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At least 721 records · Page 40Linked to original sources
PubMed2006

A method for computing the overall statistical significance of a treatment effect among a group of genes.

BACKGROUND: In studies that use DNA arrays to assess changes in gene expression, our goal is to evaluate the statistical significance of treatments on sets of genes. Genes can be grouped by a molecular function, a biological process, or a cellular component, e.g., gene ontology (GO) terms. The meaning of an affected GO group is often clearer than interpretations arising from a list of the statistically significant genes. RESULTS: Computer simulations demonstrated that correlations among genes invalidate many statistical methods that are commonly used to assign significance to GO terms. Ignoring these correlations overstates the statistical significance. Meta-analysis methods for combining p-values were modified to adjust for correlation. One of these methods is elaborated in the context of a comparison between two treatments. The form of the correlation adjustment depends upon the alternative hypothesis. CONCLUSION: Reliable corrections for the effect of correlations among genes on the significance level of a GO term can be constructed for an alternative hypothesis where all transcripts in the GO term increase (decrease) in response to treatment. For general alternatives, which allow some transcripts to increase and others to decrease, the bias of naïve significance calculations can be greatly decreased although not eliminated.

Biometry↗
PubMed1993

The use of a microcomputer to automate measurement of action potential duration for both transmembrane and monophasic action potentials.

Measurement of action potential duration is made more valuable if it can be made simultaneously with other variables, to which it may be related. We have developed a microcomputer-based system which allows measurement of action potential duration, both for transmembrane action potentials and for monophasic action potentials. The system allows simultaneous recording and analysis of action potentials and intraventricular pressures. Both end-diastolic and maximum systolic pressures have been analysed. Action potential duration was assessed at four different levels of the repolarization curve. We have analysed the consistency of measurements made by the computer, and compared them to measurements made manually, using results from six dog experiments. For action potential duration, there was no systematic difference between the manual and the computer methods, but the computer was significantly more consistent. In the case of the pressure measurements, the two methods were approximately the same in their consistency, and again there was no systematic difference. We have demonstrated that potential errors in determination of the average diastolic potential did not significantly affect the results obtained by our method. The variances of action potential duration measurements made at different levels of repolarization were equal. We demonstrated that there was no effect of amplitude on the action potential duration of potentials recorded under steady-state conditions.

Action Potentials↗
PubMed2006

A framework for describing topological frustration in models of protein folding.

In a natively folded protein of moderate or larger size, the protein backbone may weave through itself in complex ways, raising questions about what sequence of events might have to occur in order for the protein to reach its native configuration from the unfolded state. A mathematical framework is presented here for describing the notion of a topological folding barrier, which occurs when a protein chain must pass through a hole or opening, formed by other regions of the protein structure. Different folding pathways encounter different numbers of such barriers and therefore different degrees of frustration. A dynamic programming algorithm finds the optimal theoretical folding path and minimal degree of frustration for a protein based on its natively folded configuration. Calculations over a database of protein structures provide insights into questions such as whether the path of minimal frustration might tend to favor folding from one or from many sites of folding nucleation, or whether proteins favor folding around the N terminus, thereby providing support for the hypothesis that proteins fold co-translationally. The computational methods are applied to a multi-disulfide bonded protein, with computational findings that are consistent with the experimentally observed folding pathway. Attention is drawn to certain complex protein folds for which the computational method suggests there may be a preferred site of nucleation or where folding is likely to proceed through a relatively well-defined pathway or intermediate. The computational analyses lead to testable models for protein folding.

Algorithms↗
PubMed1996

Modeling dose distributions from portal dose images using the convolution/superposition method.

