A general method applicable to the search for similarities in the amino acid sequence of two proteins

Needleman, Saul B.; Wunsch, Christian D.

doi:10.1016/0022-2836(70)90057-4

Cited by 9,460 publications

(3,618 citation statements)

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“…[47]. The intervening segments are aligned using NeedlemanWunsch algorithm [39] (B) The PB sequence identities calculated from pairwise alignments, are used to generate a distance matrix (C) A guide tree is obtained from the distance matrix using the Neighbour Joining algorithm [49] (D) The guide tree determines the progressive manner of alignment of PB sequences (E) The residue equivalences from the multiple PB sequence alignment is translated into a 3D fit using ProFit [53]. given, the average length is indicated within parentheses.…”

Section: Resultsmentioning

confidence: 99%

“…The pairwise alignments are obtained using iPBA which performs an anchor based alignment by finding structurally conserved regions, identified as local alignments [41,42]. A combination of local [47] and global [39] dynamic programming algorithms is used for the alignment. A set of local alignments (anchors) associated with these two sequences is derived using a modified version of SIM algorithm [42,47].…”

Section: Pairwise Alignmentsmentioning

confidence: 99%

“…The structures were translated into PB sequences followed by the alignment of the PB sequences. Classical Needleman-Wunsch dynamic programming [39] was used and a dedicated PB substitution matrix was generated for scoring the alignment [40]. Significant improvement in the alignment quality could be achieved with the use of an anchor-based dynamic programming algorithm.…”

Section: Introductionmentioning

confidence: 99%

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Progressive structure-based alignment of homologous proteins: Adopting sequence comparison strategies

2012

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Comparison of multiple protein structures has a broad range of applications in the analysis of protein structure, function and evolution. Multiple structure alignment tools (MSTAs) are necessary to obtain a simultaneous comparison of a family of related folds. In this study, we have developed a method for multiple structure comparison largely based on sequence alignment techniques. A widely used Structural Alphabet named Protein Blocks (PBs) was used to transform the information on 3D protein backbone conformation as a 1D sequence string.A progressive alignment strategy similar to CLUSTALW was adopted for multiple PB sequence alignment (mulPBA). Highly similar stretches identified by the pairwise alignments are given higher weights during the alignment. The residue equivalences from PB based alignments are used to obtain a three dimensional fit of the structures followed by an iterative refinement of the structural superposition.Systematic comparisons using benchmark datasets of MSTAs underlines that the alignment quality is better than MULTIPROT, MUSTANG and the alignments in HOMSTRAD, in more than 85% of the cases. Comparison with other rigid-body and flexible MSTAs also indicate that mulPBA alignments are superior to most of the rigid-body MSTAs and highly comparable to the flexible alignment methods.3

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Section: Resultsmentioning

confidence: 99%

Section: Pairwise Alignmentsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Progressive structure-based alignment of homologous proteins: Adopting sequence comparison strategies

2012

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“…Therefore, usually for the purpose of homology detection, the biologist is interested in finding if there are any biologically relevant targets sharing important structural and functional characteristics, which are common to the two sequences. Thus, pairwise local alignment [63] is more commonly used for this purpose which finds highly similar regions between two sequences, rather than global alignment [45] which are optimized along the whole length of the two sequences. Local pairwise sequence alignment methods align two sequences using a substitution matrix consisting of pairwise scores of aligning different residues with each other (like BLOSUM62), and give an alignment score for the given sequence-pair.…”

Section: Nature Of the Problemmentioning

confidence: 99%

Sequence-Specific Sequence Comparison Using Pairwise Statistical Significance

Huang

Agrawal

2011

Advances in Experimental Medicine and Biology

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“…Most existing alignment methods are inspired by the dynamic programming approach [1,2] which attempts to examine all possible pairings of the two sequences and chooses the highest matching score alignment. This dynamic programming alignment approach has quadratic time and space complexities and hence is unattractive for handling long sequences and high volume sequence databases.…”

Section: Introductionmentioning

confidence: 99%

A genome alignment algorithm based on compression

2010

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BackgroundTraditional genome alignment methods consider sequence alignment as a variation of the string edit distance problem, and perform alignment by matching characters of the two sequences. They are often computationally expensive and unable to deal with low information regions. Furthermore, they lack a well-principled objective function to measure the performance of sets of parameters. Since genomic sequences carry genetic information, this article proposes that the information content of each nucleotide in a position should be considered in sequence alignment. An information-theoretic approach for pairwise genome local alignment, namely XMAligner, is presented. Instead of comparing sequences at the character level, XMAligner considers a pair of nucleotides from two sequences to be related if their mutual information in context is significant. The information content of nucleotides in sequences is measured by a lossless compression technique.ResultsExperiments on both simulated data and real data show that XMAligner is superior to conventional methods especially on distantly related sequences and statistically biased data. XMAligner can align sequences of eukaryote genome size with only a modest hardware requirement. Importantly, the method has an objective function which can obviate the need to choose parameter values for high quality alignment. The alignment results from XMAligner can be integrated into a visualisation tool for viewing purpose.ConclusionsThe information-theoretic approach for sequence alignment is shown to overcome the mentioned problems of conventional character matching alignment methods. The article shows that, as genomic sequences are meant to carry information, considering the information content of nucleotides is helpful for genomic sequence alignment.AvailabilityDownloadable binaries, documentation and data can be found at ftp://ftp.infotech.monash.edu.au/software/DNAcompress-XM/XMAligner/.

show abstract

A general method applicable to the search for similarities in the amino acid sequence of two proteins

Cited by 9,460 publications

References 7 publications

Progressive structure-based alignment of homologous proteins: Adopting sequence comparison strategies

Progressive structure-based alignment of homologous proteins: Adopting sequence comparison strategies

Sequence-Specific Sequence Comparison Using Pairwise Statistical Significance

A genome alignment algorithm based on compression

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