Using multi-objective artificial immune systems to find core collections based on molecular markers

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

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 contribution

AN - SCOPUS:84963706195

SN - 9781450334723

SP - 1271

EP - 1278

BT - GECCO 2015 - Proceedings of the 2015 Genetic and Evolutionary Computation Conference

PB - ACM

T2 - 16th Genetic and Evolutionary Computation Conference, GECCO 2015

Y2 - 11 July 2015 through 15 July 2015

ER -