Post-treatment dose verification refers to the process of reconstructing delivered dose distributions internal to a patient from information obtained during the treatment. The exit dose is commonly used to describe the dose beyond the exit surface of the patient from a megavoltage photon beam. Portal imaging provides a method of determining the dose in a plane distal to a patient from a megavoltage therapeutic beam. This exit dose enables reconstruction of the dose distribution from external beam radiation throughout the patient utilizing the convolution/superposition method and an extended phantom. An iterative convolution/superposition algorithm has been created to reconstruct dose distributions in patients from exit dose measurements during a radiotherapy treatment. The method is based on an extended phantom that includes the patient CT representation and an electronic portal imaging device (EPID). The convolution/superposition method computes the dose throughout the extended phantom, which allows the portal dose image to be predicted in the EPID. The process is then reversed to take the portal dose measurement and infer what the dose distribution must have been to produce the measured portal dose. The dose distribution is modeled without knowledge of the incident intensity distribution, and includes the effects of scatter in the computation. The iterative method begins by assuming that the primary energy fluence (PEF) at the portal image plane is equal to the portal dose image, the PEF is then back-projected through the extended phantom and convolved with the dose deposition kernel to determine a new prediction of the portal dose image. The image of the ratio of the computed PEF to the computed portal dose is then multiplied by the measured portal dose image to produce a better representation of the PEF. Successive iterations of this process then converge to the exiting PEF image that would produce the measured portal dose image. Once convergence is established, the dose distribution is determined by back-projecting the PEF and convolving with the dose deposition kernel. The method is accurate, provided the patient representation during treatment is known. The method was used on three phantoms with a photon energy of 6 MV to verify convergence and accuracy of the algorithm. The reconstructed dose volumes agree to within 3% of the forward computation dose volumes. Furthermore, this technique assumes no prior knowledge of the incident fluence and therefore may better represent the dose actually delivered.

Algorithms↗
PubMed1997

Analysis and convergence of the iterative convolution/superposition dose reconstruction technique for multiple treatment beams and tomotherapy.

An iterative convolution/superposition (C/S) algorithm has been created to reconstruct dose distributions in patients from exit dose measurements during a radiotherapy treatment. The method is based on an extended phantom which includes the patient CT representation and an electronic portal imaging device (EPID). The patient CT is assumed to be a true and rigid representation of the patient at the time of treatment. The C/S method computes the dose throughout the extended phantom which allows the exit dose to be predicted in the EPID. The process is then reversed to take the exit dose measurement and infer what the dose distribution must have been to produce the measured exit dose. The dose distribution is modeled without knowledge of the incident intensity distribution, and includes the effects of scatter in the computation. The iterative method begins by assuming that the exit primary energy fluence (PEF) is equal to the exit dose, the PEF is then backprojected through the extended phantom and superposed with the dose deposition kernel to determine a new prediction of the exit dose. The ratio of the computed PEF to exit dose is then multiplied by the measured exit dose image to produce a better representation of the exit PEF. Successive iterations then converge to the exit PEF image that would produce the measured exit dose image. Once convergence is established, the dose distribution is determined by backprojecting the exit PEF followed by superposition with the dose deposition kernel. The method is used to reconstruct the dose from a stimulated dynamic wedge and verified with film. Convergence and termination of the algorithm is then investigated with no noise and in the presence of noise. The method is then expanded to handle multiple treatment beams by separating the representation of the EPID from the patient or phantom representation in the computation process. Investigation of the effects of noise during the process of iterative dose reconstruction is necessary to understand the capabilities of the algorithm using exit dose images that may contain significant amounts of noise. The capability of the algorithm is evaluated for multiple field treatments to a cube phantom and a prostate patient CT representation in the presence of noise. The method is then used to simulate the dose reconstruction process for tomotherapy using 72 intensity-modulated fan beams. Dose reconstruction is shown to be capable of verifying the dose distributions in patients including multiple beams and dynamic collimation, provided the patient CT is known at the time of treatment.

Algorithms↗
PubMed2005

Recent developments in structural proteomics for protein structure determination.

