Literature DB >> 9475984

A genetic algorithm for multiple molecular sequence alignment.

C Zhang1, A K Wong.   

Abstract

MOTIVATION: Multiple molecular sequence alignment is among the most important and most challenging tasks in computational biology. The currently used alignment techniques are characterized by great computational complexity, which prevents their wider use. This research is aimed at developing a new technique for efficient multiple sequence alignment. APPROACH: The new method is based on genetic algorithms. Genetic algorithms are stochastic approaches for efficient and robust searching. By converting biomolecular sequence alignment into a problem of searching for optimal or near-optimal points in an 'alignment space', a genetic algorithm can be used to find good alignments very efficiently.
RESULTS: Experiments on real data sets have shown that the average computing time of this technique may be two or three orders lower than that of a technique based on pairwise dynamic programming, while the alignment qualities are very similar. AVAILABILITY: A C program on UNIX has been written to implement the technique. It is available on request from the authors.

Entities:  

Mesh:

Substances:

Year:  1997        PMID: 9475984     DOI: 10.1093/bioinformatics/13.6.565

Source DB:  PubMed          Journal:  Comput Appl Biosci        ISSN: 0266-7061


  8 in total

1.  Analysis of DNA microarrays using algorithms that employ rule-based expert knowledge.

Authors:  Kuang-Hung Pan; Chih-Jian Lih; Stanley N Cohen
Journal:  Proc Natl Acad Sci U S A       Date:  2002-02-19       Impact factor: 11.205

2.  Comparative protein structure modeling by iterative alignment, model building and model assessment.

Authors:  Bino John; Andrej Sali
Journal:  Nucleic Acids Res       Date:  2003-07-15       Impact factor: 16.971

3.  Using the miraEST assembler for reliable and automated mRNA transcript assembly and SNP detection in sequenced ESTs.

Authors:  Bastien Chevreux; Thomas Pfisterer; Bernd Drescher; Albert J Driesel; Werner E G Müller; Thomas Wetter; Sándor Suhai
Journal:  Genome Res       Date:  2004-05-12       Impact factor: 9.043

4.  A prediction model based on an artificial intelligence system for moderate to severe obstructive sleep apnea.

Authors:  Lei Ming Sun; Hung-Wen Chiu; Chih Yuan Chuang; Li Liu
Journal:  Sleep Breath       Date:  2010-07-04       Impact factor: 2.816

5.  Assessing Activity Pattern Similarity with Multidimensional Sequence Alignment based on a Multiobjective Optimization Evolutionary Algorithm.

Authors:  Mei-Po Kwan; Ningchuan Xiao; Guoxiang Ding
Journal:  Geogr Anal       Date:  2015-07

6.  Vertical decomposition with Genetic Algorithm for Multiple Sequence Alignment.

Authors:  Farhana Naznin; Ruhul Sarker; Daryl Essam
Journal:  BMC Bioinformatics       Date:  2011-08-25       Impact factor: 3.169

Review 7.  [Artificial intelligence empowers laboratory medicine in Industry 4.0].

Authors:  Quan Zhou; Suwen Qi; Bin Xiao; Qiaoliang Li; Zhaohui Sun; Linhai Li
Journal:  Nan Fang Yi Ke Da Xue Xue Bao       Date:  2020-02-29

8.  An enhanced algorithm for multiple sequence alignment of protein sequences using genetic algorithm.

Authors:  Manish Kumar
Journal:  EXCLI J       Date:  2015-12-15       Impact factor: 4.068

  8 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.