UsefulLinks
Biology
General Biology
Modeling in Biology
1. Introduction to Biological Modeling
2. Types of Biological Models
3. Mathematical Foundations for Modeling
4. Modeling Paradigms and Techniques
5. Applications Across Biological Scales
6. Model Implementation, Analysis, and Validation
7. Advanced and Emerging Topics
6.
Model Implementation, Analysis, and Validation
6.1.
Computational Tools
6.1.1.
Programming Languages
6.1.1.1.
Python
6.1.1.1.1.
SciPy
6.1.1.1.2.
NumPy
6.1.1.1.3.
Matplotlib
6.1.1.1.4.
Pandas
6.1.1.1.5.
SymPy
6.1.1.2.
R
6.1.1.2.1.
deSolve
6.1.1.2.2.
EpiModel
6.1.1.2.3.
ggplot2
6.1.1.3.
MATLAB
6.1.1.3.1.
Simulink
6.1.1.3.2.
Bioinformatics Toolbox
6.1.1.4.
Julia
6.1.1.4.1.
DifferentialEquations.jl
6.1.1.4.2.
Plots.jl
6.1.2.
Specialized Modeling Software
6.1.2.1.
VCell
6.1.2.2.
COPASI
6.1.2.3.
NetLogo
6.1.2.4.
COMSOL Multiphysics
6.1.2.5.
CellDesigner
6.1.2.6.
SBML Tools
6.2.
Model Analysis Techniques
6.2.1.
Parameter Estimation
6.2.1.1.
Fitting Models to Data
6.2.1.2.
Maximum Likelihood Estimation
6.2.1.3.
Least Squares Methods
6.2.1.4.
Identifiability Analysis
6.2.1.5.
Optimization Methods
6.2.2.
Sensitivity Analysis
6.2.2.1.
Local Sensitivity Analysis
6.2.2.2.
Global Sensitivity Analysis
6.2.2.3.
Morris Method
6.2.2.4.
Sobol Indices
6.2.3.
Bifurcation Analysis
6.2.3.1.
Identifying Critical Thresholds
6.2.3.2.
Tipping Points in System Behavior
6.2.3.3.
Continuation Methods
6.2.4.
Stability Analysis
6.2.4.1.
Linear Stability Analysis
6.2.4.2.
Lyapunov Functions
6.2.4.3.
Basin of Attraction
6.3.
Model Validation and Verification
6.3.1.
Verification of Code and Algorithms
6.3.1.1.
Debugging and Testing
6.3.1.2.
Reproducibility Checks
6.3.1.3.
Code Documentation
6.3.2.
Validation Against Experimental Data
6.3.2.1.
Data Comparison
6.3.2.2.
Model Calibration
6.3.2.3.
Goodness of Fit Measures
6.3.3.
Assessing Predictive Accuracy
6.3.3.1.
Cross-Validation
6.3.3.2.
Out-of-Sample Testing
6.3.3.3.
Prediction Intervals
6.3.4.
Model Comparison
6.3.4.1.
Information Criteria
6.3.4.2.
Likelihood Ratio Tests
6.3.4.3.
Bayesian Model Selection
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7. Advanced and Emerging Topics