The major challenges in structural proteomics include identifying all the proteins on the genome-wide scale, determining their structure-function relationships, and outlining the precise three-dimensional structures of the proteins. Protein structures are typically determined by experimental approaches such as X-ray crystallography or nuclear magnetic resonance (NMR) spectroscopy. However, the knowledge of three-dimensional space by these techniques is still limited. Thus, computational methods such as comparative and de novo approaches and molecular dynamic simulations are intensively used as alternative tools to predict the three-dimensional structures and dynamic behavior of proteins. This review summarizes recent developments in structural proteomics for protein structure determination; including instrumental methods such as X-ray crystallography and NMR spectroscopy, and computational methods such as comparative and de novo structure prediction and molecular dynamics simulations.

Aspergillus↗
PubMed1990

The Bin Area Method: a computationally efficient technique for analysis of ventricular and atrial intracardiac electrograms.

Recent studies have reported a significant false positive rate in delivery of therapy by implantable antitachycardia devices utilizing detection algorithms based on sustained high rate. More selective decision schemes for the recognition of life-threatening arrhythmias have been recently proposed that use analysis of the intrinsic electrogram rather than rate alone. Morphological discrimination of abnormal electrograms using correlation waveform analysis (CWA) has been proposed as an effective method of intracardiac electrogram analysis, but its computational demands limit its use in implantable devices. A new method for intracardiac electrogram analysis, the bin area method (BAM), was created to detect abnormal cardiac conduction with computational requirements of one-half to one-tenth those of CWA. Like CWA, BAM is a template matching method that is sensitive to conduction changes revealed in the electrogram morphology and is independent of amplitude and baseline fluctuations. Performance of BAM and CWA were compared using bipolar right ventricular and right atrial electrode recordings from 47 patients undergoing clinical cardiac electrophysiology studies. Nineteen patients had 31 distinct monomorphic ventricular tachycardias (VTs) induced (group I), thirteen patients had paroxysmal bundle branch block of supraventricular origin (BBB) induced (group II), and 19 patients had retrograde atrial activation during right ventricular overdrive pacing (group III). (One patient was common to all three groups, and two patients were common to groups II and III.) Using the ventricular electrogram, both BAM and CWA distinguished VT from sinus rhythm in 28/31 (90%) cases, and BBB from Normal Sinus Rhythm (NSR) in 13/13 (100%) patients. Using the atrial electrogram, both BAM and CWA distinguished anterograde from retrograde atrial activation in 19/19 (100%) patients. BAM achieves similar performance to CWA with significantly reduced computational demands, and may make real-time analysis of intracardiac electrograms feasible for implantable pacemakers and antitachycardia devices.

Algorithms↗
PubMed1998

Pedigree analysis package (PAP) vs. MORGAN: model selection and hypothesis testing on a large pedigree.

The MORGAN package of programs is compared to a commonly used package, PAP, with respect to model selection in segregation analysis of a quantitative trait. MORGAN uses Monte Carlo Markov chain (MCMC) methods to estimate the likelihood, whereas both versions of PAP used employ an approximation to the likelihood for the mixed model. Comparisons are done by using results obtained from simulated data. All simulations were done on the same 232-member pedigree using data generated under each of several variations of models, which included different combinations of environmental, polygenic, and major gene components. PAP, version 4.0, and MORGAN gave similar results with respect to model selection for the majority of situations, suggesting that MCMC methods provide a computationally tractable approach for analysis of more complex models that cannot be analyzed by more direct computational methods. PAP, version 3.0, gave somewhat more disparate results compared with either PAP version 4.0 or MORGAN. Both MORGAN and the two versions of PAP confirmed that the major gene component is much easier to detect in the presence of some dominance. All three packages frequently falsely accepted the polygenic model when there was high residual heritability.

Computer Simulation↗
PubMed2005

New and fast statistical-thermodynamic method for computation of protein-ligand binding entropy substantially improves docking accuracy.

