Multi-scale models integrating biomolecular data from genetic, transcriptional, and
translational levels, coupled with extracellular microenvironments can assist in decoding the …

Rapid advancements in high-throughput omics technologies and experimental protocols
have led to the generation of vast amounts of biomolecular data on cancer that now …

Rapid advancements in high-throughput omics technologies and experimental protocols
have led to the generation of vast amounts of scale-specific biomolecular data on cancer …

Cancer research in the field of Computational Systems Biology attempts to address
questions that will advance current knowledge in the mechanisms of cancer progression or …

Computational methods that simulate tumors mathematically to describe cellular and
molecular interactions are emerging as promising tools to simulate the impact of therapy …

Despite a growing body of knowledge on the mechanisms underlying the onset and
progression of cancer, treatment success rates in oncology are at best modest. Current …

Precision medicine has changed thinking in cancer therapy, highlighting a better
understanding of the individual clinical interventions. But what role do the drivers and …

Recent progress in our understanding of cancer mostly relies on the systematic profiling of
patient samples with high-throughput techniques like transcriptomics. With this approach …

Abstract Systems biology combines computational modeling with quantitative experimental
measurements to study complex biological processes. Here, we outline an approach for …

Background Cancer is a complex, multiscale dynamical system, with interactions between
tumor cells and non-cancerous host systems. Therapies act on this combined cancer-host …