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At least 379 records · Page 21Linked to original sources
PubMed2000

Iterative sequence/secondary structure search for protein homologs: comparison with amino acid sequence alignments and application to fold recognition in genome databases.

MOTIVATION: Sequence alignment techniques have been developed into extremely powerful tools for identifying the folding families and function of proteins in newly sequenced genomes. For a sufficiently low sequence identity it is necessary to incorporate additional structural information to positively detect homologous proteins. We have carried out an extensive analysis of the effectiveness of incorporating secondary structure information directly into the alignments for fold recognition and identification of distant protein homologs. A secondary structure similarity matrix based on a database of three-dimensionally aligned proteins was first constructed. An iterative application of dynamic programming was used which incorporates linear combinations of amino acid and secondary structure sequence similarity scores. Initially, only primary sequence information is used. Subsequently contributions from secondary structure are phased in and new homologous proteins are positively identified if their scores are consistent with the predetermined error rate. RESULTS: We used the SCOP40 database, where only PDB sequences that have 40% homology or less are included, to calibrate homology detection by the combined amino acid and secondary structure sequence alignments. Combining predicted secondary structure with sequence information results in a 8-15% increase in homology detection within SCOP40 relative to the pairwise alignments using only amino acid sequence data at an error rate of 0.01 errors per query; a 35% increase is observed when the actual secondary structure sequences are used. Incorporating predicted secondary structure information in the analysis of six small genomes yields an improvement in the homology detection of approximately 20% over SSEARCH pairwise alignments, but no improvement in the total number of homologs detected over PSI-BLAST, at an error rate of 0.01 errors per query. However, because the pairwise alignments based on combinations of amino acid and secondary structure similarity are different from those produced by PSI-BLAST and the error rates can be calibrated, it is possible to combine the results of both searches. An additional 25% relative improvement in the number of genes identified at an error rate of 0.01 is observed when the data is pooled in this way. Similarly for the SCOP40 dataset, PSI-BLAST detected 15% of all possible homologs, whereas the pooled results increased the total number of homologs detected to 19%. These results are compared with recent reports of homology detection using sequence profiling methods. AVAILABILITY: Secondary structure alignment homepage at http://lutece.rutgers.edu/ssas CONTACT: anders@rutchem.rutgers.edu; ronlevy@lutece.rutgers.edu SUPPLEMENTARY INFORMATION: Genome sequence/structure alignment results at http://lutece.rutgers.edu/ss_fold_predictions.

Algorithms↗
PubMed2000

Optimizing reduced-space sequence analysis.

MOTIVATION: Dynamic programming is the core algorithm of sequence comparison, alignment and linear hidden Markov model (HMM) training. For a pair of sequence lengths m and n, the problem can be solved readily in O(mn)time and O(mn)space. The checkpoint algorithm introduced by Grice et al. (CABIOS, 13, 45--53, 1997) runs in O(Lmn)time and O(Lm(L) square root of n)space, where L is a positive integer determined by m, n, and the amount of available workspace. The algorithm is appropriate for many string comparison problems, including all-paths and single-best-path hidden Markov model training, and is readily parallelizable. The checkpoint algorithm has a diagonal version that can solve the single-best-path alignment problem in O(mn)time and O(m + n)space. RESULTS: In this work, we improve performance by analyzing optimal checkpoint placement. The improved row checkpoint algorithm performs up to one half the computation of the original algorithm. The improved diagonal checkpoint algorithm performs up to 35% fewer computational steps than the original. We modified the SAM hidden Markov modeling package to use the improved row checkpoint algorithm. For a fixed sequence length, the new version is up to 33% faster for all-paths and 56% faster for single-best-path HMM training, depending on sequence length and allocated memory. Over a typical set of protein sequence lengths, the improvement is approximately 10%.

Algorithms↗
PubMed2000

Homology-based gene structure prediction: simplified matching algorithm using a translated codon (tron) and improved accuracy by allowing for long gaps.

