Transcriptional regulation is a fundamental molecular mechanism involved in almost every
aspect of life, from homeostasis to development, from metabolism to behavior, from reaction …

The increasing power of computer technology does not dispense with the need to extract
meaningful information out of data sets of ever growing size, and indeed typically …

Inference of gene regulatory network from expression data is a challenging task. Many
methods have been developed to this purpose but a comprehensive evaluation that covers …

An important problem in bioinformatics is the inference of gene regulatory networks (GRNs)
from expression profiles. In general, the main limitations faced by GRN inference methods …

Unraveling transcriptional regulatory networks is essential for understanding and predicting
cellular responses in different developmental and environmental contexts. Information …

Thanks to recent advances in molecular biology, allied to an ever increasing amount of
experimental data, the functional state of thousands of genes can now be extracted …

Background The inference of gene regulatory networks (GRNs) from large-scale expression
profiles is one of the most challenging problems of Systems Biology nowadays. Many …

Background Gene regulatory networks (GRN) inference is an important bioinformatics
problem in which the gene interactions need to be deduced from gene expression data …

Finding a minimal subset of objects that correctly classify the training set for the nearest
neighbors classifier has been an active research area in Pattern Recognition and Machine …

Gene regulatory networks (GRN) inference is an important bioinformatics problem in which
the gene interactions need to be deduced from gene expression data, such as microarray …