eprintid: 2892 rev_number: 9 eprint_status: archive userid: 327 dir: disk0/00/00/28/92 datestamp: 2017-12-29 08:50:38 lastmod: 2018-01-04 14:27:21 status_changed: 2017-12-29 08:50:38 type: article metadata_visibility: show creators_name: Vu Thi Ngoc, Anh creators_name: Thai Dinh, Phuc creators_name: Nguyen, Hoang Duc creators_name: Dang, Thanh Hai creators_name: Do Duc, Dong creators_id: hai.dang@vnu.edu.vn creators_id: dongdd@vnu.edu.vn title: Ant colony optimization based founder sequence reconstruction ispublished: inpress subjects: IT divisions: fac_fit abstract: 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. date: 2017 date_type: published publisher: VNU Journal of Science full_text_status: none publication: VNU Journal of Computer Science and Communication Engineering refereed: TRUE issn: 0866-8612 funders: Vietnam National University, Hanoi (VNU), under Project No. QG.15.21. citation: Vu Thi Ngoc, Anh and Thai Dinh, Phuc and Nguyen, Hoang Duc and Dang, Thanh Hai and Do Duc, Dong (2017) Ant colony optimization based founder sequence reconstruction. VNU Journal of Computer Science and Communication Engineering . ISSN 0866-8612 (In Press)