TY - GEN
T1 - Using multi-objective artificial immune systems to find core collections based on molecular markers
AU - Schlottfeldt, Shana
AU - Carvalho, André C.P.L.F.
AU - Walter, Maria Emilia M.T.
AU - Telles, Mariana P.C.
AU - Timmis, Jon
AU - Diniz-Filho, José Alexandre F.
N1 - Funding Information:
SS wishes to thank the University of York and Prof. Jon Timmis for the PhD stay, and the support from CNPq throughout a Science without Borders scholarship. GENPAC has been supportedbyCNPq/MCT/CAPES. WorkbyMEMTW, ACPLFC, MPCT, RDL and JAFDF have been continuously supported by productivity fellowships from CNPq. Jon Timmis is part funded by The Royal Society and The Royal Academy of Engineering.
Publisher Copyright:
© 2015 ACM.
PY - 2015/7/11
Y1 - 2015/7/11
N2 - Germplasm collections are an important strategy for conservation of diversity, a challenge in ecoinformatics. It is common to select a core to represent the genetic diversity of a germplasm collection, aiming to minimize the costs of conservation, while ensuring the maximization of genetic variation. For the problem of finding a core for a germplasm collection, we proposed the use of a constrained multi-objective artificial immune algorithm (MAIS), based on principles of systematic conservation planning (SCP), and incorporating heterozygosity information. Therefore, optimization takes genotypic diversity and variability patterns into account. As a case study, we used Dipteryx alata molecular marker information. We were able to identify within several accessions, the exact entries that should be chosen to preserve species diversity. MAIS presented better performance measure results when compared to NSGA-II. The proposed approach can be used to help construct cores with maximal genetic richness, and also be extended to in situ conservation. As far as we know, this is the first time that an AIS algorithm is applied to the problem of finding a core for a germplasm collection using heterozygosity information as well.
AB - Germplasm collections are an important strategy for conservation of diversity, a challenge in ecoinformatics. It is common to select a core to represent the genetic diversity of a germplasm collection, aiming to minimize the costs of conservation, while ensuring the maximization of genetic variation. For the problem of finding a core for a germplasm collection, we proposed the use of a constrained multi-objective artificial immune algorithm (MAIS), based on principles of systematic conservation planning (SCP), and incorporating heterozygosity information. Therefore, optimization takes genotypic diversity and variability patterns into account. As a case study, we used Dipteryx alata molecular marker information. We were able to identify within several accessions, the exact entries that should be chosen to preserve species diversity. MAIS presented better performance measure results when compared to NSGA-II. The proposed approach can be used to help construct cores with maximal genetic richness, and also be extended to in situ conservation. As far as we know, this is the first time that an AIS algorithm is applied to the problem of finding a core for a germplasm collection using heterozygosity information as well.
KW - Artificial immune systems
KW - Biodiversity
KW - Core collection
KW - Genetic variability
KW - Germplasm
KW - Multi-objective optimization
KW - Systematic conservation planning
UR - http://www.scopus.com/inward/record.url?scp=84963706195&partnerID=8YFLogxK
U2 - 10.1145/2739480.2754653
DO - 10.1145/2739480.2754653
M3 - Conference Proceeding (Non-Journal item)
AN - SCOPUS:84963706195
T3 - GECCO 2015 - Proceedings of the 2015 Genetic and Evolutionary Computation Conference
SP - 1271
EP - 1278
BT - GECCO 2015 - Proceedings of the 2015 Genetic and Evolutionary Computation Conference
A2 - Silva, Sara
PB - Association for Computing Machinery
T2 - 16th Genetic and Evolutionary Computation Conference, GECCO 2015
Y2 - 11 July 2015 through 15 July 2015
ER -