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At least 109 records · Page 6Linked to original sources
PubMed1993

Mix'n'Match: an improved multiple sequence alignment procedure for distantly related proteins using secondary structure predictions, designed to be independent of the choice of gap penalty and scoring matrix.

A new multiple sequence alignment procedure is presented. Several different multiple alignments are made using differing criteria. Having divided the sequences into strongly conserved regions (SCRs) and loosely conserved regions (LCRs), the 'best' alignment for each LCR is chosen, independently of the other LCRs, from a selection of possibilities in the multiple alignments. To help make this choice for each LCR, the secondary structure is predicted and shown alongside each different possible alignment. One advantage of this method over automatic, non-interactive methods, is that the final alignment is not dependent on the choice of a single set of scoring parameters. Another is that, by allowing interactive choice and by taking account of secondary structural information, the final alignment is based more on biological rather than mathematical factors. This method can produce better alignments than any of the initial automatic multiple alignment methods used.

Amino Acid Sequence↗
PubMed2004

ABC: software for interactive browsing of genomic multiple sequence alignment data.

BACKGROUND: Alignment and comparison of related genome sequences is a powerful method to identify regions likely to contain functional elements. Such analyses are data intensive, requiring the inclusion of genomic multiple sequence alignments, sequence annotations, and scores describing regional attributes of columns in the alignment. Visualization and browsing of results can be difficult, and there are currently limited software options for performing this task. RESULTS: The Application for Browsing Constraints (ABC) is interactive Java software for intuitive and efficient exploration of multiple sequence alignments and data typically associated with alignments. It is used to move quickly from a summary view of the entire alignment via arbitrary levels of resolution to individual alignment columns. It allows for the simultaneous display of quantitative data, (e.g., sequence similarity or evolutionary rates) and annotation data (e.g. the locations of genes, repeats, and constrained elements). It can be used to facilitate basic comparative sequence tasks, such as export of data in plain-text formats, visualization of phylogenetic trees, and generation of alignment summary graphics. CONCLUSIONS: The ABC is a lightweight, stand-alone, and flexible graphical user interface for browsing genomic multiple sequence alignments of specific loci, up to hundreds of kilobases or a few megabases in length. It is coded in Java for cross-platform use and the program and source code are freely available under the General Public License. Documentation and a sample data set are also available http://mendel.stanford.edu/sidowlab/downloads.html.

Animals↗
PubMed2005

PRALINE: a multiple sequence alignment toolbox that integrates homology-extended and secondary structure information.

PRofile ALIgNEment (PRALINE) is a fully customizable multiple sequence alignment application. In addition to a number of available alignment strategies, PRALINE can integrate information from database homology searches to generate a homology-extended multiple alignment. PRALINE also provides a choice of seven different secondary structure prediction programs that can be used individually or in combination as a consensus for integrating structural information into the alignment process. The program can be used through two separate interfaces: one has been designed to cater to more advanced needs of researchers in the field, and the other for standard construction of high confidence alignments. The web-based output is designed to facilitate the comprehensive visualization of the generated alignments by means of five default colour schemes based on: residue type, position conservation, position reliability, residue hydrophobicity and secondary structure, depending on the options set. A user can also define a custom colour scheme by selecting which colour will represent one or more amino acids in the alignment. All generated alignments are also made available in the PDF format for easy figure generation for publications. The grouping of sequences, on which the alignment is based, can also be visualized as a dendrogram. PRALINE is available at http://ibivu.cs.vu.nl/programs/pralinewww/.

Computer Graphics↗
PubMed2004

Multiple sequence alignment with user-defined constraints at GOBICS.

Most multi-alignment methods are fully automated, i.e. they are based on a fixed set of mathematical rules. For various reasons, such methods may fail to produce biologically meaningful alignments. Herein, we describe a semi-automatic approach to multiple sequence alignment where biological expert knowledge can be used to influence the alignment procedure. The user can specify parts of the sequences that are biologically related to each other; our software program uses these sites as anchor points and creates a multiple alignment respecting these user-defined constraints. By using known functionally, structurally or evolutionarily related positions of the input sequences as anchor points, our method can produce alignments that reflect the true biological relationships among the input sequences more accurately than fully automated procedures can do.

