Welcome to B2-Bayesian for Biology, a collaborative organization dedicated to studying and implementing Bayesian methods for modeling biological systems. Our primary focus is on Ordinary Differential Equation (ODE) based models, though we aim to explore other types of models in the future.
- Effective Use of Bayesian Methods: Investigate how Bayesian methods can be effectively applied to model biological systems.
- Exploration of Priors: Study the effects of different prior distributions on model outcomes.
- Error Models: Understand the role and impact of various error models in Bayesian analysis.
- Time Series Analysis: Analyze time series data within the Bayesian framework to derive meaningful biological insights.
B2-Bayesian for Biology is an international multi-university venture, led by scientists from:
- The University of Tennessee, Knoxville (UTK), USA.
- The University of Maryland (UMD), USA.
- Banyuls-sur-Mer, France.
- Future you 🧙
We are open to contributions from researchers, students, and professionals across the globe. Whether you are a seasoned Bayesian statistician or a beginner interested in learning more about this fascinating field, your input and participation are welcome.
Our organization embraces a multi-language approach, utilizing the strengths of different programming languages to achieve our research goals. Currently, our projects incorporate:
- Python
- Julia
- MATLAB
Currently this is managed by Raunak Dey (rdey@umd.edu). Feel free to reach out to me with questions, comments and suggestions. This project is led by Prof. David Talmy (U.T.K.)
