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At least 73 records · Page 4Linked to original sources
PubMed2001

Automatic discovery of sub-molecular sequence domains in multi-aligned sequences: a dynamic programming algorithm for multiple alignment segmentation.

Automatic identification of sub-structures in multi-aligned sequences is of great importance for effective and objective structural/functional domain annotation, phylogenetic treeing and other molecular analyses. We present a segmentation algorithm that optimally partitions a given multi-alignment into a set of potentially biologically significant blocks, or segments. This algorithm applies dynamic programming and progressive optimization to the statistical profile of a multi-alignment in order to optimally demarcate relatively homogenous sub-regions. Using this algorithm, a large multi-alignment of eukaryotic 16S rRNA was analyzed. Three types of sequence patterns were identified automatically and efficiently: shared conserved domain; shared variable motif; and rare signature sequence. Results were consistent with the patterns identified through independent phylogenetic and structural approaches. This algorithm facilitates the automation of sequence-based molecular structural and evolutionary analyses through statistical modeling and high performance computation.

Algorithms↗
PubMed1993

A real-time gesture recognizer based on dynamic programming.

Coded gestures are physical movements to which precise meanings have been attached. Their use with an electronic pointing device potentially increases the power of the pointer by allowing several distinct control functions to be incorporated. The formation of a coded gesture is invariably subject to distortions which make its automatic recognition difficult. After particular consideration of three techniques, a dynamic programming algorithm was developed and was used in the design of a real-time gesture recognizer that allows mouse-driven software to be operated purely by means of an electronic pointer. The decision was taken to implement the gesture recognizer using a widely available, obsolescent microcomputer in order to keep down costs. Despite the inevitable technical compromises in this approach, results of preliminary trials using 10 normal subjects show an average gesture recognition rate of 98.3% and a gesture confusion rate of only 0.4%.

Algorithms↗
PubMed1994

Protein structure comparisons using a combination of a genetic algorithm, dynamic programming and least-squares minimization.

We introduce a completely automatic and objective procedure for the comparison of protein structures. A genetic algorithm is used to search for a near optimal solution of the rigid-body superposition of two whole protein structures. The specification of an initial set of equivalences is not required. Topological equivalences in the final structural alignment are defined by a conventional dynamic programming routine, which is commonly used to compare protein sequences. A least-squares fitting algorithm is then used to optimize the fit between the final set of equivalences. We have applied our method to the comparison of ribonucleic acid structures, as well as protein structures. The structural alignments are generally consistent with those previously published. In fact, on most occasions our method defines at least the same number of topological equivalences as other procedures, but always with a lower r.m.s. distance between them.

Algorithms↗
PubMed1999

Two tests of a stochastic dynamic programming model of daily singing routines in birds.

Many hypotheses have been put forward to account for the dawn chorus in birds. Few of these, however, are able to account for variation in song output over the whole day, or for differences in daily singing routines between species, individuals, seasons and environmental conditions. One hypothesis that does offer a more general explanation is based on a stochastic dynamic programming (SDP) model of daily singing routines. This model relates the relative costs and benefits of feeding and singing at different times of day to the size of a bird's fat reserves and calculates the optimal daily routines of singing and foraging that will maximize the amount that the bird can sing while avoiding starvation. The use of SDP models in behavioural ecology has become well established, but they remain largely untested empirically. I tested two predictions of the SDP model of daily routines of singing, using free-living European robins Erithacus rubecula. The results supported both predictions: (1) food supplementation causing unpredictable short-term increases in foraging success increased subsequent song output; and (2) changes in ambient temperature were positively associated with changes in subsequent song output. Copyright 1999 The Association for the Study of Animal Behaviour.

Journal Article↗
PubMed2004

Optimal femoral head contour segmentation in CT images using dynamic programming.

We present a new contour segmentation method for femoral head detection in CT images. The principal idea underlying our approach is to represent the contour using active rays. Each ray has internal energy (continuity and smoothness constraints), as well as external energy (image-oriented edges and global a-priori knowledge). The causal nature of this representation allows a globally optimal, non-iterative solution to be found using dynamic programming. Moreover, even pathological bone structures can be automatically segmented. Several clinical situations on pelvis CT scan with hip degenerative change shows that this approach is more efficient than conventional methods. In this paper, we describe our method and discuss how it can be used to create graphical 3D models of the hip that are suitable for preoperative planning.

Algorithms↗
PubMed1994

When awaiting 'Bio' Champollion: dynamic programming regularization of the protein secondary structure predictions.

