Exploring the druggable space around the Fanconi anemia pathway using machine learning and mechanistic models.
Journal:
BMC bioinformatics
Published Date:
Jul 2, 2019
Abstract
BACKGROUND: In spite of the abundance of genomic data, predictive models that describe phenotypes as a function of gene expression or mutations are difficult to obtain because they are affected by the curse of dimensionality, given the disbalance between samples and candidate genes. And this is especially dramatic in scenarios in which the availability of samples is difficult, such as the case of rare diseases.