We present a novel method to estimate the contributions of translational and rotational entropy to protein-ligand binding affinity. The method is based on estimates of the configurational integral through the sizes of clusters obtained from multiple docking positions. Cluster sizes are defined as the intervals of variation of center of ligand mass and Euler angles in the cluster. Then we suggest a method to consider the entropy of torsional motions. We validate the suggested methods on a set of 135 PDB protein-ligand complexes by comparing the averaged root-mean square deviations (RMSD) of the top-scored ligand docked positions, accounting and not accounting for entropy contributions, relative to the experimentally determined positions. We demonstrate that the method increases docking accuracy by 10-21% when used in conjunction with the AutoDock docking program, thus reducing the percent of incorrectly docked ligands by 1.4-fold to four-fold, so that in some cases the percent of ligands correctly docked to within an RMSD of 2 A is above 90%. We show that the suggested method to account for entropy of relative motions is identical to the method based on the Monte Carlo integration over intervals of variation of center of ligand mass and Euler angles in the cluster.

Algorithms↗
PubMed1988

A computer-based method for on-line acquisition and analysis of bronchial challenge test.

We developed a computer program for the optimization and management of data collection in order to compute the change of forced expiratory volume in the first second (delta FEV1), provocative doses and to plot the dose-response curve for bronchial challenge test. Doses of methacholine are entered via the keyboard and forced vital capacity (FVC) with the highest FEV1 value obtained in each step is selected. When the imposed threshold of response has been reached, doses of administered methacholine and corresponding spirometric parameters are displayed and printed. Dose-response relationships are analysed: the increase of delta FEV1 for each unit of metacholine is computed in the interval between the two doses where delta FEV1 reached one of the imposed values (i.e. 15% or 20% or 30%). Finally spirometric values, dose-response curve and provocative doses are shown in a print-out. Computer values of provocative doses are higher than those obtained manually. This difference may be ascribed to the incorrect manual linear extrapolation. In conclusion the computer program is able to reduce consistently the time spent to analyze data from bronchial challenge test and allows a more precise determination of provocative doses by avoiding also inter-intra individual errors.

Asthma↗
PubMed1969

Computer-assisted method for compiling a blood group register.

The compilation of the records of a serology department using a computer to produce alphabetically ordered files is described. This has proved to be an efficient and economical technique which may well be applied to other similar problems in a large clinical laboratory.

Blood Group Antigens↗
PubMed1986

Evaluation of the effect of variability in the volume of distribution of theophylline on the predictability of the iterative and the Chiou methods using computer simulations.

The effect of variations in the volume of distribution on the precision of the ability of two methods--the Chiou and the iterative--to predict the total body clearance (TBC) of theophylline was evaluated utilizing computer simulations. Pharmacokinetic data [volume of distributions (V), elimination constants (k)] measured in a group of 55 adult bronchitic patients were utilized to conduct the simulations. An average V of 0.45 L/kg was utilized to calculate TBC with the Chiou and the iterative methods. Separate simulations were conducted utilizing initial (C1) serum concentrations of 2 and 10 micrograms/ml. At the C1 = 2 micrograms/ml condition, the iterative method was statistically significantly more precise (mean squared prediction error, 379.5 vs. 508.5). There were no differences when the initial serum concentration was 10 micrograms/ml under the simulated conditions. At the lower initial condition (C1 = 2) the mean prediction error was 62.3 and 54.9% for the Chiou and the iterative methods, respectively, and it ranged from 0 to 477%. It is recommended that caution be utilized when theophylline doses are individualized using these methods.

Adult↗
PubMed1997

In vitro and in vivo transcription from a computer predicted promoter.

A fragment (172 bp) of B. subtilis phage phi29 DNA, which does not contain a functional promoter for phage transcription, has been shown to direct transcription in the promoter-probe plasmid pPV33. The promoter candidate found in this fragment by the computer method of acceptability is compared with cryptic promoters selected by this computer method. It is characterized in vitro by electron microscopic visualization of RNA polymerase binding and 'run off' transcription, and in vivo by high resolution S1 mapping.

Bacillus Phages↗