MOTIVATION: Locating protein-coding exons (CDSs) on a eukaryotic genomic DNA sequence is the initial and an essential step in predicting the functions of the genes embedded in that part of the genome. Accurate prediction of CDSs may be achieved by directly matching the DNA sequence with a known protein sequence or profile of a homologous family member(s). RESULTS: A new convention for encoding a DNA sequence into a series of 23 possible letters (translated codon or tron code) was devised to improve this type of analysis. Using this convention, a dynamic programming algorithm was developed to align a DNA sequence and a protein sequence or profile so that the spliced and translated sequence optimally matches the reference the same as the standard protein sequence alignment allowing for long gaps. The objective function also takes account of frameshift errors, coding potentials, and translational initiation, termination and splicing signals. This method was tested on Caenorhabditis elegans genes of known structures. The accuracy of prediction measured in terms of a correlation coefficient (CC) was about 95% at the nucleotide level for the 288 genes tested, and 97. 0% for the 170 genes whose product and closest homologue share more than 30% identical amino acids. We also propose a strategy to improve the accuracy of prediction for a set of paralogous genes by means of iterative gene prediction and reconstruction of the reference profile derived from the predicted sequences. AVAILABILITY: The source codes for the program 'aln' written in ANSI-C and the test data will be available via anonymous FTP at ftp.genome.ad.jp/pub/genomenet/saitama-cc. CONTACT: gotoh@cancer-c.pref.saitama.jp

Algorithms↗
PubMed2000

The language of RNA: a formal grammar that includes pseudoknots.

MOTIVATION: In a previous paper, we presented a polynomial time dynamic programming algorithm for predicting optimal RNA secondary structure including pseudoknots. However, a formal grammatical representation for RNA secondary structure with pseudoknots was still lacking. RESULTS: Here we show a one-to-one correspondence between that algorithm and a formal transformational grammar. This grammar class encompasses the context-free grammars and goes beyond to generate pseudoknotted structures. The pseudoknot grammar avoids the use of general context-sensitive rules by introducing a small number of auxiliary symbols used to reorder the strings generated by an otherwise context-free grammar. This formal representation of the residue correlations in RNA structure is important because it means we can build full probabilistic models of RNA secondary structure, including pseudoknots, and use them to optimally parse sequences in polynomial time.

Algorithms↗
PubMed2000

Using traveling salesman problem algorithms for evolutionary tree construction.

MOTIVATION: The construction of evolutionary trees is one of the major problems in computational biology, mainly due to its complexity. RESULTS: We present a new tree construction method that constructs a tree with minimum score for a given set of sequences, where the score is the amount of evolution measured in PAM distances. To do this, the problem of tree construction is reduced to the Traveling Salesman Problem (TSP). The input for the TSP algorithm are the pairwise distances of the sequences and the output is a circular tour through the optimal, unknown tree plus the minimum score of the tree. The circular order and the score can be used to construct the topology of the optimal tree. Our method can be used for any scoring function that correlates to the amount of changes along the branches of an evolutionary tree, for instance it could also be used for parsimony scores, but it cannot be used for least squares fit of distances. A TSP solution reduces the space of all possible trees to 2n. Using this order, we can guarantee that we reconstruct a correct evolutionary tree if the absolute value of the error for each distance measurement is smaller than f2.gif" BORDER="0">, where f3.gif" BORDER="0">is the length of the shortest edge in the tree. For data sets with large errors, a dynamic programming approach is used to reconstruct the tree. Finally simulations and experiments with real data are shown.

Algorithms↗
PubMed2001

Efficient primer design algorithms.

MOTIVATION: Primer design involves various parameters such as string-based alignment scores, melting temperature, primer length and GC content. This entails a design approach from multicriteria decision making. Values of some of the criteria are easy to compute while others require intense calculations. RESULTS: The reference point method was found to be tractable for trading-off between deviations from ideal values of all the criteria. Some criteria computations are based on dynamic programs with value iteration whose run time can be bounded by a low-degree polynomial. For designing standard PCR primers, the scheme offers in a relative gain in computing speed of up to 50: 1 over ad-hoc computational methods. Single PCR primer pairs have been used as model systems in order to simplify the quantization of the computational acceleration factors. The program has been structured so as to facilitate the analysis of large numbers of primer pairs with minor modifications. The scheme significantly increases primer design throughput which in turn facilitates the use of oligonucleotides in a wide range of applications including: multiplex PCR and other nucleic acid-based amplification systems, as well as in zip code targeting, oligonucleotide microarrays and nucleic acid-based nanoengineering.

