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PubMed2000

A probabilistic learning approach to whole-genome operon prediction.

We present a computational approach to predicting operons in the genomes of prokaryotic organisms. Our approach uses machine learning methods to induce predictive models for this task from a rich variety of data types including sequence data, gene expression data, and functional annotations associated with genes. We use multiple learned models that individually predict promoters, terminators and operons themselves. A key part of our approach is a dynamic programming method that uses our predictions to map every known and putative gene in a given genome into its most probable operon. We evaluate our approach using data from the E. coli K-12 genome.

Gene Expression Profiling↗

PubMed1995

Computer simulation of human body dynamics.

Understanding human body dynamics is important in many situations, such as automobile and aircraft crashes, aircraft ejections, falls, and other acceleration environments. The design of automobile interiors, cockpits, and safety equipment requires knowledge of the forces and accelerations encountered during an emergency. Because of the limited information available from actual events and the various constraints in testing, computer simulations are often the only means of obtaining detailed information. The Armstrong Laboratory (AL) developed the Articulated Total Body (ATB) model to predict the human body dynamics in many of these environments. This model is a three-dimensional rigid body dynamics program in which the human body is modeled as a series of segments. Forces on the body segments are calculated based on their interaction with the surroundings including seat and cockpit surfaces. The model also calculates the internal joint resistive and constraint forces. Because of this capability to predict both internal and external forces acting on the body, the ATB model can be used in investigating injuries. It is also a valuable design tool for evaluating safety of proposed systems before prototypes are built or costly tests conducted. When testing is conducted, the model provides data that cannot be measured, such as forces within the body, and supplementing test data with parameter variation simulations. To validate the model, tests such as those conducted on the AL impact sled are simulated. Test films and instrumentation data are compared with simulation graphics and quantitative output to gain confidence in the simulation results.

Acceleration↗

PubMedDate not supplied

[Restoration theory in models of optimal feeding behavior].

The method of stochastic dynamic programming is widely used in ecology of behavior, but has some imperfections because of use of temporal limits. The authors presented an alternative approach based on the methods of the theory of restoration. Suggested method uses cumulative energy reserves per time unit as a criterium, that leads to stationary cycles in the area of states. This approach allows to study the optimal feeding by analytic methods.

Algorithms↗

PubMed2000

Biological sequence compression algorithms.

Today, more and more DNA sequences are becoming available. The information about DNA sequences are stored in molecular biology databases. The size and importance of these databases will be bigger and bigger in the future, therefore this information must be stored or communicated efficiently. Furthermore, sequence compression can be used to define similarities between biological sequences. The standard compression algorithms such as gzip or compress cannot compress DNA sequences, but only expand them in size. On the other hand, CTW (Context Tree Weighting Method) can compress DNA sequences less than two bits per symbol. These algorithms do not use special structures of biological sequences. Two characteristic structures of DNA sequences are known. One is called palindromes or reverse complements and the other structure is approximate repeats. Several specific algorithms for DNA sequences that use these structures can compress them less than two bits per symbol. In this paper, we improve the CTW so that characteristic structures of DNA sequences are available. Before encoding the next symbol, the algorithm searches an approximate repeat and palindrome using hash and dynamic programming. If there is a palindrome or an approximate repeat with enough length then our algorithm represents it with length and distance. By using this preprocessing, a new program achieves a little higher compression ratio than that of existing DNA-oriented compression algorithms. We also describe new compression algorithm for protein sequences.

Algorithms↗

PubMed2002

An integrated pattern recognition approach for intrusion detection.

Intrusion detection systems (IDS) attempt to address the vulnerability of computer-based systems for abuse by insiders and to penetration by outsiders. An IDS is required to examine an enormous amount of data generated by computer networks to assist in the abuse detection process. Thus, there is a need to develop automated tools that address these requirements to assist system operators in the detection of violations of existing security policies. In this research, an automated IDS is proposed for insider threats in a distributed system. The proposed IDS functions as an anomaly detector for insider system operations based on the analysis of the system's log files. The approach integrates dynamic programming and adaptive resonance theory (ART1) clustering. The integrated approach aligns sequences of log events with prototypical sequences of events for performing tasks and classifies the aligned sequences for intrusion detection. The system examined for this research is a Boots System for controlling the movement of boots from one place to another under specific security restrictions related to the boot orders. We present the proposed model, the results achieved and the analysis of an implemented prototype.

