5 citations · 12 across the 7 of their papers we have counts for
7 papers
A method for comparing inferred evolutionary accumulation dynamics across covariates and model structures
Jakob Fernø, Michelle B. Verstraaten, Lila Gravellier +3
In this note we describe a method for comparing inferred dynamics in evolutionary accumulation models (EvAMs). These models involve the acquisition of multiple, potentially codepen…
A structural causal framework for interventions on evolutionary accumulation models
Ramon Diaz-Uriarte, Íñigo Ríos-Arroyo, Iain G. Johnston
Evolutionary accumulation models (EvAMs), also known as cancer progression models (CPMs), infer dependencies in the order of accumulation of mutations during tumor progression from…
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…
A picture guide to cancer progression and monotonic accumulation models: evolutionary assumptions, plausible interpretations, and alternative uses
Ramon Diaz-Uriarte, Iain G. Johnston
Cancer progression and monotonic accumulation models were developed to discover dependencies in the irreversible acquisition of binary traits from cross-sectional data. They have b…