We solicit contributions on classification issues in biostatistics and bioinformatics with particular emphasis on high-dimensional “omics” data from high-throughput experiments. This includes prediction models (supervised learning) with applications to biomedicine, e.g. “gene signatures”, for instance using ensemble methods, penalized regression methods or dimension reduction techniques. Other topics of interest are regularization network inference, change-points problems and mixtures models, preparation/normalization of biological data and quite generally statistical validation issues that are crucial in many fields including life sciences.

• Prediction models/signatures
• Data preparation/normalization
• Ensemble methods
• Dimension reduction
• Statistical validation issue
• Mixture models
• Change-point problems
• Regulation network inference