Algorithms↗

PubMed2002

Atherosclerosis and flow in carotid arteries with authentic geometries.

The influence of blood flow on the depositions and development of atherosclerotic lesions have been observed and described since the 19th century. Observations have shown that depositions correlate with regions of low wall shear stress. However, the exact correlations between depositions, vessel geometry and flow parameters are not yet known. The purpose of this study was the quantification of atherosclerosis risk factors in carotid bifurcation. This artery has attracted particular interest because lesions are often found in this bifurcation. Post mortem, the arteries are excised and vessel casts are produced. Afterwards, the arteries are analyzed morphometrically. The vessel casts are used for the assessment of some geometrical parameters. 31 carotid bifurcations were analyzed in this study. Eight vessel casts were digitized and rendered three-dimensional mathematical models of the arteries. These data were imported by the computational fluid dynamics program FLUENT. Further, the blood flow was reconstructed in a computer model based on the individual vessel geometry. The flow parameters, such as velocity, pressure and wall shear stress were computed. At the same time the geometrical parameters and wall alterations are known. This permits the comparison of the anatomical shape and its flow with the distribution and level of the wall alterations.

Adult↗

PubMed1996

Large-scale Homologous Analysis of Genome Sequence.

We described a new method for the large-scale homologous analysis of genome sequences, which used hashing technique combined with sparse dynamic programming to get a sequence alignment. Three examples, the plant chloroplast genomes, the mammalian T-cell receptors C(alpha)/C(delta) gene loci and the mammalian gamma-crystallin gene clusters were analysed. The results showed that the method was more rapid to obtain accurate enough data and might be useful in genome analysis.

Journal Article↗

PubMed2003

Probabilistic graphical models for computational biomedicine.

BACKGROUND: As genomics becomes increasingly relevant to medicine, medical informatics and bioinformatics are gradually converging into a larger field that we call computational biomedicine. OBJECTIVES: Developing a computational framework that is common to the different disciplines that compose computational biomedicine will be a major enabler of the further development and integration of this research domain. METHODS: Probabilistic graphical models such as Hidden Markov Models, belief networks, and missing-data models together with computational methods such as dynamic programming, Expectation-Maximization, data-augmentation Gibbs sampling, and the Metropolis-Hastings algorithm provide the tools for an integrated probabilistic approach to computational biomedicine. RESULTS AND CONCLUSIONS: We show how graphical models have already found a broad application in different fields composing computational biomedicine. We also indicate several challenges that lie at the interface between medical informatics, statistical genomics, and bioinformatics. We also argue that graphical models offer a unified framework making it possible to integrate in a statistically meaningful way multiple models ranging from the molecular level to cellular and to clinical levels. Because of their versatility and firm statistical underpinning, we assert that probabilistic graphical models can serve as the lingua franca for many computationally intensive approaches to biology and medicine. As such, graphical models should be a foundation of the curriculum of students in these fields. From such a foundation, students could then build towards specific computational methods in medical informatics, medical image analysis, statistical genetics, or bioinformatics while keeping the communication open between these areas.

Computational Biology↗

PubMed2004

waveTM: wavelet-based transmembrane segment prediction.

waveTM is a web tool for the prediction of transmembrane segments in alpha-helical membrane proteins. Prediction is performed by a dynamic programming algorithm on wavelet-denoised 'hydropathy' signals. Users submit a protein sequence and receive interactively the results. Topology prediction can also be obtained in conjunction with the algorithm OrienTM. A web server that implements the waveTM algorithm is freely available at http://bioinformatics.biol.uoa.gr/waveTM.

Algorithms↗

PubMed2002

Semi-automatic landmark detection in digital X-ray images of the spine.