Predictions of protein secondary structure using current methods are often unrealistic, i.e. the predicted alpha-helices or beta-strands are too short. To improve the realism, various heuristic 'filtering' or 'smoothing' methods are used. They are more or less intuitive and are based on ad hoc corrections. We present a regularization method to obtain a realistic secondary structure from predicted propensities. It is based on the known dynamic programming algorithm and is quite objective. It can be used with any prediction method which yields propensities. The regularized predictions conserve well the overall prediction accuracy and improve the 'protein-likeness' of the prediction.

Algorithms↗
PubMed2002

GAZE: a generic framework for the integration of gene-prediction data by dynamic programming.

We describe a method (implemented in a program, GAZE) for assembling arbitrary evidence for individual gene components (features) into predictions of complete gene structures. Our system is generic in that both the features themselves, and the model of gene structure against which potential assemblies are validated and scored, are external to the system and supplied by the user. GAZE uses a dynamic programming algorithm to obtain the highest scoring gene structure according to the model and posterior probabilities that each input feature is part of a gene. A novel pruning strategy ensures that the algorithm has a run-time effectively linear in sequence length. To demonstrate the flexibility of our system in the incorporation of additional evidence into the gene prediction process, we show how it can be used to both represent nonstandard gene structures (in the form of trans-spliced genes in Caenorhabditis elegans), and make use of similarity information (in the form of Expressed Sequence Tag alignments), while requiring no change to the underlying software. GAZE is available at http://www.sanger.ac.uk/Software/analysis/GAZE.

Algorithms↗
PubMed1994

A theoretical study of the socioecology of ungulates. II. A dynamic programming study of the stochastic formulation.

We develop a stochastic version of a previously discussed model of optimal herd size selection in ungulates. We assume that a large herd size confers to the animals a high level of protection against predators, but reduces the amount of food which can be eaten by each individual; on the contrary animals belonging to small herds would have access to large amounts of food but would bear a high risk of being killed by predators. Employing a dynamic programming approach we analyze the optimal trade-off between starvation and predation risks under the hypothesis that the animals would try to maximize their expected reproductive fitness during the incoming breeding period. We compare the optimal strategy in environments described by different kinds of stochastic food distributions (including the deterministic limit) for different values of predation pressure and of overall food availability. We obtain general information about the effect of the level of randomness of food distribution on the mean individual fitness and on the number of reproducers (the animals which survive to the beginning of the reproductive season). Moreover we discuss how a certain number of behavioral and ecological processes--which have been often described in natural populations of ungulates and which are usually explained in terms of phenological variations of the ecological landscape--may be interpreted as caused by intrinsic variations of the animals' strategy.

Animal Nutritional Physiological Phenomena↗
PubMed2005

SW-ARRAY: a dynamic programming solution for the identification of copy-number changes in genomic DNA using array comparative genome hybridization data.

Comparative genome hybridization (CGH) to DNA microarrays (array CGH) is a technique capable of detecting deletions and duplications in genomes at high resolution. However, array CGH studies of the human genome noting false negative and false positive results using large insert clones as probes have raised important concerns regarding the suitability of this approach for clinical diagnostic applications. Here, we adapt the Smith-Waterman dynamic-programming algorithm to provide a sensitive and robust analytic approach (SW-ARRAY) for detecting copy-number changes in array CGH data. In a blind series of hybridizations to arrays consisting of the entire tiling path for the terminal 2 Mb of human chromosome 16p, the method identified all monosomies between 267 and 1567 kb with a high degree of statistical significance and accurately located the boundaries of deletions in the range 267-1052 kb. The approach is unique in offering both a nonparametric segmentation procedure and a nonparametric test of significance. It is scalable and well-suited to high resolution whole genome array CGH studies that use array probes derived from large insert clones as well as PCR products and oligonucleotides.

Algorithms↗
PubMed2001

A dynamic programming approach to de novo peptide sequencing via tandem mass spectrometry.

Tandem mass spectrometry fragments a large number of molecules of the same peptide sequence into charged molecules of prefix and suffix peptide subsequences and then measures mass/charge ratios of these ions. The de novo peptide sequencing problem is to reconstruct the peptide sequence from a given tandem mass spectral data of k ions. By implicitly transforming the spectral data into an NC-spectrum graph G (V, E) where /V/ = 2k + 2, we can solve this problem in O(/V//E/) time and O(/V/2) space using dynamic programming. For an ideal noise-free spectrum with only b- and y-ions, we improve the algorithm to O(/V/ + /E/) time and O(/V/) space. Our approach can be further used to discover a modified amino acid in O(/V//E/) time. The algorithms have been implemented and tested on experimental data.

Algorithms↗
PubMed1995

Identification of human gene structure using linear discriminant functions and dynamic programming.

