The complexity of cellular gene, protein, and metabolite networks can hinder attempts to
elucidate their structure and function. To address this problem, we used systematic …

Inferring, or ‘reverse‐engineering’, gene networks can be defined as the process of
identifying gene interactions from experimental data through computational analysis. Gene …

We describe an innovative experimental and computational approach to control the expression
of a protein in a population of yeast cells. We designed a simple control algorithm to …

The lysosomal–autophagic pathway is activated by starvation and plays an important role in
both cellular clearance and lipid catabolism. However, the transcriptional regulation of this …

This study describes comprehensive polling of transcription start and termination sites and
analysis of previously unidentified full-length complementary DNAs derived from the mouse …

A bottleneck in drug discovery is the identification of the molecular targets of a compound (mode
of action, MoA) and of its off-target effects. Previous approaches to elucidate drug MoA …

Motivation: Time series expression experiments are an increasingly popular method for
studying a wide range of biological systems. Here we developed an algorithm that can infer the …

A major challenge in drug discovery is to distinguish the molecular targets of a bioactive
compound from the hundreds to thousands of additional gene products that respond indirectly to …

Systems biology approaches are extensively used to model and reverse engineer gene
regulatory networks from experimental data. Conversely, synthetic biology allows "de novo" …

Phosphoinositides (PtdIns) control fundamental cell processes, and inherited defects of PtdIns
kinases or phosphatases cause severe human diseases, including Lowe syndrome due …