Bayesian networks of data from a cohort study:
Stand by for inferred Bayesian networks concerning the relationship between early respiratory infections and childhood asthma pathogenesis.
Biological subtypes of asthma from exclusive predictors:
A variable predictive of a only a given subtype will be weakly predictive of the more general case. The corresponding Areas Under the Curve are related in a way determined by the fraction of cases belonging to the subtype, allowing the definition of an index which indicates whether the predictive power of the variable is exclusive to the subtype in question. Details to come...
Biochemical Property Prediction:
BioPPsy is a package to predict clinically relevant properties of small molecules from those molecules from which such properties are already known. It works by training the chosen model with a given set of molecules and then using the trained model to predict the desired property, typically membrane permeability, to molecules for which this is unknown. When I took over this project it only had linear models available and was not yet on a public repository. Apart from some debugging and improving its structure in places, I have since added Partial Linear Squares, Neural Networks and Support Vector Regression (these last two by implementing the weka package). Just as importantly, this has been done in such a way that anyone can code their own algorithm and simply add it to the project. BioPPsy may be downloaded from my sourceforge repository.
Studying and modelling the dynamics of the plant hormone auxin and its molecular transporter PIN:
The distribution of auxin is at the heart of plant morphogenesis, but how do plant cells "decide" to locate their PIN transporters. Our approach was based on the so-called "flux-based" model, in which the expression of PIN in a cell wall is proportional to the flow of auxin passing through it. We were able to show that this single model produces both diffused and canalised distributions as they are distributed in the floral meristem with implementing a change in model or model parameters.