Background: Multiple sequence alignment algorithms are very important tools in molecular biology today. Accurate alignment of proteins is central to several areas such as homology modelling, docking studies, understan...
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Background: Multiple sequence alignment algorithms are very important tools in molecular biology today. Accurate alignment of proteins is central to several areas such as homology modelling, docking studies, understanding evolutionary trends and study of structure-function relationships. In recent times, improvement of existing progressing programs and implementation of new iterative algorithms have made a significant change in this field. Results: We report an alignment algorithm that combines progressive dynamic algorithm, local substructure alignment and iterative refinement to achieve an improved, user-interactive tool. Large-scale benchmarking studies show that this FMALIGN server produces alignments that, aside from preservation of functional and structural conservation, have accuracy comparable to other popular multiple alignment programs. Conclusions: The FMALIGN server allows the user to fix conserved regions in equivalent position in the alignment thereby reducing the chance of global misalignment to a great extent. FMALIGN is available at http://***/FMALIGN/***.
Background: Covariance models (CMs) are probabilistic models of RNA secondary structure, analogous to profile hidden Markov models of linear sequence. The dynamic programming algorithm for aligning a CM to an RNA sequ...
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Background: Covariance models (CMs) are probabilistic models of RNA secondary structure, analogous to profile hidden Markov models of linear sequence. The dynamic programming algorithm for aligning a CM to an RNA sequence of length N is O(N-3) in memory. This is only practical for small RNAs. Results: I describe a divide and conquer variant of the alignment algorithm that is analogous to memory-efficient Myers/Miller dynamic programming algorithms for linear sequence alignment. The new algorithm has an O(N-2 log N) memory complexity, at the expense of a small constant factor in time. Conclusions: Optimal ribosomal RNA structural alignments that previously required up to 150 GB of memory now require less than 270 MB.
An algorithm for nucleic acid and protein sequence alignment is presented. It is a non-metric local similarity minimal-difference algorithm and in the current implementation, assembles the matching regions found into ...
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An algorithm for nucleic acid and protein sequence alignment is presented. It is a non-metric local similarity minimal-difference algorithm and in the current implementation, assembles the matching regions found into a pseudo-global format. Its strengths are its speed of execution and the especially convenient presentation of its output. The algorithm is intended for use in sequence melding and local (small-region) similarity searching. It is not designed to replace a metric Needleman-Wunsch-Sellers-type similarity algorithm. The program is written in FORTRAN and is designed to be easily transportable to a variety of computer systems.
An algorithm for aligning partially denatured DNA molecules was applied to various collections of molecules, using a Hewlett Packard desk-top calculator. The algorithm consists of two stages. The first is analogous to...
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An algorithm for aligning partially denatured DNA molecules was applied to various collections of molecules, using a Hewlett Packard desk-top calculator. The algorithm consists of two stages. The first is analogous to existing methods in that molecules are incorporated in a predetermined order into a reference map. The second refines the map via iteration which terminates upon convergence, resulting in a final map. Molecule order-dependence and the effects of algorithmic parameters on computation time and reproducibility of denaturation maps were studied. Differences between reference and final maps varied, as did differences between final maps derived from various molecule orders. Iteration consistently led to increased area overlap between histograms, hence, order-independence. Histogram quality is expressed in terms of a parameter which measures the correlation of all molecules of a population with their partial denaturation map. A preferential molecule order is suggested. Application to a unique (non-permuted) population showed that molecular, statistical and experimental factors inherent to all populations are crucial for the outcome of alignments. The present algorithm negotiates these more successfully than a pairwise cross-correlation alignment procedure used before. However, if these factors are too large, resolution is impaired but not necessarily due to algorithm quality. It is concluded that the present algorithm is operationally simple, generates maps with a high degree of reproducibility, produces optimal correlation of all molecules with their partial denaturation map, is time-saving and yields improved resolution compared to other methods. It also produces reliable results as judged from marker mapping capability.
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