Computational and mathematical models are key to obtain a system-level understanding of
biological processes, but their limitations have to be clearly defined to allow their proper …

Breast cancer responds variably to anticancer therapies, often leading to significant off-
target effects. This study proposes that the variability in tumour responses and drug-induced …

Cells use signaling pathways to sense and respond to their environments. The transforming
growth factor-β (TGF-β) pathway produces context-specific responses. Here, we combined …

Chemotaxis, regulated by oscillatory signals, drives critical processes in cancer metastasis.
Crucial chemoattractant molecules in breast cancer, CXCL12 and EGF, drive the activation …

Following the invention of high-throughput sequencing, cancer research focused on
investigating disease-related alterations, often inadvertently omitting tumor heterogeneity …

Modeling in systems biology: Causal understanding before prediction?: Patterns Skip to Main
Content Advertisement Patterns All content is freely available to readers and supported …

Genes are fundamental for analyzing biological systems and many recent works proposed
to utilize gene expression for various biological tasks by deep learning models. Despite their …

High dimensional characterization of drug targets, compound effects and disease
phenotypes are crucial for increased efficiency of drug discovery. High-throughput gene …

Chemotaxis drives critical processes in cancer metastasis. While commonly studied at the
population scale, metastasis arises from small numbers of cells that successfully …

Breast cancer is characterised by varied responses to different anticancer therapies, which
may provoke several different off-target effects. We hypothesise that for drugs that target cell …