Optimus

Optimus performs stochastic optimization of model parameters using acceptance-ratio simulated annealing and replica exchange to enable parameter estimation and configurational space exploration in biological models.

Key Features:

• Flexible Integration: Integrates with a wide range of modeling initiatives from simple to complex systems.
• Acceptance Ratio Simulated Annealing: Explores solution spaces by probabilistically accepting solutions based on a calculated acceptance ratio.
• Acceptance Ratio Replica Exchange: Implements parallel tempering to enhance simulated annealing and facilitate escape from local minima to explore global optima.
• Adaptive Thermoregulation: Dynamically adjusts pseudo-temperatures during optimization to balance exploration and exploitation without fixed temperature schedules.
• Monte Carlo Optimization Process: Uses an unconstrained adaptive approach to pseudo-temperature regulation while maintaining a constrained acceptance frequency to improve robustness and efficiency in complex landscapes.

Scientific Applications:

• Parameter estimation for biological models: Applied to estimate parameters in biological modeling frameworks.
• Data fitting in genomics and proteomics: Used for data fitting and analysis in genomics and proteomics datasets.
• Systems biology optimization: Addresses optimization problems in systems biology that require extensive configurational space exploration.

Methodology:

Optimization uses acceptance-ratio simulated annealing, acceptance-ratio replica exchange (parallel tempering), adaptive thermoregulation of pseudo-temperatures, and a Monte Carlo optimization process with unconstrained adaptive pseudo-temperature regulation and constrained acceptance frequency.