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 …

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 …

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 …

The transformation of normal cells into cancer cells and maintenance of the malignant state
and phenotypes are associated with genetic and epigenetic deregulations, altered cellular …

Cancer is a heterogeneous disease, originating in different tissues and involving a number
of distinct molecular pathways. With the growing availability of high-throughput biological …

Mechanistic models are essential to deepen the understanding of complex diseases at the
molecular level. Nowadays, high-throughput molecular and phenotypic characterizations …

The future of cancer treatment lies in personalized strategies designed to specifically target
tumorigenic cell populations present in an individual. Although recent advances in directed …

The response of cancer cells to drugs is determined by various factors, including the cells'
mutations and gene expression levels. These factors can be assessed using next …

We provide an overview on the use of biological assays to calibrate and initialize
mechanism-based models of cancer phenomena. Although artificial intelligence methods …

A significant challenge in the field of biomedicine is the development of methods to integrate
the multitude of dispersed data sets into comprehensive frameworks to be used to generate …