Algorithms↗
PubMed2001

A new approach to sequence comparison: normalized sequence alignment.

The Smith-Waterman algorithm for local sequence alignment is one of the most important techniques in computational molecular biology. This ingenious dynamic programming approach was designed to reveal the highly conserved fragments by discarding poorly conserved initial and terminal segments. However, the existing notion of local similarity has a serious flaw: it does not discard poorly conserved intermediate segments. The Smith-Waterman algorithm finds the local alignment with maximal score but it is unable to find local alignment with maximum degree of similarity (e.g. maximal percent of matches). Moreover, there is still no efficient algorithm that answers the following natural question: do two sequences share a (sufficiently long) fragment with more than 70% of similarity? As a result, the local alignment sometimes produces a mosaic of well-conserved fragments artificially connected by poorly-conserved or even unrelated fragments. This may lead to problems in comparison of long genomic sequences and comparative gene prediction as recently pointed out by Zhang et al. (Bioinformatics, 15, 1012-1019, 1999). In this paper we propose a new sequence comparison algorithm (normalized local alignment ) that reports the regions with maximum degree of similarity. The algorithm is based on fractional programming and its running time is O(n2log n). In practice, normalized local alignment is only 3-5 times slower than the standard Smith-Waterman algorithm.

Algorithms↗
PubMed2001

Representation of amino acids as five-bit or three-bit patterns for filtering protein databases.

MOTIVATION: We propose representing amino acids by bit-patterns so they may be used in a filter algorithm for similarity searches over protein databases, to rapidly eliminate non-homologous regions of database sequences. The filter algorithm would be based on dynamic programming optimization. It would have the advantage over previous filter algorithms that its substitution scoring function distinguishes between conservative and non-conservative amino acid substitutions. RESULTS: Simulated annealing was used to search for the best five-bit or three-bit patterns to represent amino acids, where similar amino acids were given similar bit-patterns. The similarity between amino acids was estimated from the BLOSUM45 matrix. Representing amino acids by these five-bit and three-bit patterns, the Escherichia coli PhoE precursor and the bacteriophage PA2 LC precursor were aligned. The alignments were nearly the same as that obtained when BLOSUM45 was used to score substitutions. AVAILABILITY: The C code of the optimization algorithm for searching for the optimal bit-pattern representation of amino acids is available from the authors upon request.

Algorithms↗
PubMed2001

SCOPE: a probabilistic model for scoring tandem mass spectra against a peptide database.

Proteomics, or the direct analysis of the expressed protein components of a cell, is critical to our understanding of cellular biological processes in normal and diseased tissue. A key requirement for its success is the ability to identify proteins in complex mixtures. Recent technological advances in tandem mass spectrometry has made it the method of choice for high-throughput identification of proteins. Unfortunately, the software for unambiguously identifying peptide sequences has not kept pace with the recent hardware improvements in mass spectrometry instruments. Critical for reliable high-throughput protein identification, scoring functions evaluate the quality of a match between experimental spectra and a database peptide. Current scoring function technology relies heavily on ad-hoc parameterization and manual curation by experienced mass spectrometrists. In this work, we propose a two-stage stochastic model for the observed MS/MS spectrum, given a peptide. Our model explicitly incorporates fragment ion probabilities, noisy spectra, and instrument measurement error. We describe how to compute this probability based score efficiently, using a dynamic programming technique. A prototype implementation demonstrates the effectiveness of the model.

Amino Acid Sequence↗
PubMed2002

Selecting signature oligonucleotides to identify organisms using DNA arrays.

