Computational modeling and analysis of biomolecular network models annotated with
cancer patient-specific multi-omics data can enable the development of personalized …

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 …

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 …

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

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

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 …

If mathematical modeling is to be used effectively in cancer drug development, future models
must take into account both the mechanistic details of cellular signal transduction networks …

Background High throughput technologies have been used to profile genes in multiple
different dimensions, such as genetic variation, copy number, gene and protein expression …

With multiple omics strategies being applied to several cancer genomics projects,
researchers have the opportunity to develop a rational planning of targeted cancer therapy …

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 …