Algorithms↗
PubMed2005

Improvement in the accuracy of multiple sequence alignment program MAFFT.

In 2002, we developed and released a rapid multiple sequence alignment program MAFFT that was designed to handle a huge (up to approximately 5,000 sequences) and long data (approximately 2,000 aa or approximately 5,000 nt) in a reasonable time on a standard desktop PC. As for the accuracy, however, the previous versions (v.4 and lower) of MAFFT were outperformed by ProbCons and TCoffee v.2, both of which were released in 2004, in several benchmark tests. Here we report a recent extension of MAFFT that aims to improve the accuracy with as little cost of calculation time as possible. The extended version of MAFFT (v.5) has new iterative refinement options, G-INS-i and L-INS-i (collectively denoted as [GL]-INS-i in this report). These options use a new objective function combining the weighted sum-of-pairs (WSP) score and a score similar to COFFEE derived from all pairwise alignments. We discuss the improvement in accuracy brought by this extension, mainly using two benchmark tests released very recently, BAliBASE v.3 (for protein alignments) and BRAliBASE (for RNA alignments). According to BAliBASE v.3, the overall average accuracy of L-INS-i was higher than those of other methods successively released in 2004, although the difference among the most accurate methods (ProbCons, TCoffee v.2 and new options of MAFFT) was small. The advantage in accuracy of [GL]-INS-i became greater for the alignments consisting of approximately 50-100 sequences. By utilizing this feature of MAFFT, we also examined another possible approach to improve the accuracy by incorporating homolog information collected from database. The [GL]-INS-i options are applicable to aligning up to approximately 200 sequences, although not applicable to thousands of sequences because of time and space complexities.

Amino Acid Sequence↗
PubMed2002

Multiple sequence alignment with arbitrary gap costs: computing an optimal solution using polyhedral combinatorics.

Multiple sequence alignment is one of the dominant problems in computational molecular biology. Numerous scoring functions and methods have been proposed, most of which result in NP-hard problems. In this paper we propose for the first time a general formulation for multiple alignment with arbitrary gap-costs based on an integer linear program (ILP). In addition we describe a branch-and-cut algorithm to effectively solve the ILP to optimality. We evaluate the performances of our approach in terms of running time and quality of the alignments using the BAliBase database of reference alignments. The results show that our implementation ranks amongst the best programs developed so far.

Algorithms↗
PubMed2005

MSAID: multiple sequence alignment based on a measure of information discrepancy.

We propose an algorithm of global multiple sequence alignment that is based on a measure of what we call information discrepancy. The algorithm follows a progressive alignment iteration strategy that makes use of what we call a function of degree of disagreement (FDOD). MSAID begins with distance calculation of pairwise sequences, based on FDOD as a numerical scoring measure. In the next step, the resulting distance matrix is used to construct a guide tree via the neighbor-joining method. The tree is then used to produce a multiple alignment. Current alignment is next used to produce a new matrix and a new tree (with FDOD scoring measure again). This iterative process continues until convergence criteria (or a stopping rule) are satisfied. MSAID was tested and compared with other prior methods by using reference alignments from BAliBASE 2.01. For the alignments with no large N/C-terminal extensions or internal insertions MSAID received the top overall average in the tests. Moreover, the results of testing indicate that MSAID performs as well as other alignment methods with an occasional tendency to perform better than these prior techniques. We, therefore, believe that MSAID is a solid and reliable method of choice, which is often (if not always) superior to other global alignment techniques.

Algorithms↗
PubMed1997

The CLUSTAL_X windows interface: flexible strategies for multiple sequence alignment aided by quality analysis tools.

