Enhancing the Scalability of Consistency-based Progressive Multiple Sequences Alignment Applications

2012 ◽  
Author(s):  
M. Orobitg ◽  
F. Cores ◽  
F. Guirado ◽  
C. Kemena ◽  
C. Notredame ◽  
...  
Keyword(s):  
Multiple Sequences ◽  
Sequences Alignment ◽  
Multiple Sequences Alignment

DCMOGA: a New Method for Multiple Sequences Alignment Based on the Principle Divide and Conquers and the Multi-Objective Genetic Algorithm

2016 ◽  
Vol 11 (8) ◽  
pp. 715
Author(s):  
Abdelhakim El Fatmi ◽  
Arakil Chentoufi ◽  
Molay Ali Bekri ◽  
Said Benhlima ◽  
Mohamed Sabbane
Keyword(s):  
Genetic Algorithm ◽  
New Method ◽  
Multi Objective ◽  
Multi Objective Genetic Algorithm ◽  
Multiple Sequences ◽  
Sequences Alignment ◽  
Multiple Sequences Alignment

The optimization dialectical method for the multiple sequences alignment problem

2018 ◽  
pp. 251-263
Author(s):  
Rodrigo Gomes de Souza ◽  
Wellington Pinheiro dos Santos ◽  
Manoel Eusebio de Lima
Keyword(s):  
Dialectical Method ◽  
Alignment Problem ◽  
Multiple Sequences ◽  
Sequences Alignment ◽  
Multiple Sequences Alignment

FAME: fast and memory efficient multiple sequences alignment tool through compatible chain of roots

2020 ◽  
Vol 36 (12) ◽  
pp. 3662-3668
Author(s):  
Etminan Naznooshsadat ◽  
Parvinnia Elham ◽  
Sharifi-Zarchi Ali
Keyword(s):  
Genome Size ◽  
Supplementary Information ◽  
Multiple Sequence ◽  
Multiple Alignments ◽  
Alignment Tool ◽  
Multiple Sequences ◽  
Sequences Alignment ◽  
Multiple Sequences Alignment ◽  
Combinatorial Methods ◽  
Memory Efficient

Abstract Motivation Multiple sequence alignment (MSA) is important and challenging problem of computational biology. Most of the existing methods can only provide a short length multiple alignments in an acceptable time. Nevertheless, when the researchers confront the genome size in the multiple alignments, the process has required a huge processing space/time. Accordingly, using the method that can align genome size rapidly and precisely has a great effect, especially on the analysis of the very long alignments. Herein, we have proposed an efficient method, called FAME, which vertically divides sequences from the places that they have common areas; then they are arranged in consecutive order. Then these common areas are shifted and placed under each other, and the subsequences between them are aligned using any existing MSA tool. Results The results demonstrate that the combination of FAME and the MSA methods and deploying minimizer are capable to be executed on personal computer and finely align long length sequences with much higher sum-of-pair (SP) score compared to the standalone MSA tools. As we select genomic datasets with longer length, the SP score of the combinatorial methods is gradually improved. The calculated computational complexity of methods supports the results in a way that combining FAME and the MSA tools leads to at least four times faster execution on the datasets. Availability and implementation The source code and all datasets and run-parameters are accessible free on http://github.com/naznoosh/msa. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals GENOTIPE DAN SUBTIPE VIRUS HEPATITIS B PENDERITA YANG TERINFEKSI KRONIK AKTIF

2018 ◽  
Vol 20 (2) ◽  
pp. 111
Author(s):  
Gondo Mastutik ◽  
Juniastuti Juniastuti ◽  
Ali Rohman ◽  
Mochamad Amin ◽  
Poernomo Boedi Setiawan
Keyword(s):  
Hepatitis B ◽  
Chronic Active Hepatitis ◽  
Group Method ◽  
Amino Acid Residues ◽  
Hbv Genotypes ◽  
Pair Group ◽  
B Virus ◽  
Multiple Sequences ◽  
Sequences Alignment ◽  
Multiple Sequences Alignment

Chronic activivity of Hepatitis B Virus (HBV) infection can lead to liver cirrhosis or hepatocellular carcinoma. The objective of thisstudy was to know by analyzing the distribution of HBV genotypes and subtypes from hepatitis B patients suffering from chronic activehepatitis B infection in Surabaya. The HBV genotypes were determined by comparing the S gene sequences to those kept in the GeneBank. The phylogenetic tree was constructed by means of the unweighted-pair group method using arithmetic averages. Furthermore,the subtypes were deduced based on the prediction of amino acid residues 116 to 183 of HBsAg on multiple sequences alignment withClustalW2. This study involved 20 sera obtained from patients suffering chronic active hepatitis B infection. After PCR and sequencing,it was found that 13 samples could be used for sequence analysis. The results showed that all sequences were clustered into HBV genotypeB. The subtype adw2 was identified from 12 of 13 sequences, whereas one (1) belonged to ayw1. The subtype adw2 is most prevalent inIndonesia, namely in the islands of Sumatra, Java, South Kalimantan, Bali, Lombok, Ternate, and Morotai, while ayw1 is found in theislands of Nusa Tenggara and Moluccas. Based on this study, it was found that the patients with HBV subtype adw2 were from Surabaya, whereas with ayw1 was from Nusa Tenggara. It can be concluded that the HBV infected patients with chronic active hepatitis B inSurabaya have the genotype B with subtype adw2 which was originally from Surabaya, whereas, ayw1 was a patient originally fromNusa Tenggara.

A genetic algorithm on multiple sequences alignment problems in biology

2002 ◽  
Vol 7 (2) ◽  
pp. 139-144
Author(s):  
Shi Feng ◽  
Huang Jing ◽  
Mo Zhong-xi ◽  
Zheng Hui-rao
Keyword(s):  
Genetic Algorithm ◽  
Multiple Sequences ◽  
Sequences Alignment ◽  
Multiple Sequences Alignment

An Intelligent System for Multiple Sequences Alignment

2006 ◽  
Author(s):  
Zne-Jung Lee ◽  
Chou-Yuan Lee ◽  
Huei-Lung Yu ◽  
Kuan-Hung Liu ◽  
Shun-Feng Su
Keyword(s):  
Intelligent System ◽  
Multiple Sequences ◽  
Sequences Alignment ◽  
Multiple Sequences Alignment
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