5 citations · 5 across the 1 of their papers we have counts for
4 papers
Extracting useful information about reversible evolutionary processes from irreversible evolutionary accumulation models
Iain G. Johnston
Evolutionary accumulation models (EvAMs) are an emerging class of machine learning methods designed to infer the evolutionary pathways by which features are acquired. Applications…
An Algebraic Approach to Evolutionary Accumulation Models
Jessica Renz, Frederik Witt, Iain G. Johnston
We present an algebraic approach to evolutionary accumulation modelling (EvAM). EvAM is concerned with learning and predicting the order in which evolutionary features accumulate o…
Flexible inference of evolutionary accumulation dynamics using uncertain observational data
Jessica Renz, Morten Brun, Iain G. Johnston
Understanding and predicting evolutionary accumulation pathways is a key objective in many fields of research, ranging from classical evolutionary biology to diverse applications i…
Evolutionary accumulation modelling in AMR: machine learning to infer and predict evolutionary dynamics of multi-drug resistance
Jessica Renz, Kazeem A. Dauda, Olav N. L. Aga +4
Can we understand and predict the evolutionary pathways by which bacteria acquire multi-drug resistance (MDR)? These questions have substantial potential impact in basic biology an…