CLUSTAL X is a new windows interface for the widely-used progressive multiple sequence alignment program CLUSTAL W. The new system is easy to use, providing an integrated system for performing multiple sequence and profile alignments and analysing the results. CLUSTAL X displays the sequence alignment in a window on the screen. A versatile sequence colouring scheme allows the user to highlight conserved features in the alignment. Pull-down menus provide all the options required for traditional multiple sequence and profile alignment. New features include: the ability to cut-and-paste sequences to change the order of the alignment, selection of a subset of the sequences to be realigned, and selection of a sub-range of the alignment to be realigned and inserted back into the original alignment. Alignment quality analysis can be performed and low-scoring segments or exceptional residues can be highlighted. Quality analysis and realignment of selected residue ranges provide the user with a powerful tool to improve and refine difficult alignments and to trap errors in input sequences. CLUSTAL X has been compiled on SUN Solaris, IRIX5.3 on Silicon Graphics, Digital UNIX on DECstations, Microsoft Windows (32 bit) for PCs, Linux ELF for x86 PCs, and Macintosh PowerMac.

Algorithms↗
PubMed2004

MSARI: multiple sequence alignments for statistical detection of RNA secondary structure.

We present a highly accurate method for identifying genes with conserved RNA secondary structure by searching multiple sequence alignments of a large set of candidate orthologs for correlated arrangements of reverse-complementary regions. This approach is growing increasingly feasible as the genomes of ever more organisms are sequenced. A program called msari implements this method and is significantly more accurate than existing methods in the context of automatically generated alignments, making it particularly applicable to high-throughput scans. In our tests, it discerned clustalw-generated multiple sequence alignments of signal recognition particle or RNaseP orthologs from controls with 89.1% sensitivity at 97.5% specificity and with 74.4% sensitivity with no false positives in 494 controls. We used msari to conduct a comprehensive scan for secondary structure in mRNAs of coding genes, and we found many genes with known mRNA secondary structure and compelling evidence for secondary structure in other genes. msari uses a method for coping with sequence redundancy that is likely to have applications in a large set of other comparison-based search methods. The program is available for download from http://theory.csail.mit.edu/MSARi.

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↗
PubMed2004

Influence of conservation on calculations of amino acid covariance in multiple sequence alignments.

It has long been argued that algorithms that find correlated mutations in multiple sequence alignments can be used to find structurally or functionally important residues in proteins. We examined the properties of four different methods for detecting these correlated mutations. On both simple, artificial alignments and real alignments from the Pfam database, we found a surprising lack of agreement between the four correlated mutation methods. We argue that these differences are caused in part by differing sensitivities to background conservation. Correlated mutation algorithms can be envisioned as "filters" of background conservation with each algorithm searching for correlated mutations that occur at a different background conservation frequency.

Algorithms↗
PubMed2005

Multiple sequence alignment using an exhaustive and greedy algorithm.

We describe an exhaustive and greedy algorithm for improving the accuracy of multiple sequence alignment. A simple progressive alignment approach is employed to provide initial alignments. The initial alignment is then iteratively optimized against an objective function. For any working alignment, the optimization involves three operations: insertions, deletions and shuffles of gaps. The optimization is exhaustive since the algorithm applies the above operations to all eligible positions of an alignment. It is also greedy since only the operation that gives the best improving objective score will be accepted. The algorithms have been implemented in the EGMA (Exhaustive and Greedy Multiple Alignment) package using Java programming language, and have been evaluated using the BAliBASE benchmark alignment database. Although EGMA is not guaranteed to produce globally optimized alignment, the tests indicate that EGMA is able to build alignments with high quality consistently, compared with other commonly used iterative and non-iterative alignment programs. It is also useful for refining multiple alignments obtained by other methods.

Algorithms↗
PubMedDate not supplied

Bayesian segmental models with multiple sequence alignment profiles for protein secondary structure and contact map prediction.

In this paper, we develop a segmental semi-Markov model (SSMM) for protein secondary structure prediction which incorporates multiple sequence alignment profiles with the purpose of improving the predictive performance. The segmental model is a generalization of the hidden Markov model where a hidden state generates segments of various length and secondary structure type. A novel parameterized model is proposed for the likelihood function that explicitly represents multiple sequence alignment profiles to capture the segmental conformation. Numerical results on benchmark data sets show that incorporating the profiles results in substantial improvements and the generalization performance is promising. By incorporating the information from long range interactions in beta-sheets, this model is also capable of carrying out inference on contact maps. This is an important advantage of probabilistic generative models over the traditional discriminative approach to protein secondary structure prediction. The Web server of our algorithm and supplementary materials are available at http://public.kgi.edu/-wild/bsm.html.

