Elements of information theory
Elements of information theory
ACM Computing Surveys (CSUR)
A new approach to analyzing gene expression time series data
Proceedings of the sixth annual international conference on Computational biology
Biclustering Algorithms for Biological Data Analysis: A Survey
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Analyzing time series gene expression data
Bioinformatics
Algorithmic algebraic model checking i: challenges from systems biology
CAV'05 Proceedings of the 17th international conference on Computer Aided Verification
Decidable Compositions of O-Minimal Automata
ATVA '08 Proceedings of the 6th International Symposium on Automated Technology for Verification and Analysis
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Biotechnological innovations which sample gene expressions allow to measure the gene expression levels of a biological system with varying degree of accuracy, cost and speed. By repeating the measurement steps at different sampling rates, one can both infer relations among the genes and define a dynamic model of the underlying biological system. When a very large number of genes and measurements are involved, they raise several difficult algorithmic questions, as accurate model-building, checking and inference tasks. Semi-algebraic hybrid automata were proposed as a modeling formalism for biological systems (see, e.g., [17,6]), and demonstrated their abilities to handle complex biochemical pathways. This paper proposes an automatic procedure to build semi-algebraic hybrid automata from gene-expression profiles. In order to reduce the size of the resulting automata and to minimize their analysis computational complexity, our approach exploits various dimensionality reduction techniques. The paper concludes with several experimental results about peach fruit.