Environmental inventory and the distribution of inorganic nutrients in a tropical estuary of the south-west coast of India

Dissolved nutrients (PO sub(4)-P, NO sub(3)-N, NO sub(2)-N and SiO sub(4)-Si) estimated in the surface and bottom waters of five selected stations of the Paravur Lake, Kerala, India, during February 1987 to January 1988 revealed distinct seasonal variations. Rainfall and land drainage play significant roles in the nutrient economy, particularly NO sub(3)-N and SiO sub(4)-Si, of this water body. Abnormally high values of PO sub(4)-P indicated extremely polluted condition at the wetting zone of the lake during the premonsoon season. SiO sub(4)-Si showed significant negative relationship with salinity.

Nonparametric Bayesian sparse factor models with application to gene expression modeling

A nonparametric Bayesian extension of Factor Analysis (FA) is proposed where observed data $\mathbf{Y}$ is modeled as a linear superposition, $\mathbf{G}$, of a potentially infinite number of hidden factors, $\mathbf{X}$. The Indian Buffet Process (IBP) is used as a prior on $\mathbf{G}$ to incorporate sparsity and to allow the number of latent features to be inferred. The model's utility for modeling gene expression data is investigated using randomly generated data sets based on a known sparse connectivity matrix for E. Coli, and on three biological data sets of increasing complexity.