BioJazz

BioJazz enables in silico evolution and design of dynamic biochemical reaction networks to study how structural and dynamic features of cellular networks emerge through evolutionary processes.

Key Features:

• In silico evolution: Performs evolutionary simulations of dynamic biochemical reaction networks.
• Rule-based modeling: Represents biochemical interactions and reaction mechanisms using rule-based modeling.
• Genome-like encoding: Encodes network structures with a genome-like representation for exploration of architectural variation.
• Unbounded complexity: Supports simulations with unbounded model complexity by combining rule-based modeling and genome-like encoding.
• Selective pressures: Implements biologically realistic selective pressures within evolutionary simulations.
• Network space exploration: Enables exploration of the space of possible network architectures and dynamics.
• Evolutionary insight: Provides analysis of intermediary evolutionary steps and potential general design principles underlying network dynamics.
• Function-directed evolution: Simulates evolutionary processes that can lead to specified physiological functions.
• Complex reaction dynamics: Simulates complex biochemical reaction dynamics under realistic selective conditions.

Scientific Applications:

• Study of network evolution: Investigates how structural and dynamic features of cellular networks emerge through evolution.
• Deciphering cellular networks: Analyzes intermediary states and mechanisms to interpret existing cellular biochemical networks.
• Design of synthetic networks: Supports engineering of novel biochemical reaction network architectures informed by evolutionary trajectories.
• Derivation of design principles: Identifies general design principles that govern network dynamics and function.
• Simulation of functional emergence: Models evolutionary routes leading to specific physiological functions.

Methodology:

Combines rule-based modeling, a genome-like encoding for network structures, and in silico evolutionary simulations with biologically realistic selective pressures.