This paper addresses the problem of network reconstruction from data. Previous work
identified necessary and sufficient conditions for network reconstruction of LTI systems …

DNA copy number aberrations (CNAs) are a hallmark of cancer genomes. However, little is
known about how such changes affect global gene expression. We develop a modeling …

The performance of genome-wide gene regulatory network inference algorithms depends
on the sample size. It is generally considered that the larger the sample size, the better the …

A key question in network inference, that has not been properly answered, is what accuracy
can be expected for a given biological dataset and inference method. We present …

Statistical regularisation methods such as LASSO and related L1 regularised regression
methods are commonly used to construct models of gene regulatory networks. Although they …

Gene regulatory network inference (that is, determination of the regulatory interactions
between a set of genes) provides mechanistic insights of central importance to research in …

A common problem in inference of gene regulatory networks from experimental response
data is the relatively small number of samples available in relation to the number of …

Motivated by biological applications, this paper addresses the problem of network
reconstruction from data. Previous work has shown necessary and sufficient conditions for …

Recently, simplified graphical modeling approaches based on low-order conditional (in-)
dependence calculations have received attention because of their potential to model gene …

Background To infer gene regulatory networks from time series gene profiles, two important
tasks that are related to biological systems must be undertaken. One task is to determine a …