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At least 523 records · Page 29Linked to original sources
PubMed1991

Scanning protein sequence databanks using a distributed processing workstation network.

The programme pscan has been developed to distribute protein databank scans over a network of computers that share a common file system. pscan may be used in conjunction with most conventional sequence comparison programmes with few modifications. In test runs using the Smith-Waterman dynamic programming algorithm, the time required to scan a 6858 sequence databank using a query sequence 740 residues long was reduced from approximately 50 min for a single processor, to approximately 11 minutes for five processors. Accordingly, pscan provides a low-cost, portable alternative to dedicated parallel processing computers.

Algorithms↗
PubMed1992

Statistical distance between texts and filtration methods in sequence comparison.

Upon searching local similarities in long sequences, the necessity of a 'rapid' similarity search becomes acute. Quadratic complexity of dynamic programming algorithms forces the employment of filtration methods that allow elimination of the sequences with a low similarity level. The paper is devoted to the theoretical substantiations of the filtration method based on the statistical distance between texts. The notion of the filtration efficiency is introduced and the efficiency of several filters is estimated. It is shown that the efficiency of the statistical l-tuple filtration upon DNA database search is associated with a potential extension of the original four-letter alphabet and grows exponentially with increasing l. The formula that allows one to estimate the filtration parameters is presented.

Amino Acid Sequence↗
PubMed1992

Parallelization of a local similarity algorithm.

The local similarity problem is to determine the similar regions within two given sequences. We recently developed a dynamic programming algorithm for the local similarity problem that requires only space proportional to the sum of the two sequence lengths, whereas earlier methods use space proportional to the product of the lengths. In this paper, we describe how to parallelize the new algorithm and present results of experimental studies on an Intel hypercube. The parallel method provides rapid, high-resolution alignments for users of our software toolkit for pairwise sequence comparison, as illustrated here by a comparison of the chloroplast genomes of tobacco and liverwort.

Algorithms↗
PubMed1992

Base-pair probability profiles of RNA secondary structures.

Dynamic programming algorithms are able to predict optimal and suboptimal secondary structures of RNA. These suboptimal or alternative secondary structures are important for the biological function of RNA. The distribution of secondary structures present in solution is governed by the thermodynamic equilibrium between the different structures. An algorithm is presented which approximates the total partition function by a Boltzmann-weighted summation of optimal and suboptimal secondary structures at several temperatures. A clear representation of the equilibrium distribution of secondary structures is derived from a two-dimensional bonding matrix with base-pairing probability as the third dimension. The temperature dependence of the equilibrium distribution gives the denaturation behavior of the nucleic acid, which may be compared to experimental optical denaturation curves after correction for the hypochromicities of the different base-pairs. Similarly, temperature-induced mobility changes detected in temperature-gradient gel electrophoresis of nucleic acids may be interpreted on the basis of the temperature dependence of the equilibrium distribution. Results are illustrated for natural circular and synthetic linear potato spindle tuber viroid RNA respectively, and are compared to experimental data.

Algorithms↗
PubMed1993

A fast, sensitive pattern-matching approach for protein sequences.

Pattern-matching algorithms are a powerful tool for finding similarities and relationships among the steadily growing amount of known protein sequences. We present a fast, sensitive pattern-matching algorithm that describes a pattern by its physico-chemical properties rather than by occurrence of amino acids, using a fast, dynamic programming algorithm. Selected examples will demonstrate applications and advantages of our approach.

Algorithms↗
PubMed1993

Optimal alignment between groups of sequences and its application to multiple sequence alignment.

Four algorithms, A-D, were developed to align two groups of biological sequences. Algorithm A is equivalent to the conventional dynamic programming method widely used for aligning ordinary sequences, whereas algorithms B-D are designed to evaluate the cost for a deletion/insertion more accurately when internal gaps are present in either or both groups of sequences. Rigorous optimization of the 'sum of pairs' (SP) score is achieved by algorithm D, whose average performance is close to O(MNL2), where M and N are numbers of sequences included in the two groups and L is the mean length of the sequences. Algorithm B uses some approximations to cope with profile-based operations, whereas algorithm C is a simpler variant of algorithm D. These group-to-group alignment algorithms were applied to multiple sequence alignment with two iterative strategies: a progressive method based on a given binary tree and a randomized grouping--realignment method. The advantages and disadvantages of the four algorithms are discussed on the basis of the results of examinations of several protein families.

Algorithms↗
PubMed1993

Discovering simple DNA sequences by the algorithmic significance method.

