Biological data can be very complex and we are using various machine learning strategies to mine the data for novel insights into how cells work.

Examples include: 1) Predicting function by integrating various protein sequence features. 2) Predicting protein homology from sequence alignments. 3) Predicting the phenotypic effect of disease mutations. 4) Convolutional neural networks for various imaging datasets