Development of advanced technique to identify gene structure is one of the main challenges of the Human Genome Project. Discriminant analysis was applied to the construction of recognition functions for various components of gene structure. Linear discriminant functions for splice sites, 5'-coding, internal exon, and 3'-coding region recognition have been developed. A gene structure prediction system FGENE has been developed based on the exon recognition functions. We compute a graph of mutual compatibility of different exons and present a gene structure models as paths of this directed acyclic graph. For an optimal model selection we apply a variant of dynamic programming algorithm to search for the path in the graph with the maximal value of the corresponding discriminant functions. Prediction by FGENE for 185 complete human gene sequences has 81% exact exon recognition accuracy and 91% accuracy at the level of individual exon nucleotides with the correlation coefficient (C) equals 0.90. Testing FGENE on 35 genes not used in the development of discriminant functions shows 71% accuracy of exact exon prediction and 89% at the nucleotide level (C = 0.86). FGENE compares very favorably with the other programs currently used to predict protein-coding regions. Analysis of uncharacterized human sequences based on our methods for splice site (HSPL, RNASPL), internal exons (HEXON), all type of exons (FEXH) and human (FGENEH) and bacterial (CDSB) gene structure prediction and recognition of human and bacterial sequences (HBR) (to test a library for E. coli contamination) is available through the University of Houston, Weizmann Institute of Science network server and a WWW page of the Human Genome Center at Baylor College of Medicine.

Algorithms↗
PubMed1994

Constructing gene models from accurately predicted exons: an application of dynamic programming.

This paper presents a computationally efficient algorithm, the Gene Assembly Program III (GAP III), for constructing gene models from a set of accurately-predicted 'exons'. The input to the algorithm is a set of clusters of exon candidates, generated by a new version of the GRAIL coding region recognition system. The exon candidates of a cluster differ in their presumed edges and occasionally in their reading frames. Each exon candidate has a numerical score representing its 'probability' of being an actual exon. GAP III uses a dynamic programming algorithm to construct a gene model, complete or partial, by optimizing a predefined objective function. The optimal gene models constructed by GAP III correspond very well with the structures of genes which have been determined experimentally and reported in the Genome Sequence Database (GSDB). On a test set of 137 human and mouse DNA sequences consisting of 954 true exons, GAP III constructed 137 gene models using 892 exons, among which 859 (859/954 = 90%) are true exons and 33 (33/892 = 3%) are false positive. Among the 859 true positives, 635 (74%) match the actual exons exactly, and 838 (98%) have at least one edge correct. GAP III is computationally efficient. If we use E and C to represent the total number of exon candidates in all clusters and the number of clusters, respectively, the running time of GAP III is proportional to (E x C).

Algorithms↗
PubMed2001

A dynamic programming approach to the efficient design of clinical trials.

If the prospective evaluation of all feasible strategies of patient management is not possible or efficient then this poses a number of questions: (i) which clinical decision problems will be worth evaluating through prospective clinical research; (ii) if a clinical decision problem is worth evaluating which of the many competing alternatives should be considered "relevant" and be compared in the evaluation; (iii) what is the optimal (technically efficient) scale of this prospective research; (iv) what is an optimal allocation of trial entrants between the competing alternatives; and (v) what is the value of this proposed research? The purpose of this paper is to present a Bayesian decision theoretic approach to the value of information which can provide answers to each of these questions. An analysis of the value of sample information was combined with dynamic programming and applied to numerical examples of sequential decision problems. The analysis demonstrates that this approach can be used to establish: optimal sample size; optimal sample allocation; and the societal payoff to proposed research. This approach provides a consistent way to identify which of the competing alternatives can be regarded as "relevant" and should be included in any evaluative study design. Bayesian decision theory can provide a general methodological framework that can ensure consistency in decision making between service provision, research and development, and the design, conduct and interpretation clinical research.

Bayes Theorem↗
PubMed1998

Dynamic programming approach for newborn's incubator humidity control.

The anatomy, physiology, and biochemistry of the human skin have been studied for a long time. A special interest has been shown in the water permeability of the premature infant's skin, which is known to be an important factor in the maintenance of a controlled water and heat balance. The rate of evaporative heat exchange between the skin surface of a very premature infant and the surrounding incubator air may be so high that evaporative heat loss alone may exceed the infant's total metabolic heat production. However, it has been demonstrated in several investigations published in recent years that basal evaporative water loss can be consistently reduced by increasing the ambient humidity. Nevertheless, the passive humidification system (water reservoir) used in most incubators cannot achieve high and steady humidity levels. In this paper, we propose an active humidification system. The algorithm is based on a combination of optimal control theory and dynamic programming approach. The relative-humidity (R.H.) regulation is performed in range of 35-90% at 33 degrees C with small oscillations (+/- 0.5% R.H.) around the reference value (i.e., prescribed R.H.).

