Simultaneous learning of instantaneous and time-delayed genetic interactions using novel information theoretic scoring technique.
BACKGROUND
Understanding gene interactions is a fundamental question in systems biology. Currently, modeling of gene regulations using the Bayesian Network (BN) formalism assumes that genes interact either instantaneously or with a certain amount of time delay. However in reality, biological regulations, both instantaneous and time-delayed, occur simultaneously. A framework that can detect and model both these two types of interactions simultaneously would represent gene regulatory networks more accurately.


RESULTS
In this paper, we introduce a framework based on the Bayesian Network (BN) formalism that can represent both instantaneous and time-delayed interactions between genes simultaneously. A novel scoring metric having firm mathematical underpinnings is also proposed that, unlike other recent methods, can score both interactions concurrently and takes into account the reality that multiple regulators can regulate a gene jointly, rather than in an isolated pair-wise manner. Further, a gene regulatory network (GRN) inference method employing an evolutionary search that makes use of the framework and the scoring metric is also presented.


CONCLUSIONS
By taking into consideration the biological fact that both instantaneous and time-delayed regulations can occur among genes, our approach models gene interactions with greater accuracy. The proposed framework is efficient and can be used to infer gene networks having multiple orders of instantaneous and time-delayed regulations simultaneously. Experiments are carried out using three different synthetic networks (with three different mechanisms for generating synthetic data) as well as real life networks of Saccharomyces cerevisiae, E. coli and cyanobacteria gene expression data. The results show the effectiveness of our approach.
Gippsland School of Information Technology, Faculty of Information Technology, Monash University, VIC 3842, Northways Road, Australia. nizamul.morshed@monash.edu
Nizamul
N
Morshed
Madhu
M
Chetty
Xuan Vinh
XV
Nguyen
D001499:Bayes Theorem; D000458:Cyanobacteria / Q000235:genetics; D004260:DNA Repair / Q000235:genetics; D004926:Escherichia coli / Q000235:genetics; D005786:Gene Expression Regulation; D053263:Gene Regulatory Networks; D005947:Glucose / Q000378:metabolism; D006706:Homeostasis / Q000235:genetics; D012441:Saccharomyces cerevisiae / Q000235:genetics / Q000378:metabolism; D020839:Son of Sevenless Protein, Drosophila / Q000378:metabolism; D049490:Systems Biology / Q000379:methods*; D013997:Time Factors
D020839:Son of Sevenless Protein, Drosophila; D005947:Glucose