TY - GEN
T1 - Evolving concurrent petri net models of epistasis
AU - Mayo, Michael
AU - Beretta, Lorenzo
PY - 2010
Y1 - 2010
N2 - A genetic algorithm is used to learn a non-deterministic Petri net-based model of non-linear gene interactions, or statistical epistasis. Petri nets are computational models of concurrent processes. However, often certain global assumptions (e.g. transition priorities) are required in order to convert a non-deterministic Petri net into a simpler deterministic model for easier analysis and evaluation. We show, by converting a Petri net into a set of state trees, that it is possible to both retain Petri net non-determinism (i.e. allowing local interactions only, thereby making the model more realistic), whilst also learning useful Petri nets with practical applications. Our Petri nets produce predictions of genetic disease risk assessments derived from clinical data that match with over 92% accuracy.
AB - A genetic algorithm is used to learn a non-deterministic Petri net-based model of non-linear gene interactions, or statistical epistasis. Petri nets are computational models of concurrent processes. However, often certain global assumptions (e.g. transition priorities) are required in order to convert a non-deterministic Petri net into a simpler deterministic model for easier analysis and evaluation. We show, by converting a Petri net into a set of state trees, that it is possible to both retain Petri net non-determinism (i.e. allowing local interactions only, thereby making the model more realistic), whilst also learning useful Petri nets with practical applications. Our Petri nets produce predictions of genetic disease risk assessments derived from clinical data that match with over 92% accuracy.
KW - concurrency
KW - digital ulcers
KW - epistasis
KW - genetic algorithm
KW - Petri net
KW - systemic schlerosis
UR - http://www.scopus.com/inward/record.url?scp=77955337037&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=77955337037&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-12101-2_18
DO - 10.1007/978-3-642-12101-2_18
M3 - Conference contribution
AN - SCOPUS:77955337037
SN - 9783642121005
VL - 5991 LNAI
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 166
EP - 175
BT - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
T2 - 2010 Asian Conference on Intelligent Information and Database Systems, ACIIDS 2010
Y2 - 24 March 2010 through 26 March 2010
ER -