Quantitative diagnosis of 3D scoliotic deformities depends on a number of dedicated measurements. Existing methods rely on the manual determination of a series of anatomical landmarks in X-ray images. We have developed an automatic method to alleviate the burden of this tedious task. Our method looks for a compromise between local image information and global prior constraints and finds the most probable points using dynamic programming optimization. Remaining errors can be quickly corrected by effective user interaction. The first results are promising.

Humans↗

PubMed2004

Graphical approach to weak motif recognition.

We address the weak motif recognition problem in DNA sequences, which extends the general motif recognition to more difficult cases, allowing more degenerations in motif instances. Several algorithms have earlier attempted to find weak motifs in DNA sequences but with limitations. In this paper, we propose a graph-based algorithm for weak motif detection, which uses dynamic programming approach to find cliques indicating motif instances. The experiments on synthetic datasets show that the algorithm finds weak motif instances more accurately and efficiently compared to earlier approaches. Its performances on real datasets in finding transcription factor binding sites are comparable with the existing techniques.

Algorithms↗

PubMed2004

IRIS: intermolecular RNA interaction search.

Here we present IRIS, a method for prediction of RNA-RNA interactions that is based on dynamic programming and extends current RNA secondary structure prediction approaches. Using this method we have found a number of interesting refinements to the structures of RNA-RNA complexes that have been studied previously and predicted novel targets for several known regulatory RNAs in E. coli. The computational time and memory usage of IRIS are O(n(3)m(3)) and O(n(2)m(2)), respectively, where n and m are the lengths of the input sequences. IRIS can be used for analysis of antisense regulatory systems in sequenced organisms and for the design of artificial riboregulators such as antisense drugs.

Base Sequence↗

PubMed2003

Efficient tree-matching methods for accurate carbohydrate database queries.

One aspect of glycome informatics is the analysis of carbohydrate sugar chains, or glycans, whose basic structure is not a sequence, but a tree structure. Although there has been much work in the development of sequence databases and matching algorithms for sequences (for performing queries and analyzing similarity), the more complicated tree structure of glycans does not allow a direct implementation of such a database for glycans, and further, does not allow for the direct application of sequence alignment algorithms for performing searches or analyzing similarity. Therefore, we have utilized a polynomial-time dynamic programming algorithm for solving the maximum common subtree of two trees to implement an accurate and efficient tool for finding and aligning maximally matching glycan trees. The KEGG Glycan database for glycan structures released recently incorporates our tree-structure alignment algorithm with various parameters to adapt to the needs of a variety of users. Because we use similarity scores as opposed to a distance metric, our methods are more readily used to display trees of higher similarity. We present the two methods developed for this purpose and illustrate its validity.

Algorithms↗

PubMed2005

Discovering sequence-structure motifs from protein segments and two applications.

We present a novel method for clustering short protein segments having strong sequence-structure correlations, and demonstrate that these clusters contain useful structural information via two applications. When applied to local tertiary structure prediction, we achieve approximately 60% accuracy with a novel dynamic programming algorithm. When applied to secondary structure prediction based on Support Vector Machines, we obtain a approximately 2% gain in Q3 performance by incorporating cluster-derived data into training and classification. These encouraging results illustrate the great potential of using conserved local motifs to tackle protein structure predictions and possibly other important problems in biology.

Algorithms↗

PubMed2002

Fast and sensitive algorithm for aligning ESTs to human genome.

There is a pressing need to align growing set of expressed sequence tags (ESTs) to newly sequenced human genome. The problem is, however, complicated by the exon/intron structure of eucaryotic genes, misread nucleotides in ESTs, and millions of repeptive sequences in genomic sequences. Indeed, to solve this, algorithms that use dynamic programming have been proposed, but in reality, these algorithms require an enormous amount of processing time. In an effort to improve the computational efficiency of these classical DP algorithms, we develop software that fully utilizes the lookup-table for allowing the efficient detection of the start- and endpoints of an EST within a given DNA sequence, and subsequently, the prompt identification of exons and introns. In addition, high sensitivity and accuracy must be achieved by calculating locations of all spliced sites correctly for more ESTs while retaining high computational efficiency. This goal is hard to accomplish in practice, owing to misread nucleotides in ESTs and repeptive sequences in the genome, but we present a couple of heuristics effective in settling this issue. Experimental results have confirmed that our technique improves the overall computation time by orders of magnitude compared with common tools such as sim4 and BLAT, and attains high sensitivity and accuracy against datasets of clean and documented genes at the same time.

