Abstract The Ras-Raf-MEK-ERK signal transduction cascade is arguably the most important
oncogenic pathway in human cancers. Ras-GTP promotes the formation of active …

Predicting the effects of one or more mutations to the in vivo or in vitro properties of a wild-
type protein is a major computational challenge, due to the presence of epistasis, that is, of …

Statistical analysis of evolutionary-related protein sequences provides information about
their structure, function, and history. We show that Restricted Boltzmann Machines (RBM) …

Dysregulation and mutations of protein kinases play causal roles in many diseases
including cancer. The KLIFS (kinase–ligand interaction fingerprint and structure) catalog …

Computational models starting from large ensembles of evolutionarily related protein
sequences capture a representation of protein families and learn constraints associated to …

Potts models and variational autoencoders (VAEs) have recently gained popularity as
generative protein sequence models (GPSMs) to explore fitness landscapes and predict …

Single-point mutations in kinase proteins can affect their stability and fitness, and
computational analysis of these effects can provide insights into the relationships among …

The development of drug resistance in HIV is the result of primary mutations whose effects
on viral fitness depend on the entire genetic background, a phenomenon called 'epistasis' …

We introduce a model of amino acid sequence evolution that accounts for the statistical
behavior of real sequences induced by epistatic interactions. We base the model dynamics …

Potts statistical models have become a popular and promising way to analyze mutational
covariation in protein multiple sequence alignments (MSAs) in order to understand protein …