phase relationship was found. CONCLUSION: The above data indicate that spontaneous fluctuations in heart rate and blood pressure within the standard low-frequency range of 0.04-0.15 Hz typically occur at two frequency components rather than only at one as widely believed, and these components are not harmonically related. This new observation in humans can help explain divergent results in the literature concerning spontaneous low-frequency oscillations. It also raises methodological and computational questions regarding the usability and validity of the low-frequency spectral band when estimating sympathetic activity and baroreflex gain.

Adult↗

Contribution of non-extensor muscles of the leg to maximal-effort countermovement jumping.

BACKGROUND: The purpose of this study was to determine the effects of non-extensor muscles of the leg (i.e., muscles whose primary function is not leg extension) on the kinematics and kinetics of human maximal-effort countermovement jumping. Although it is difficult to address this type of question through experimental procedures, the methodology of computer simulation can be a powerful tool. METHODS: A skeletal model that has nine rigid body segments and twenty degrees of freedom was developed. Two sets of muscle models were attached to this skeletal model: all (most of) major muscles in the leg ("All Muscles" model) and major extensor muscles in the leg (i.e., muscles whose primary function is leg extension; "Extensors Only" model). Neural activation input signal was represented by a series of step functions with a step duration of 0.05 s. Simulations were started from an identical upright standing posture. The optimal pattern of the activation input signal was searched through extensive random-search numerical optimization with a goal of maximizing the height reached by the mass centre of the body after jumping up. RESULTS: The simulated kinematics was almost two-dimensional, suggesting the validity of two-dimensional analyses when evaluating net mechanical outputs around the joints using inverse dynamics. A greater jumping height was obtained for the "All Muscles" model (0.386 m) than for the "Extensors Only" model (0.301 m). For the "All Muscles" model, flexor muscles developed force in the beginning of the countermovement. For the "All Muscles" model, the sum of the work outputs from non-extensor muscles was 47.0 J, which was 13% of the total amount (359.9 J). The quantitative distribution of the work outputs from individual muscles was markedly different between these two models. CONCLUSION: It was suggested that the contribution of non-extensor muscles in maximal-effort countermovement jumping is substantial. The use of a computer simulation model that includes non-extensor muscles seems to be more desirable for the assessment of muscular outputs during jumping.

Computer Simulation↗

A high productivity/low maintenance approach to high-performance computation for biomedicine: four case studies.

The rapid advances in high-throughput biotechnologies such as DNA microarrays and mass spectrometry have generated vast amounts of data ranging from gene expression to proteomics data. The large size and complexity involved in analyzing such data demand a significant amount of computing power. High-performance computation (HPC) is an attractive and increasingly affordable approach to help meet this challenge. There is a spectrum of techniques that can be used to achieve computational speedup with varying degrees of impact in terms of how drastic a change is required to allow the software to run on an HPC platform. This paper describes a high- productivity/low-maintenance (HP/LM) approach to HPC that is based on establishing a collaborative relationship between the bioinformaticist and HPC expert that respects the former's codes and minimizes the latter's efforts. The goal of this approach is to make it easy for bioinformatics researchers to continue to make iterative refinements to their programs, while still being able to take advantage of HPC. The paper describes our experience applying these HP/LM techniques in four bioinformatics case studies: (1) genome-wide sequence comparison using Blast, (2) identification of biomarkers based on statistical analysis of large mass spectrometry data sets, (3) complex genetic analysis involving ordinal phenotypes, (4) large-scale assessment of the effect of possible errors in analyzing microarray data. The case studies illustrate how the HP/LM approach can be applied to a range of representative bioinformatics applications and how the approach can lead to significant speedup of computationally intensive bioinformatics applications, while making only modest modifications to the programs themselves.

Amino Acid Sequence↗

Methodology and clinical experience with computed tomography and a computer-resident stereotactic atlas.

We have developed a computer-resident stereotactic atlas of the human brain that quantitatively defines subcortical structures within anatomical landmarks detected on obliquely reconstructed computed tomography (CT) slices. Horizontal stereotactic atlas sections can be stretched and contracted by polar transformation and labeled by a computer to fit within these CT scan-defined landmarks. The stereotactic coordinates of any substructure on the atlas-labeled CT slice may then be calculated by the computer and expressed in mechanical adjustments on a stereotactic surgical frame located in the operating room. We demonstrate the use of this method in the stereotactic treatment of movement disorders as an augmentation to conventional ventriculography and microelectrode recording.

Aged↗

Predicting the metabolic energy costs of bipedalism using evolutionary robotics.

To understand the evolution of bipedalism among the hominoids in an ecological context we need to be able to estimate the energetic cost of locomotion in fossil forms. Ideally such an estimate would be based entirely on morphology since, except for the rare instances where footprints are preserved, this is the only primary source of evidence available. In this paper we use evolutionary robotics techniques (genetic algorithms, pattern generators and mechanical modeling) to produce a biomimetic simulation of bipedalism based on human body dimensions. The mechanical simulation is a seven-segment, two-dimensional model with motive force provided by tension generators representing the major muscle groups acting around the lower-limb joints. Metabolic energy costs are calculated from the muscle model, and bipedal gait is generated using a finite-state pattern generator whose parameters are produced using a genetic algorithm with locomotor economy (maximum distance for a fixed energy cost) as the fitness criterion. The model is validated by comparing the values it generates with those for modern humans. The result (maximum efficiency of 200 J m(-1)) is within 15% of the experimentally derived value, which is very encouraging and suggests that this is a useful analytic technique for investigating the locomotor behaviour of fossil forms. Initial work suggests that in the future this technique could be used to estimate other locomotor parameters such as top speed. In addition, the animations produced by this technique are qualitatively very convincing, which suggests that this may also be a useful technique for visualizing bipedal locomotion.

Biomechanical Phenomena↗