A new method, 'algorithmic significance', is proposed as a tool for discovery of patterns in DNA sequences. The main idea is that patterns can be discovered by finding ways to encode the observed data concisely. In this sense, the method can be viewed as a formal version of the Occam's Razor principle. In this paper the method is applied to discover significantly simple DNA sequences. We define DNA sequences to be simple if they contain repeated occurrences of certain 'words' and thus can be encoded in a small number of bits. Such definition includes minisatellites and microsatellites. A standard dynamic programming algorithm for data compression is applied to compute the minimal encoding lengths of sequences in linear time. An electronic mail server for identification of simple sequences based on the proposed method has been installed at the Internet address pythia/anl.gov.

Algorithms↗
PubMed2026

Theseus: fast and optimal affine-gap sequence-to-graph alignment.

MOTIVATION: Sequence-to-graph alignment is a central problem in bioinformatics, with applications in multiple sequence alignment (MSA) and pangenome analysis, among others. However, current algorithms for optimal affine-gap alignment impose high memory and computational requirements, limiting their scalability to aligning long sequences to complex graphs. Practical solutions partially address this problem using heuristic strategies that ultimately trade off optimality for speed. RESULTS: This work presents Theseus, a novel, fast, and optimal affine-gap sequence-to-graph alignment algorithm. Theseus leverages similarities between genomic sequences to accelerate the alignment computation and reduces the overall memory requirements without compromising optimality. To that end, Theseus processes only a subset of the dynamic programming cells, using a sparse-data strategy that enables efficient sequence-to-graph alignment. Moreover, our algorithm supports optimal affine-gap alignment on arbitrary directed graphs, including those with cycles. We evaluate Theseus on two key problems: MSA and pangenome read mapping. For MSA, we compare it against SPOA, abPOA, and POASTA. Theseus is 1.6× to 17.6× faster than POASTA, and 7.3× faster, on average, than SPOA, both optimal aligners. Compared with abPOA, Theseus ensures optimality and scales to the largest problems. For pangenome read mapping, we benchmark Theseus against the alignment stage of the mapping tool vg map, along with the alignment kernels of SPOA, abPOA, and POASTA. Theseus outperforms the other methods, showing a 1.9× to 16.9× speedup on short reads. Moreover, Theseus is 1.5× to 36.3× faster than vg when aligning against synthetic cyclic graphs. AVAILABILITY AND IMPLEMENTATION: Theseus code and documentation are publicly available at https://github.com/albertjimenezbl/theseus-lib.

Algorithms↗
PubMed2003

Fast identification and statistical evaluation of segmental homologies in comparative maps.

MOTIVATION: Chromosomal segments that share common ancestry, either through genomic duplication or species divergence, are said to be segmental homologs of one another. Their identification allows researchers to leverage knowledge of model organisms for use in other systems and is of value for studies of genome evolution. However, identification and statistical evaluation of segmental homologies can be a challenge when the segments are highly diverged. RESULTS: We describe a flexible dynamic programming algorithm for the identification of segments having multiple homologous features. We model the probability of observing putative segmental homologies by chance and incorporate our findings into the parameterization of the algorithm and the statistical evaluation of its output. Combined, these findings allow segmental homologies to be identified in comparisons within and between genomic maps in a rigorous, rapid, and automated fashion.

Algorithms↗
PubMed2003

HMM sampling and applications to gene finding and alternative splicing.

The standard method of applying hidden Markov models to biological problems is to find a Viterbi (maximal weight) path through the HMM graph. The Viterbi algorithm reduces the problem of finding the most likely hidden state sequence that explains given observations, to a dynamic programming problem for corresponding directed acyclic graphs. For example, in the gene finding application, the HMM is used to find the most likely underlying gene structure given a DNA sequence. In this note we discuss the applications of sampling methods for HMMs. The standard sampling algorithm for HMMs is a variant of the common forward-backward and backtrack algorithms, and has already been applied in the context of Gibbs sampling methods. Nevetheless, the practice of sampling state paths from HMMs does not seem to have been widely adopted, and important applications have been overlooked. We show how sampling can be used for finding alternative splicings for genes, including alternative splicings that are conserved between genes from related organisms. We also show how sampling from the posterior distribution is a natural way to compute probabilities for predicted exons and gene structures being correct under the assumed model. Finally, we describe a new memory efficient sampling algorithm for certain classes of HMMs which provides a practical sampling alternative to the Hirschberg algorithm for optimal alignment. The ideas presented have applications not only to gene finding and HMMs but more generally to stochastic context free grammars and RNA structure prediction.

Algorithms↗
PubMed2003

Generating consensus sequences from partial order multiple sequence alignment graphs.

