Biological Modeling Framework Compiler
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional biological modeling practices require skilled modelers to understand both the biological system and the modeling technique, leading to dependency on technical expertise and the accumulation of artifacts that obscure the relevance of model components to the biological system being modeled.
Innovation Solution
A computer-implemented framework that decouples technical skill from scientific understanding by using a compiler to convert biological data into a format suitable for selected modeling techniques, automatically generating models without requiring additional technical parameters, thereby minimizing artifacts unrelated to the biological system.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional biological modeling practices are used where modelers translate biological systems into technical forms dictated by chosen modeling techniques, then the model can simulate biological system behavior, but the model requires advanced technical knowledge and accumulates artifacts that obscure relevance to the biological system
Solution Approach 1:
The patent introduces a compiler as an intermediary component that translates biological data into modeling technique-specific configurations. This compiler acts as a mediator between the biological system representation and the simulation engine, automatically handling the translation process and eliminating the need for modelers to manually create technical artifacts, thus reducing model complexity while maintaining simulation accuracy
Solution Approach 2:
The system enables self-service by allowing biological data to automatically generate appropriate model configurations through the compiler. The biological data itself contains sufficient information to drive the modeling process without requiring external technical expertise to interpret or transform the data, making the system self-sufficient in generating accurate simulations
2Adaptability or versatility
If modelers manually translate biological systems into modeling technique formats, then the model can be customized for different techniques, but the process depends on modeler technical expertise and time
Solution Approach 1:
The compiler is designed with multi-functionality to support multiple modeling techniques (e.g., ODEs, PDEs, Boolean networks, Monte Carlo simulations). A single compiler instance can automatically adapt biological data to various modeling techniques by selecting appropriate configuration templates, providing versatility without requiring separate manual translation processes for each technique
Solution Approach 2:
The system performs preliminary action by pre-compiling biological data into multiple modeling technique formats in advance. The compiler can generate configurations for different modeling techniques before simulation is actually needed, so when a user wants to run a simulation, the appropriate model configuration is already prepared, eliminating time-consuming manual translation at the moment of use
3Ease of operation
If modeling constructs accumulate artifacts to overcome technical barriers, then the model can function within the chosen technique, but the relevance of model components to the biological system becomes unclear
Solution Approach 1:
The patent replaces the manual mechanical process of model construction with an automated computational compiler. Instead of modelers manually creating artifacts to overcome technical barriers, the compiler automatically generates appropriate model configurations based on the biological data and selected modeling technique, eliminating unnecessary artifacts while preserving essential biological relationships
Solution Approach 2:
The compiler extracts only the essential biological information needed for simulation from the complete biological data set. By selectively extracting relevant parameters and relationships required by the chosen modeling technique, the system removes extraneous artifacts and intermediate constructs that do not contribute to the simulation accuracy, thereby preserving the relevance of model components to the biological system
Data Source
AI summary
Methods, systems, and apparatuses, including computer programs encoded on a computer storage medium, can be implemented to perform certain actions. The actions can include maintaining biological data related to multiple biological systems in a first format in a data repository, receiving a first selection of a biological system of the multiple biological systems for constructing a model that simulates a behavior of the biological system, retrieving a subset of data of the biological data that is associated with the first selection of the biological system, receiving a second selection of a modeling technique of the multiple modeling techniques for constructing the model, compiling the subset of biological data into configuration data of a second format that is specific to the modeling technique and that is different from the first format, and generating the model using the modeling technique and the configuration data.