Algorithms↗
PubMed2004

Frequent word section extraction in a presentation speech by an effective dynamic programming algorithm.

Word frequency in a document has often been utilized in text searching and summarization. Similarly, identifying frequent words or phrases in a speech data set for searching and summarization would also be meaningful. However, obtaining word frequency in a speech data set is difficult, because frequent words are often special terms in the speech and cannot be recognized by a general speech recognizer. This paper proposes another approach that is effective for automatic extraction of such frequent word sections in a speech data set. The proposed method is applicable to any domain of monologue speech, because no language models or specific terms are required in advance. The extracted sections can be regarded as speech labels of some kind or a digest of the speech presentation. The frequent word sections are determined by detecting similar sections, which are sections of audio data that represent the same word or phrase. The similar sections are detected by an efficient algorithm, called Shift Continuous Dynamic Programming (Shift CDP), which realizes fast matching between arbitrary sections in the reference speech pattern and those in the input speech, and enables frame-synchronous extraction of similar sections. In experiments, the algorithm is applied to extract the repeated sections in oral presentation speeches recorded in academic conferences in Japan. The results show that Shift CDP successfully detects similar sections and identifies the frequent word sections in individual presentation speeches, without prior domain knowledge, such as language models and terms.

Algorithms↗
PubMed2006

Performance characterization of the dynamic programming obstacle detection algorithm.

A computer vision-based system using images from an airborne aircraft can increase flight safety by aiding the pilot to detect obstacles in the flight path so as to avoid mid-air collisions. Such a system fits naturally with the development of an external vision system proposed by NASA for use in high-speed civil transport aircraft with limited cockpit visibility. The detection techniques should provide high detection probability for obstacles that can vary from subpixels to a few pixels in size, while maintaining a low false alarm probability in the presence of noise and severe background clutter. Furthermore, the detection algorithms must be able to report such obstacles in a timely fashion, imposing severe constraints on their execution time. For this purpose, we have implemented a number of algorithms to detect airborne obstacles using image sequences obtained from a camera mounted on an aircraft. This paper describes the methodology used for characterizing the performance of the dynamic programming obstacle detection algorithm and its special cases. The experimental results were obtained using several types of image sequences, with simulated and real backgrounds. The approximate performance of the algorithm is also theoretically derived using principles of statistical analysis in terms of the signal-to-noise ration (SNR) required for the probabilities of false alarms and misdetections to be lower than prespecified values. The theoretical and experimental performance are compared in terms of the required SNR.

Algorithms↗
PubMed2000

Bimolecular reaction simulation using Weighted Ensemble Brownian dynamics and the University of Houston Brownian Dynamics program.

We discuss here the implementation of the Weighted Ensemble Brownian (WEB) dynamics algorithm of Huber and Kim in the University of Houston Brownian Dynamics (UHBD) suite of programs and its application to bimolecular association problems. WEB dynamics is a biased Brownian dynamics (BD) algorithm that is more efficient than the standard Northrup-Allison-McCammon (NAM) method in cases where reaction events are infrequent because of intervening free energy barriers. Test cases reported here include the Smoluchowski rate for association of spheres, the association of the enzyme copper-zinc superoxide dismutase with superoxide anion, and the binding of the superpotent sweetener N-(p-cyanophenyl)-N'-(diphenylmethyl)-guanidinium acetic acid to a monoclonal antibody fragment, NC6.8. Our results show that the WEB dynamics algorithm is a superior simulation method for enzyme-substrate reaction encounters with large free energy barriers.

Acetates↗
PubMed1996

Refining neural network predictions for helical transmembrane proteins by dynamic programming.

For transmembrane proteins experimental determination of three-dimensional structure is problematic. However, membrane proteins have important impact for molecular biology in general, and for drug design in particular. Thus, prediction method are needed. Here we introduce a method that started from the output of the profile-based neural network system PHDhtm (Rost, et al. 1995). Instead of choosing the neural network output unit with maximal value as prediction, we implemented a dynamic programming-like refinement procedure that aimed at producing the best model for all transmembrane helices compatible with the neural network output. The refined prediction was used successfully to predict transmembrane topology based on an empirical rule for the charge difference between extra- and intra-cytoplasmic regions (positive-inside rule). Preliminary results suggest that the refinement was clearly superior to the initial neural network system; and that the method predicted all transmembrane helices correctly for more proteins than a previously applied empirical filter. The resulting accuracy in predicting topology was better than 80%. Although a more thorough evaluation of the method on a larger data set will be required, the results compared favourably with alternative methods. The results reflected the strength of the refinement procedure which was the successful incorporation of global information: whereas the residue preferences output by the neural network were derived from stretches of 17 adjacent residues, the refinement procedure involved constraints on the level of the entire protein.

Algorithms↗