MOTIVATION: Consensus sequence generation is important in many kinds of sequence analysis ranging from sequence assembly to profile-based iterative search methods. However, how can a consensus be constructed when its inherent assumption-that the aligned sequences form a single linear consensus-is not true? RESULTS: Partial Order Alignment (POA) enables construction and analysis of multiple sequence alignments as directed acyclic graphs containing complex branching structure. Here we present a dynamic programming algorithm (heaviest_bundle) for generating multiple consensus sequences from such complex alignments. The number and relationships of these consensus sequences reveals the degree of structural complexity of the source alignment. This is a powerful and general approach for analyzing and visualizing complex alignment structures, and can be applied to any alignment. We illustrate its value for analyzing expressed sequence alignments to detect alternative splicing, reconstruct full length mRNA isoform sequences from EST fragments, and separate paralog mixtures that can cause incorrect SNP predictions. AVAILABILITY: The heaviest_bundle source code is available at http://www.bioinformatics.ucla.edu/poa

Algorithms↗
PubMed2003

CGH-Plotter: MATLAB toolbox for CGH-data analysis.

CGH-Plotter is a MATLAB toolbox with a graphical user interface for the analysis of comparative genomic hybridization (CGH) microarray data. CGH-Plotter provides a tool for rapid visualization of CGH-data according to the locations of the genes along the genome. In addition, the CGH-Plotter identifies regions of amplifications and deletions, using k-means clustering and dynamic programming. The application offers a convenient way to analyze CGH-data and can also be applied for the analysis of cDNA microarray expression data. CGH-Plotter toolbox is platform independent and requires MATLAB 6.1 or higher to operate.

Cluster Analysis↗
PubMed2004

Efficient filtering methods for clustering cDNAs with spliced sequence alignment.

MOTIVATION: Clustering sequences of a full-length cDNA library into alternative splice form candidates is a very important problem. RESULTS: We developed a new efficient algorithm to cluster sequences of a full-length cDNA library into alternative splice form candidates. Current clustering algorithms for cDNAs tend to produce too many clusters containing incorrect splice form candidates. Our algorithm is based on a spliced sequence alignment algorithm that considers splice sites. The spliced sequence alignment algorithm is a variant of an ordinary dynamic programming algorithm, which requires O(nm) time for checking a pair of sequences where n and m are the lengths of the two sequences. Since the time bound is too large to perform all-pair comparison for a large set of sequences, we developed new techniques to reduce the computation time without affecting the accuracy of the output clusters. Our algorithm was applied to 21 076 mouse cDNA sequences of the FANTOM 1.10 database to examine its performance and accuracy. In these experiments, we achieved about 2-12-fold speedup against a method using only a traditional hash-based technique. Moreover, without using any information of the mouse genome sequence data or any gene data in public databases, we succeeded in listing 87-89% of all the clusters that biologists have annotated manually. AVAILABILITY: We provide a web service for cDNA clustering located at https://access.obigrid.org/ibm/cluspa/, for which registration for the OBIGrid (http://www.obigrid.org) is required.

Algorithms↗
PubMed2004

An iterated loop matching approach to the prediction of RNA secondary structures with pseudoknots.

MOTIVATION: Pseudoknots have generally been excluded from the prediction of RNA secondary structures due to its difficulty in modeling. Although, several dynamic programming algorithms exist for the prediction of pseudoknots using thermodynamic approaches, they are neither reliable nor efficient. On the other hand, comparative methods are more reliable, but are often done in an ad hoc manner and require expert intervention. Maximum weighted matching, an algorithm for pseudoknot prediction with comparative analysis, suffers from low-prediction accuracy in many cases. RESULTS: Here we present an algorithm, iterated loop matching, for reliably and efficiently predicting RNA secondary structures including pseudoknots. The method can utilize either thermodynamic or comparative information or both, thus is able to predict pseudoknots for both aligned and individual sequences. We have tested the algorithm on a number of RNA families. Using 8-12 homologous sequences, the algorithm correctly identifies more than 90% of base-pairs for short sequences and 80% overall. It correctly predicts nearly all pseudoknots and produces very few spurious base-pairs for sequences without pseudoknots. Comparisons show that our algorithm is both more sensitive and more specific than the maximum weighted matching method. In addition, our algorithm has high-prediction accuracy on individual sequences, comparable with the PKNOTS algorithm, while using much less computational resources. AVAILABILITY: The program has been implemented in ANSI C and is freely available for academic use at http://www.cse.wustl.edu/~zhang/projects/rna/ilm/ SUPPLEMENTARY INFORMATION: http://www.cse.wustl.edu/~zhang/projects/rna/ilm/

Algorithms↗
PubMed2004

Discovering patterns to extract protein-protein interactions from full texts.

