TY  - INPR
ID  - SisLab2892
UR  - https://eprints.uet.vnu.edu.vn/eprints/id/eprint/2892/
A1  - Vu Thi Ngoc, Anh
A1  - Thai Dinh, Phuc
A1  - Nguyen, Hoang Duc
A1  - Dang, Thanh Hai
A1  - Do Duc, Dong
Y1  - 2017///
N2  - Reconstruction of founder (ancestor) genes for a given population is an important problem in evolutionary biology. It involves finding a set of genes that can combine together to form genes of all individuals in that population. Such reconstruction can be modeled as a combinatorial optimization problem, in which we have to find a set of founder (gene) sequences so that the individuals in a given population can be generated by the smallest number of recombination on these founder sequences. In this paper we propose a novel ant colony optimization algorithm (ACO) based method, equipped with some important improvements, for the founder gene sequence reconstruction problem. The proposed method yields excellent performance when validating on 108 test sets from three benchmark datasets. Comparing with the best by far method for founder sequence reconstruction, our proposed method performs better in 45 test sets, equally well in 44 and worse only in 19 sets. These experimental results demonstrate the efficacy and perspective of our proposed method.
PB  - VNU Journal of Science
JF  - VNU Journal of Computer Science and Communication Engineering
SN  - 0866-8612
TI  - Ant colony optimization based founder sequence reconstruction
AV  - none
ER  -