Algorithms↗

PubMed2005

[Coronary artery motion estimation using X-ray cineangiogram].

This paper presents an approach for estimating the non-rigid motion of coronary arteries using digital angiographic images. Displacement vectors of vessel points are obtained by finding points correspondences in two successive frames. Smoothness of motion field and vessel deformation measurement are considered in matching, and unmatched regions are also dealt with in the fact that the vessel after deformation may have different size with its original station. The search strategy for optimal matching is carried out using dynamic programming (DP) so that computing cost is reduced. Results of this motion estimation method applied to synthetic and clinical images have shown that the method is accurate, with a root mean square error about one pixel for simulated data. For the case of actual X-ray coronary angiographic images, visual inspection of the detected pairs of points shows that the results are very encouraging.

Angiography, Digital Subtraction↗

PubMedDate not supplied

[On prediction of folding nuclei in globular proteins].

The approach described in this paper on the prediction of folding nuclei in globular proteins with known three dimensional structures is based on a search of the lowest saddle points through the barrier separating the unfolded state from the native structure on the free-energy landscape of protein chain. This search is performed by a dynamic programming method. Comparison of theoretical results with experimental data on the folding nuclei of two dozen of proteins shows that our model provides good phi value predictions for proteins whose structures have been determined by X-ray analysis, with a less limited success for proteins whose structures have been determined by NMR techniques only. Consideration of a full ensemble of transition states results in more successful prediction than consideration of only the transition states with the minimal free energy. In conclusion we have predicted the localization of folding nuclei for three dimensional protein structures for which kinetics of folding is studied now but the localization of folding nuclei is still unknown.

Kinetics↗

PubMed2004

Pair stochastic tree adjoining grammars for aligning and predicting pseudoknot RNA structures.

MOTIVATION: Since the whole genome sequences for many species are currently available, computational predictions of RNA secondary structures and computational identifications of those non-coding RNA regions by comparative genomics become important, and require more advanced alignment methods. Recently, an approach of structural alignments for RNA sequences has been introduced to solve these problems. By structural alignments, we mean a pairwise alignment to align an unfolded RNA sequence into a folded RNA sequence of known secondary structure. Pair HMMs on tree structures (PHMMTSs) proposed by Sakakibara are efficient automata-theoretic models for structural alignments of RNA secondary structures, but are incapable of handling pseudoknots. On the other hand, tree adjoining grammars (TAGs) is a subclass of context-sensitive grammar, which is suitable for modeling pseudoknots. Our goal is to extend PHMMTSs by incorporating TAGs to be able to handle pseudoknots. RESULTS: We propose the pair stochastic tree adjoining grammars (PSTAGs) for modeling RNA secondary structures including pseudoknots and show the strong experimental evidences that modeling pseudoknot structures significantly improves the prediction accuracies of RNA secondary structures. First, we extend the notion of PHMMTSs defined on alignments of 'trees' to PSTAGs defined on alignments of "TAG (derivation) trees", which represent a top-down parsing process of TAGs and are functionally equivalent to derived trees of TAGs. Second, we modify PSTAGs so that it takes as input a pair of a linear sequence and a TAG tree representing a pseudoknot structure of RNA to produce a structural alignment. Then, we develop a polynomial-time algorithm for obtaining an optimal structural alignment by PSTAGs, based on dynamic programming parser. We have done several computational experiments for predicting pseudoknots by PSTAGs, and our computational experiments suggests that prediction of RNA pseudoknot structures by our method are more efficient and biologically plausible than by other conventional methods. The binary code for PSTAG method is freely available from our website at http://www.dna.bio.keio.ac.jp/pstag/.

Algorithms↗