MOTIVATION: Although there are several databases storing protein-protein interactions, most such data still exist only in the scientific literature. They are scattered in scientific literature written in natural languages, defying data mining efforts. Much time and labor have to be spent on extracting protein pathways from literature. Our aim is to develop a robust and powerful methodology to mine protein-protein interactions from biomedical texts. RESULTS: We present a novel and robust approach for extracting protein-protein interactions from literature. Our method uses a dynamic programming algorithm to compute distinguishing patterns by aligning relevant sentences and key verbs that describe protein interactions. A matching algorithm is designed to extract the interactions between proteins. Equipped only with a dictionary of protein names, our system achieves a recall rate of 80.0% and precision rate of 80.5%. AVAILABILITY: The program is available on request from the authors.

Algorithms↗
PubMed2004

A graph-theoretic approach for the separation of b and y ions in tandem mass spectra.

MOTIVATION: Ion-type identification is a fundamental problem in computational proteomics. Methods for accurate identification of ion types provide the basis for many mass spectrometry data interpretation problems, including (a) de novo sequencing, (b) identification of post-translational modifications and mutations and (c) validation of database search results. RESULTS: Here, we present a novel graph-theoretic approach for solving the problem of separating b ions from y ions in a set of tandem mass spectra. We represent each spectral peak as a node and consider two types of edges: type-1 edge connecting two peaks probably of the same ion types and type-2 edge connecting two peaks probably of different ion types. The problem of ion-separation is formulated and solved as a graph partition problem, which is to partition the graph into three subgraphs, representing b, y and others ions, respectively, through maximizing the total weight of type-1 edges while minimizing the total weight of type-2 edges within each partitioned subgraph. We have developed a dynamic programming algorithm for rigorously solving this graph partition problem and implemented it as a computer program PRIME (PaRtition of Ion types in tandem Mass spEctra). The tests on a large amount of simulated mass spectra and 19 sets of high-quality experimental Fourier transform ion cyclotron resonance tandem mass spectra indicate that an accuracy level of approximately 90% for the separation of b and y ions was achieved. AVAILABILITY: The executable code of PRIME is available upon request. CONTACT: xyn@bmb.uga.edu.

Algorithms↗
PubMed2005

Three-stage prediction of protein beta-sheets by neural networks, alignments and graph algorithms.

MOTIVATION: Protein beta-sheets play a fundamental role in protein structure, function, evolution and bioengineering. Accurate prediction and assembly of protein beta-sheets, however, remains challenging because protein beta-sheets require formation of hydrogen bonds between linearly distant residues. Previous approaches for predicting beta-sheet topological features, such as beta-strand alignments, in general have not exploited the global covariation and constraints characteristic of beta-sheet architectures. RESULTS: We propose a modular approach to the problem of predicting/assembling protein beta-sheets in a chain by integrating both local and global constraints in three steps. The first step uses recursive neural networks to predict pairing probabilities for all pairs of interstrand beta-residues from profile, secondary structure and solvent accessibility information. The second step applies dynamic programming techniques to these probabilities to derive binding pseudoenergies and optimal alignments between all pairs of beta-strands. Finally, the third step uses graph matching algorithms to predict the beta-sheet architecture of the protein by optimizing the global pseudoenergy while enforcing strong global beta-strand pairing constraints. The approach is evaluated using cross-validation methods on a large non-homologous dataset and yields significant improvements over previous methods. AVAILABILITY: http://www.igb.uci.edu/servers/psss.html.

Algorithms↗
PubMed2005

Recovering haplotype structure through recombination and gene conversion.

MOTIVATION: Understanding haplotype evolution subject to mutation, recombination and gene conversion is fundamental to understand genetic specificities of human populations and hereditary bases of complex disorders. The goal of this project is to develop new algorithmic tools assisting the reconstruction of historical relationships between haplotypes and the inference of haplotypes from genotypes. RESULTS: We present two new algorithms. The first one finds an optimal pathway of mutations, recombinations and gene conversions leading to a given haplotype of size m from a population of h haplotypes. It runs in time O(mhs(2)), where s is the maximum number of contiguous sites that can be exchanged in a single gene conversion. The second one finds an optimal pathway of mutations and recombinations leading to a given genotype, and runs in time O(mh(2)). Both algorithms are based on a penalty score model and use a dynamic programming approach. We apply the second one to the problem of inferring haplotypes from genotypes, and show how it can be used as an independent tool, or to improve the performance of existing methods. AVAILABILITY: The algorithms have been implemented in JAVA and are available on request.

Algorithms↗