Critical Assessment of Function Annotation

The Critical Assessment of Functional Annotation (CAFA) is an experiment designed to provide a large-scale assessment of computational methods dedicated to predicting protein function. Different algorithms are evaluated by their ability to predict the Gene Ontology (GO) terms in the categories of Molecular Function, Biological Process, and Cellular Component. The Critical Assessment of Functional Annotation (CAFA) is an experiment designed to provide a large-scale assessment of computational methods dedicated to predicting protein function. Different algorithms are evaluated by their ability to predict the Gene Ontology (GO) terms in the categories of Molecular Function, Biological Process, and Cellular Component. The experiment consists of two tracks: (i) the eukaryotic track, (ii) the prokaryotic track. In each track, a set of targets is provided by the organizers. Participants are expected to submit their predictions by the submission deadline, after which they are assessed according to a set of specific metrics. The genome of an organism may consist of hundreds to tens of thousands of genes, which encode for hundreds of thousands of different protein sequences. Due to the relatively low cost of genome sequencing, determining gene and protein sequences is fast and inexpensive. Thousands of species have been sequenced so far, yet many of the proteins are not well characterized. The process of experimentally determining the role of a protein in the cell, is an expensive and time consuming task. Further, even when functional assays are performed they are unlikely to provide complete insight into protein function. Therefore it has become important to use computational tools in order to functionally annotate proteins. There are several computational methods of protein function prediction that can infer protein function using a variety of biological and evolutionary data, but there is significant room for improvement. Accurate prediction of protein function can have longstanding implications on biomedical and pharmaceutical research.