Predicting the best treatment strategy from genomic information is a core goal of precision
medicine. Here we focus on predicting drug response based on a cohort of genomic, …

Availability of large-scale experimental data for cell biology is enabling computational methods
to systematically model the behaviour of cellular networks. This review surveys the recent …

SynergyFinder ( https://synergyfinder.fimm.fi ) is a stand-alone web-application for interactive
analysis and visualization of drug combination screening data. Since its first release in 2017…

Rational design of multi-targeted drug combinations is a promising strategy to tackle the drug
resistance problem for many complex disorders. A drug combination is usually classified …

We developed a systematic algorithmic solution for quantitative drug sensitivity scoring (DSS),
based on continuous modeling and integration of multiple dose-response relationships in …

Rational design of drug combinations has become a promising strategy to tackle the drug
sensitivity and resistance problem in cancer treatment. To systematically evaluate the pre-…

High-throughput biotechnologies, such as gene expression microarrays or mass-spectrometry-based
proteomic assays, suffer from frequent missing values due to various experimental …

SynergyFinder ( https://synergyfinder.fimm.fi ) is a free web-application for interactive analysis
and visualization of multi-drug combination response data. Since its first release in 2017, …

We present an individualized systems medicine (ISM) approach to optimize cancer drug
therapies one patient at a time. ISM is based on (i) molecular profiling and ex vivo drug …

A number of supervised machine learning models have recently been introduced for the
prediction of drug–target interactions based on chemical structure and genomic sequence …