MOTIVATION: DNA arrays are a very useful tool to quickly identify biological agents present in some given sample, e.g. to identify viruses causing disease, for quality control in the food industry, or to determine bacteria contaminating drinking water. The selection of specific oligos to attach to the array surface is a relevant problem in the experiment design process. Given a set S of genomic sequences (the target sequences), the task is to find at least one oligonucleotide, called probe, for each sequence in S. This probe will be attached to the array surface, and must be chosen in a way that it will not hybridize to any other sequence but the intended target. Furthermore, all probes on the array must hybridize to their intended targets under the same reaction conditions, most importantly at the temperature T at which the experiment is conducted. RESULTS: We present an efficient algorithm for the probe design problem. Melting temperatures are calculated for all possible probe-target interactions using an extended nearest-neighbor model, allowing for both non-Watson-Crick base-pairing and unpaired bases within a duplex. To compute temperatures efficiently, a combination of suffix trees and dynamic programming based alignment algorithms is introduced. Additional filtering steps during preprocessing increase the speed of the computation. The practicability of the algorithms is demonstrated by two case studies: The identification of HIV-1 subtypes, and of 28S rDNA sequences from >or=400 organisms.

Algorithms↗
PubMed2002

PRIMEGENS: robust and efficient design of gene-specific probes for microarray analysis.

MOTIVATION: DNA microarray is a powerful high-throughput tool for studying gene function and regulatory networks. Due to the problem of potential cross hybridization, using full-length genes for microarray construction is not appropriate in some situations. A bioinformatic tool, PRIMEGENS, has recently been developed for the automatic design of PCR primers using DNA fragments that are specific to individual open reading frames (ORFs). RESULTS: PRIMEGENS first carries out a BLAST search for each target ORF against all other ORFs of the genome to quickly identify possible homologous sequences. Then it performs optimal sequence alignment between the target ORF and each of its homologous ORFs using dynamic programming. PRIMEGENS uses the sequence alignments to select gene- specific fragments, and then feeds the fragments to the Primer3 program to design primer pairs for PCR amplification. PRIMEGENS can be run from the command line on Unix/Linux platforms as a stand-alone package or it can be used from a Web interface. The program runs efficiently, and it takes a few seconds per sequence on a typical workstation. PCR primers specific to individual ORFs from Shewanella oneidensis MR-1 and Deinococcus radiodurans R1 have been designed. The PCR amplification results indicate that this method is very efficient and reliable for designing specific probes for microarray analysis.

Algorithms↗
PubMed2002

Multiple sequence alignment using partial order graphs.

MOTIVATION: Progressive Multiple Sequence Alignment (MSA) methods depend on reducing an MSA to a linear profile for each alignment step. However, this leads to loss of information needed for accurate alignment, and gap scoring artifacts. RESULTS: We present a graph representation of an MSA that can itself be aligned directly by pairwise dynamic programming, eliminating the need to reduce the MSA to a profile. This enables our algorithm (Partial Order Alignment (POA)) to guarantee that the optimal alignment of each new sequence versus each sequence in the MSA will be considered. Moreover, this algorithm introduces a new edit operator, homologous recombination, important for multidomain sequences. The algorithm has improved speed (linear time complexity) over existing MSA algorithms, enabling construction of massive and complex alignments (e.g. an alignment of 5000 sequences in 4 h on a Pentium II). We demonstrate the utility of this algorithm on a family of multidomain SH2 proteins, and on EST assemblies containing alternative splicing and polymorphism. AVAILABILITY: The partial order alignment program POA is available at http://www.bioinformatics.ucla.edu/poa.

Algorithms↗
PubMed2002

A novel approach to local reliability of sequence alignments.

MOTIVATION: The pairwise alignment of biological sequences obtained from an algorithm will in general contain both correct and incorrect parts. Hence, to allow for a valid interpretation of the alignment, the local trustworthiness of the alignment has to be quantified. RESULTS: We present a novel approach that attributes a reliability index to every pair of residues, including gapped regions, in the optimal alignment of two protein sequences. The method is based on a fuzzy recast of the dynamic programming algorithm for sequence alignment in terms of mean field annealing. An extensive evaluation with structural reference alignments not only shows that the probability for a pair of residues to be correctly aligned grows consistently with increasing reliability index, but moreover demonstrates that the value of the reliability index can directly be translated into an estimate of the probability for a correct alignment.

