Background With the rapid accumulation of biological datasets, machine learning methods
designed to automate data analysis are urgently needed. In recent years, so-called topic …

Gene function annotations are key elements in biology and bioinformatics. A typical
annotation is the association between a gene and a feature term that describes a functional …

Topic modeling continues to grow as a popular technique for finding hidden patterns, as well
as grou** collections of new types of text and non-text data. Recent years have witnessed …

Consistency and completeness of biomolecular annotations is a keypoint of correct
interpretation of biological experiments. Yet, the associations between genes (or proteins) …

One limitation of most existing probabilistic latent topic models for document classification is
that the topic model itself does not consider useful side-information, namely, class labels of …

Background Knowledge of gene and protein functions is paramount for the understanding of
physiological and pathological biological processes, as well as in the development of new …

Background All biological processes are inherently dynamic. Biological systems evolve
transiently or sustainably according to sequential time points after perturbation by …

This paper presents an approach to extract biclusters from expression micro array data
using topic models-a class of probabilistic models which allow to detect interpretable groups …

Genomic annotations describing functional features of genes and proteins through
controlled terminologies and ontologies are extremely valuable, especially for computational …

Topic models have recently shown to be really useful tools for the analysis of microarray
experiments. In particular they have been successfully applied to gene clustering and, very …