In machine learning and data mining, most of the works in classification problems deal with
flat classification, where each instance is classified in one of a set of possible classes and …

The literature on protein function prediction is currently dominated by works aimed at
maximizing predictive accuracy, ignoring the important issues of validation and …

Motivation: S. cerevisiae is one of the most important model organisms, and has has been
the focus of over a century of study. In spite of these efforts, 40% of its open reading frames …

Proteins are the most essential and versatile macromolecules of life, and the knowledge of
their functions is a crucial link in the development of new drugs, better crops, and even the …

Motivation: Computational assignment of protein function may be the single most vital
application of bioinformatics in the post-genome era. These assignments are made based …

Background Integration of heterogeneous data types is a challenging problem, especially in
biology, where the number of databases and data types increase rapidly. Amongst the …

Protein function prediction is one of the most challenging problems in the post-genomic era.
The number of newly identified proteins has been exponentially increasing with the …

Protein function prediction, ie classification of proteins according to their biological function,
is an important task in bioinformatics. In this chapter, we illustrate that the presence of …

Abstract The Gene Ontology (GO) offers a comprehensive and standardized way to describe
a protein's biological role. Proteins are annotated with GO terms based on direct or indirect …

Abstract Motivation: The genome of Arabidopsis thaliana, which has the best understood
plant genome, still has approximately one-third of its genes with no functional annotation at …