Artificial intelligence (AI), and, in particular, deep learning as a subcategory of AI, provides
opportunities for the discovery and development of innovative drugs. Various machine …

The motor system comprises a network of cortical and subcortical areas interacting via
excitatory and inhibitory circuits, thereby governing motor behaviour. The balance within the …

To enable arrayed or pooled loss-of-function screens in a wide range of mammalian cell
types, including primary and nondividing cells, we are develo** lentiviral short hairpin …

Noise permeates biology on all levels, from the most basic molecular, sub-cellular
processes to the dynamics of tissues, organs, organisms and populations. The functional …

Cellular phenotypes are determined by the differential activity of networks linking
coregulated genes. Available methods for the reverse engineering of such networks from …

Motivation: Network inference algorithms are powerful computational tools for identifying
putative causal interactions among variables from observational data. Bayesian network …

Motivation: Bayesian networks have been applied to infer genetic regulatory interactions
from microarray gene expression data. This inference problem is particularly hard in that …

In this review we give an overview of computational and statistical methods to reconstruct
cellular networks. Although this area of research is vast and fast develo**, we show that …

Background The development of algorithms to infer the structure of gene regulatory
networks based on expression data is an important subject in bioinformatics research …

Abstract Dynamic Bayesian networks (DBNs) are considered as a promising model for
inferring gene networks from time series microarray data. DBNs have overtaken Bayesian …