Communicating sequential processes
Communicating sequential processes
CCS—and its relationship to net theory
Advances in Petri nets 1986, part II on Petri nets: applications and relationships to other models of concurrency
Genetic programming: on the programming of computers by means of natural selection
Genetic programming: on the programming of computers by means of natural selection
Logic-based genetic programming with definite clause translation grammars
New Generation Computing
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Communication and Concurrency
Programming in PROLOG
Membrane Computing: An Introduction
Membrane Computing: An Introduction
Evolutionary modeling and inference of gene network
Information Sciences—Informatics and Computer Science: An International Journal - Bioinformatics-selected papers from 4th CBGI & 6th JCIS Proceedings
Feature-based classification of time-series data
Information processing and technology
Genetic Programming IV: Routine Human-Competitive Machine Intelligence
Genetic Programming IV: Routine Human-Competitive Machine Intelligence
BioAmbients: an abstraction for biological compartments
Theoretical Computer Science - Special issue: Computational systems biology
Evolving petri nets to represent metabolic pathways
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
Evolution of mathematical models of chaotic systems based on multiobjective genetic programming
Knowledge and Information Systems
Proceedings of the 8th annual conference on Genetic and evolutionary computation
Characteristic-Based Clustering for Time Series Data
Data Mining and Knowledge Discovery
Computational Modeling of Genetic and Biochemical Networks (Computational Molecular Biology)
Computational Modeling of Genetic and Biochemical Networks (Computational Molecular Biology)
Computational Methods of Feature Selection (Chapman & Hall/Crc Data Mining and Knowledge Discovery Series)
Evolutionary Algorithms for Solving Multi-Objective Problems (Genetic and Evolutionary Computation)
Evolutionary Algorithms for Solving Multi-Objective Problems (Genetic and Evolutionary Computation)
Learning regulation functions of metabolic systems by artificial neural networks
Proceedings of the 11th Annual conference on Genetic and evolutionary computation
Evolving stochastic processes using feature tests and genetic programming
Proceedings of the 11th Annual conference on Genetic and evolutionary computation
Using genetic programming to synthesize monotonic stochastic processes
CI '07 Proceedings of the Third IASTED International Conference on Computational Intelligence
An automated translation from a narrative language for biological modelling into process algebra
CMSB'07 Proceedings of the 2007 international conference on Computational methods in systems biology
The BlenX language: a tutorial
SFM'08 Proceedings of the Formal methods for the design of computer, communication, and software systems 8th international conference on Formal methods for computational systems biology
Petri nets for modelling metabolic pathways: a survey
Natural Computing: an international journal
Evolving noisy oscillatory dynamics in genetic regulatory networks
EuroGP'06 Proceedings of the 9th European conference on Genetic Programming
P systems, a new computational modelling tool for systems biology
Transactions on Computational Systems Biology VI
A compositional approach to the stochastic dynamics of gene networks
Transactions on Computational Systems Biology IV
IEEE Transactions on Signal Processing - Part II
Evolutionary optimization in uncertain environments-a survey
IEEE Transactions on Evolutionary Computation
Rule-based modelling of cellular signalling
CONCUR'07 Proceedings of the 18th international conference on Concurrency Theory
Proceedings of the 15th annual conference on Genetic and evolutionary computation
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Computational tools for analyzing biochemical phenomena are becoming increasingly important. Recently, high-level formal languages for modeling and simulating biochemical reactions have been proposed. These languages make the formal modeling of complex reactions accessible to domain specialists outside of theoretical computer science. This research explores the use of genetic programming to automate the construction of models written in one such language. Given a description of desired time-course data, the goal is for genetic programming to construct a model that might generate the data. The language investigated is Kahramanoğullari's and Cardelli's Programming Interface for Modeling (PIM) language. The PIM syntax is defined in a grammar-guided genetic programming system. All time series generated during simulations are described by statistical feature tests, and the fitness evaluation compares feature proximity between the target and candidate solutions. PIM models of varying complexity were used as target expressions for genetic programming, and were successfully reconstructed in all cases. This shows that the compositional nature of PIM models is amenable to genetic program search.