scholarly journals Multiple Sequence Comparison and Consistency on Multipartite Graphs

1995 ◽  
Vol 16 (1) ◽  
pp. 1-22 ◽  
Author(s):  
M. Vingron ◽  
P.A. Pevzner
Keyword(s):  
Sequence Comparison ◽  
Multiple Sequence ◽  
Multipartite Graphs

A survey of multiple sequence comparison methods

1992 ◽  
Vol 54 (4) ◽  
pp. 563-598 ◽  
Author(s):  
S. C. Chan ◽  
A. K. C. Wong ◽  
D. K. Y. Chiu
Keyword(s):  
Sequence Comparison ◽  
Multiple Sequence ◽  
Comparison Methods

[27] Multiple sequence comparison

1990 ◽  
pp. 438-447 ◽  
Author(s):  
David J. Bacon ◽  
Wayne F. Anderson
Keyword(s):  
Sequence Comparison ◽  
Multiple Sequence

A multiple sequence comparison method

1993 ◽  
Vol 55 (2) ◽  
pp. 465-486 ◽  
Author(s):  
A WONG ◽  
S CHAN ◽  
D CHIU
Keyword(s):  
Sequence Comparison ◽  
Comparison Method ◽  
Multiple Sequence

MULTICOMP: a program package for multiple sequence comparison

1992 ◽  
Vol 8 (1) ◽  
pp. 35-38 ◽  
Author(s):  
Mauno Vihinen ◽  
Antti Euranto ◽  
Petri Luostarinen ◽  
Olli Nevalainen
Keyword(s):  
Sequence Comparison ◽  
Program Package ◽  
Multiple Sequence

A survey of multiple sequence comparison methods

1992 ◽  
Vol 54 (4) ◽  
pp. 563-598 ◽  
Author(s):  
S CHAN ◽  
A WONG ◽  
D CHIU
Keyword(s):  
Sequence Comparison ◽  
Multiple Sequence ◽  
Comparison Methods

scholarly journals Global atlas tree of natural proteins based on sorted composition vectors

2019 ◽  
Author(s):  
Pu Tian
Keyword(s):  
Computational Complexity ◽  
Sequence Comparison ◽  
Computational Cost ◽  
Comparison Method ◽  
Sequencing Data ◽  
Multiple Sequence ◽  
Sequence Composition ◽  
Complex Interactions ◽  
Classification Tasks ◽  
Protein Sequence Comparison

AbstractSequence comparison is the cornerstone of bioinformatics and is traditionally realized by alignment. Unfortunately, exponential computational complexity renders rigorous multiple sequence alignment (MSA) intractable. Approximate algorithms and heuristics provide acceptable performance for relatively small number of sequences but engender prohibitive computational cost and unbounded accumulation of error for massive sequence sets. Alignment free algorithms achieved linear computational cost for sequence pair comparison but the challenge for multiple sequence comparison (MSC) remains. Meanwhile, various number of parameters and procedures need to be empirically adjusted for different MSC tasks with their complex interactions and impact not well understood. Therefore, development of efficient and nonparametric global sequence comparison method is essential for explosive sequencing data. It is shown here that sorted composition vector (SCV), which is based on a physical perspective on sequence composition constraint, is a feasible non-parametric encoding scheme for global protein sequence comparison and classification with linear computational complexity, and provides a global atlas tree for natural protein sequences. This finding renders massive sequence comparison and classification, which is infeasible on supercomputers, routine on a workstation. SCV sets an example of one-way encoding that might revolutionize recognition and classification tasks in general.

scholarly journals ‘Multi-SpaM’: a maximum-likelihood approach to phylogeny reconstruction using multiple spaced-word matches and quartet trees

2019 ◽  
Vol 2 (1) ◽  
Author(s):  
Thomas Dencker ◽  
Chris-André Leimeister ◽  
Michael Gerth ◽  
Christoph Bleidorn ◽  
Sagi Snir ◽  
...  
Keyword(s):  
Maximum Likelihood ◽  
Sequence Comparison ◽  
Phylogeny Reconstruction ◽  
Neighbor Joining ◽  
Tree Reconstruction ◽  
High Quality ◽  
Multiple Sequence ◽  
Maximum Likelihood Approach ◽  
Alignment Free ◽  
Likelihood Approach

Abstract Word-based or ‘alignment-free’ methods for phylogeny inference have become popular in recent years. These methods are much faster than traditional, alignment-based approaches, but they are generally less accurate. Most alignment-free methods calculate ‘pairwise’ distances between nucleic-acid or protein sequences; these distance values can then be used as input for tree-reconstruction programs such as neighbor-joining. In this paper, we propose the first word-based phylogeny approach that is based on ‘multiple’ sequence comparison and ‘maximum likelihood’. Our algorithm first samples small, gap-free alignments involving four taxa each. For each of these alignments, it then calculates a quartet tree and, finally, the program ‘Quartet MaxCut’ is used to infer a super tree for the full set of input taxa from the calculated quartet trees. Experimental results show that trees produced with our approach are of high quality.

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