Algorithms↗
PubMed2006

VISSA: a program to visualize structural features from structure sequence alignment.

MOTIVATION: Multiple sequence alignment is an important tool to understand and analyze functions of homologous proteins. However, the logic of residue conservation/variation is usually apparent only in three-dimensional (3D) space, not on a primary sequence level. Thus, in a traditional multiple alignment it is often difficult to directly visualize and analyze key residues because they are masked by other residues along the alignment. Here we present an integrated multiple alignment and 3D structure visualization program that can (1) map and highlight residues from a 1D alignment onto a 3D structure and vice versa and (2) display only the alignment of preselected, key residues. This program, called Visualize Structure Sequence Alignment, also has many other built-in tools that can help analyze multiple sequence alignments. AVAILABILITY: http://bioinformatics.burnham.org/liwz/vissa CONTACT: liwz@burnham.org.

Computational Biology↗
PubMed2005

Grouping of amino acid types and extraction of amino acid properties from multiple sequence alignments using variance maximization.

Understanding of amino acid type co-occurrence in trusted multiple sequence alignments is a prerequisite for improved sequence alignment and remote homology detection algorithms. Two objective approaches were used to investigate co-occurrence, both based on variance maximization of the weighted residue frequencies in columns taken from a large alignment database. The first approach discretely grouped amino acid types, and the second approach extracted orthogonal properties of amino acids using principal components analysis. The grouping results corresponded to amino acid physical properties such as side chain hydrophobicity, size, or backbone flexibility, and an optimal arrangement of approximately eight groups was observed. However, interpretation of the orthogonal properties was more complex. Although the principal components accounting for the largest variances exhibited modest correlations with hydrophobicity and conservation of glycine, in general principal components did not correspond to physical properties of amino acids. Although not intuitive, these amino acid mathematical properties were demonstrated to be robust and to improve local pairwise alignment accuracy, relative to 20 amino acid frequencies alone, for a simple test case.

Amino Acids↗
PubMed1998

JavaShade: multiple sequence alignment box-and-shading on the World Wide Web.

RESULTS: JavaShade is a multiple sequence alignment box-and-shade tool for generating high quality printed output that uses a variety of methods for boxing and shading, allowing the most appropriate functions to be chosen for displaying the most meaningful positions in an alignment. AVAILABILITY: JavaShade is available from the WWW at http://industry.ebi.ac.uk/JavaShade

Algorithms↗
PubMed2005

Manipulating multiple sequence alignments via MaM and WebMaM.

MaM is a software tool that processes and manipulates multiple alignments of genomic sequence. MaM computes the exact location of common repeat elements, exons and unique regions within aligned genomics sequences using a variety of user identified programs, databases and/or tables. The program can extract subalignments, corresponding to these various regions of DNA to be analyzed independently or in conjunction with other elements of genomic DNA. Graphical displays further allow an assessment of sequence variation throughout these different regions of the aligned sequence, providing separate displays for their repeat, non-repeat and coding portions of genomic DNA. The program should facilitate the phylogenetic analysis and processing of different portions of genomic sequence as part of large-scale sequencing efforts. MaM source code is freely available for non-commercial use at http://compbio.cs.sfu.ca/MAM.htm; and the web interface WebMaM is hosted at http://atgc.lirmm.fr/mam.

Exons↗
PubMed2002

Constrained multiple sequence alignment tool development and its application to RNase family alignment.

In this paper, we design an algorithm of computing a constrained multiple sequence alignment (CMSA for short) for guaranteeing that the generated alignment satisfies the user-specified constraints that some particular residues should be aligned together. If the number of residues needed to be aligned together is a constant alpha, then the time-complexity of our CMSA algorithm for aligning K sequences is O (alphaKn4), where n is the maximum of the lengths of sequences. In addition, we have build up such a CMSA software system and made several experiments on the RNase sequences, which mainly function in catalyzing the degradation of RNA molecules. The resulting alignments illustrate the practicability of our method.

Algorithms↗