1.6k citations · 4.2k across the 72 of their papers we have counts for
13 papers · 1 filter
HyperTraPS: Inferring probabilistic patterns of trait acquisition in evolutionary and disease progression pathways
Sam F. Greenbury, Mauricio Barahona, Iain G. Johnston
The explosion of data throughout the biomedical sciences provides unprecedented opportunities to learn about the dynamics of evolution and disease progression, but harnessing these…
An edge-based formulation of elastic network models
Maxwell Hodges, Sophia N Yaliraki, Mauricio Barahona
We present an edge-based framework for the study of geometric elastic network models to model mechanical interactions in physical systems. We use a formulation in the edge space, i…
Allostery and cooperativity in multimeric proteins: bond-to-bond propensities in ATCase
Maxwell Hodges, Mauricio Barahona, Sophia N. Yaliraki
Aspartate carbamoyltransferase (ATCase) is a large dodecameric enzyme with six active sites that exhibits allostery: its catalytic rate is modulated by the binding of various subst…
Semi-supervised classification on graphs using explicit diffusion dynamics
Robert L. Peach, Alexis Arnaudon, Mauricio Barahona
Classification tasks based on feature vectors can be significantly improved by including within deep learning a graph that summarises pairwise relationships between the samples. In…
Stationary distributions of continuous-time Markov chains: a review of theory and truncation-based approximations
Juan Kuntz, Philipp Thomas, Guy-Bart Stan +1
Computing the stationary distributions of a continuous-time Markov chain (CTMC) involves solving a set of linear equations. In most cases of interest, the number of equations is in…
Graph-based data clustering via multiscale community detection
Zijing Liu, Mauricio Barahona
We present a graph-theoretical approach to data clustering, which combines the creation of a graph from the data with Markov Stability, a multiscale community detection framework.…
Extracting information from free text through unsupervised graph-based clustering: an application to patient incident records
M. Tarik Altuncu, Eloise Sorin, Joshua D. Symons +4
The large volume of text in electronic healthcare records often remains underused due to a lack of methodologies to extract interpretable content. Here we present an unsupervised f…
Cellular memory enhances bacterial chemotactic navigation in rugged environments
Adam Gosztolai, Mauricio Barahona
The response of microbes to external signals is mediated by biochemical networks with intrinsic time scales. These time scales give rise to a memory that impacts cellular behaviour…
Learning spatiotemporal signals using a recurrent spiking network that discretizes time
Amadeus Maes, Mauricio Barahona, Claudia Clopath
Learning to produce spatiotemporal sequences is a common task that the brain has to solve. The same neural substrate may be used by the brain to produce different sequential behavi…
Scale-dependent measure of network centrality from diffusion dynamics
Alexis Arnaudon, Robert L. Peach, Mauricio Barahona
Classic measures of graph centrality capture distinct aspects of node importance, from the local (e.g., degree) to the global (e.g., closeness). Here we exploit the connection betw…
Quantifying the Alignment of Graph and Features in Deep Learning
Yifan Qian, Paul Expert, Tom Rieu +2
We show that the classification performance of graph convolutional networks (GCNs) is related to the alignment between features, graph, and ground truth, which we quantify using a…
Data-driven unsupervised clustering of online learner behaviour
Robert L. Peach, Sophia N. Yaliraki, David Lefevre +1
The widespread adoption of online courses opens opportunities for the analysis of learner behaviour and for the optimisation of web-based material adapted to observed usage. Here w…
Stochastic modelling reveals mechanisms of metabolic heterogeneity
Mona K. Tonn, Philipp Thomas, Mauricio Barahona +1
Phenotypic variation is a hallmark of cellular physiology. Metabolic heterogeneity, in particular, underpins single-cell phenomena such as microbial drug tolerance and growth varia…