TY - GEN
T1 - Towards a partitioning of the input space of Boolean networks
T2 - 1st International Conference on Complex Sciences: Theory and Applications, Complex 2009
AU - Emmert-Streib, Frank
AU - Dehmer, Matthias
PY - 2009
Y1 - 2009
N2 - In this paper we present an algorithm that allows to select the input variables of Boolean networks from incomplete data. More precisely, sets of input variables, instead of single variables, are evaluated using mutual information to find the combination that maximizes the mutual information of input and output variables. To account for the incompleteness of the data bootstrap aggregation is used to find a stable solution that is numerically demonstrated to be superior in many cases to the solution found by using the complete data set all at once.
AB - In this paper we present an algorithm that allows to select the input variables of Boolean networks from incomplete data. More precisely, sets of input variables, instead of single variables, are evaluated using mutual information to find the combination that maximizes the mutual information of input and output variables. To account for the incompleteness of the data bootstrap aggregation is used to find a stable solution that is numerically demonstrated to be superior in many cases to the solution found by using the complete data set all at once.
KW - Boolean networks
KW - Bootstrap aggregation
KW - Causality
KW - Mutual Information
UR - http://www.scopus.com/inward/record.url?scp=84885887482&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-02466-5_69
DO - 10.1007/978-3-642-02466-5_69
M3 - Conference contribution
AN - SCOPUS:84885887482
SN - 3642024653
SN - 9783642024658
VL - 4 LNICST
T3 - Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering
SP - 715
EP - 723
BT - Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering
Y2 - 23 February 2009 through 25 February 2009
ER -