Search for: multiple-sequences
Article Bioinformatics ; Volume 36, Issue 12 , 15 June , 2020 , Pages 3662-3668 ; Parvinnia, E ; Sharifi Zarchi, A ; Sharif University of Technology
Oxford University Press 2020
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...
Article Journal of Knowledge and Health in Basic Medical Sciences ; Volume 16, Issue 1 , 2021 , Pages 13-20 ; 1735577X (ISSN) ; Parvinnia, E ; Sharifi Zarchi, A ; Sharif University of Technology
Shahroud University of Medical Sciences 2021
Introduction: The study of life and the detection of gene functions is an important issue in biological science. Multiple sequences alignment methods measure the similarity of DNA sequences. Nonetheless, when the size of genome sequences is increased, we encounter with the lack of memory and increasing the run time. Therefore, a fast method with a suitable accuracy for genome alignment has a significant impact on the analysis of long sequences. Methods: We introduce a new method in which, it first divides each sequence into short sequences. Then, it uses evolutionary algorithms to align the sequences. Results: The proposed method has been evaluated in seven datasets with different number of...
M.Sc. Thesis Sharif University of Technology ; Abolhassani, Hassan
Protein multiple sequence alignment is one of important problems in biology which no polynomial time algorithms is known for it yet. Due to importance of this problem, several methods have been developed to find an approximate solution for it. Approximation algorithms, Evolutionary algorithms and Probabilistic methods are some of these methods. According to evolutionary nature of this problem, evolutionary algorithms and specifically genetic algorithms can be a potential good solution method for this problem. In this project we have a survey on using genetic algorithms for this problem and after mentioning benefits and draw backs of existing methods, we develop a method for improving one of...
Article 2019 Iran Workshop on Communication and Information Theory, IWCIT 2019, 24 April 2019 through 25 April 2019 ; 2019 ; 9781728105840 (ISBN) ; Maddah Ali, M. A ; Motahari, S. A ; Sharif University of Technology
Institute of Electrical and Electronics Engineers Inc 2019
DNA sequencing has faced a huge demand since it was first introduced as a service to the public. This service is often offloaded to the sequencing companies who will have access to full knowledge of individuals' sequences, a major violation of privacy. To address this challenge, we propose a solution, which is based on separating the process of reading the fragments of sequences, which is done at a sequencing machine, and assembling the reads, which is done at a trusted local data collector. To confuse the sequencer, in a pooled sequencing scenario, in which multiple sequences are going to be sequenced simultaneously, for each target individual, we add fragments of one non-target individual,...
Article International Journal of Computational Intelligence and Applications ; Volume 11, Issue 4 , December , 2012 ; 14690268 (ISSN) ; Beigy, H ; Abolhassani, H ; Sharif University of Technology
Multiple sequence alignment (MSA) is one of the basic and important problems in molecular biology. MSA can be used for different purposes including finding the conserved motifs and structurally important regions in protein sequences and determine evolutionary distance between sequences. Aligning several sequences cannot be done in polynomial time and therefore heuristic methods such as genetic algorithms can be used to find approximate solutions of MSA problems. Several algorithms based on genetic algorithms have been developed for this problem in recent years. Most of these algorithms use very complicated, problem specific and time consuming mutation operators. In this paper, we propose a...