Cyclin-dependent kinase 4 drives cystic kidney disease in the absence of mTORC1 signaling activity.

Progression of cystic kidney disease has been linked to activation of the mTORC1 signaling pathway. Yet the utility of mTORC1 inhibitors to treat patients with polycystic kidney disease remains controversial despite promising preclinical data. To define the cell intrinsic role of mTORC1 for cyst development, the mTORC1 subunit gene Raptor was selectively inactivated in kidney tubular cells lacking cilia due to simultaneous deletion of the kinesin family member gene Kif3A.

Inferring gene expression networks with hubs using a degree weighted Lasso approach.

Motivation: Genome-scale gene networks contain regulatory genes called hubs that have many interaction partners. These genes usually play an essential role in gene regulation and cellular processes. Despite recent advancements in high-throughput technology, inferring gene networks with hub genes from high-dimensional data still remains a challenging problem.

Understanding the mTOR signaling pathway via mathematical modeling.

The mechanistic target of rapamycin (mTOR) is a central regulatory pathway that integrates a variety of environmental cues to control cellular growth and homeostasis by intricate molecular feedbacks. In spite of extensive knowledge about its components, the molecular understanding of how these function together in space and time remains poor and there is a need for Systems Biology approaches to perform systematic analyses. In this work, we review the recent progress how the combined efforts of mathematical models and quantitative experiments shed new light on our understanding of the mTOR signaling pathway.

Graph reconstruction using covariance-based methods.

Methods based on correlation and partial correlation are today employed in the reconstruction of a statistical interaction graph from high-throughput omics data. These dedicated methods work well even for the case when the number of variables exceeds the number of samples. In this study, we investigate how the graphs extracted from covariance and concentration matrix estimates are related by using Neumann series and transitive closure and through discussing concrete small examples.

Replication vesicles are load- and choke-points in the hepatitis C virus lifecycle.

Hepatitis C virus (HCV) infection develops into chronicity in 80% of all patients, characterized by persistent low-level replication. To understand how the virus establishes its tightly controlled intracellular RNA replication cycle, we developed the first detailed mathematical model of the initial dynamic phase of the intracellular HCV RNA replication. We therefore quantitatively measured viral RNA and protein translation upon synchronous delivery of viral genomes to host cells, and thoroughly validated the model using additional, independent experiments.