Algorithms↗
PubMed2002

A sequence-profile-based HMM for predicting and discriminating beta barrel membrane proteins.

MOTIVATION: Membrane proteins are an abundant and functionally relevant subset of proteins that putatively include from about 15 up to 30% of the proteome of organisms fully sequenced. These estimates are mainly computed on the basis of sequence comparison and membrane protein prediction. It is therefore urgent to develop methods capable of selecting membrane proteins especially in the case of outer membrane proteins, barely taken into consideration when proteome wide analysis is performed. This will also help protein annotation when no homologous sequence is found in the database. Outer membrane proteins solved so far at atomic resolution interact with the external membrane of bacteria with a characteristic beta barrel structure comprising different even numbers of beta strands (beta barrel membrane proteins). In this they differ from the membrane proteins of the cytoplasmic membrane endowed with alpha helix bundles (all alpha membrane proteins) and need specialised predictors. RESULTS: We develop a HMM model, which can predict the topology of beta barrel membrane proteins using, as input, evolutionary information. The model is cyclic with 6 types of states: two for the beta strand transmembrane core, one for the beta strand cap on either side of the membrane, one for the inner loop, one for the outer loop and one for the globular domain state in the middle of each loop. The development of a specific input for HMM based on multiple sequence alignment is novel. The accuracy per residue of the model is 83% when a jack knife procedure is adopted. With a model optimisation method using a dynamic programming algorithm seven topological models out of the twelve proteins included in the testing set are also correctly predicted. When used as a discriminator, the model is rather selective. At a fixed probability value, it retains 84% of a non-redundant set comprising 145 sequences of well-annotated outer membrane proteins. Concomitantly, it correctly rejects 90% of a set of globular proteins including about 1200 chains with low sequence identity (<30%) and 90% of a set of all alpha membrane proteins, including 188 chains.

Algorithms↗
PubMed2003

A generalized global alignment algorithm.

MOTIVATION: Homologous sequences are sometimes similar over some regions but different over other regions. Homologous sequences have a much lower global similarity if the different regions are much longer than the similar regions. RESULTS: We present a generalized global alignment algorithm for comparing sequences with intermittent similarities, an ordered list of similar regions separated by different regions. A generalized global alignment model is defined to handle sequences with intermittent similarities. A dynamic programming algorithm is designed to compute an optimal general alignment in time proportional to the product of sequence lengths and in space proportional to the sum of sequence lengths. The algorithm is implemented as a computer program named GAP3 (Global Alignment Program Version 3). The generalized global alignment model is validated by experimental results produced with GAP3 on both DNA and protein sequences. The GAP3 program extends the ability of standard global alignment programs to recognize homologous sequences of lower similarity. AVAILABILITY: The GAP3 program is freely available for academic use at http://bioinformatics.iastate.edu/aat/align/align.html.

Algorithms↗
PubMed1988

Profile scanning for three-dimensional structural patterns in protein sequences.

Profile analysis measures the similarity between a target sequence and a group of aligned sequences (the probe). The probe sequences are used to produce a position-specific scoring table (the profile) that can be aligned with any sequence (the target) using standard dynamic programming methods. We are developing a library of profiles, each describing a different structural motif. This allows any target sequence to be rapidly scanned for the presence of structural motifs. Levels of significance for the comparison of target sequences with the profile are determined in advance, permitting an objective decision to be made as to whether a protein is likely to possess a structural motif.

Amino Acid Sequence↗
PubMed1989

RNA secondary structures: comparison and determination of frequently recurring substructures by consensus.

A method for assessing the preserved stem-loops of RNA secondary structures is presented. Frequently recurring helical stems in a set of secondary structures resulting from the simulated folding process of a given RNA are assessed and consensus structural motifs can then be selected to construct a secondary structure of the RNA. Alternatively, it can be applied to a series of 'optimal' and 'suboptimal' secondary structures computed using the dynamic program developed by Williams and Tinoco. To demonstrate the power and the usefulness of the program we give examples of this procedure.

Algorithms↗
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↗