Publications
Explore 467 academic publications
High Performance of <sup>18</sup>F-Fluorodeoxyglucose Positron Emission Tomography and Contrast-Enhanced CT in a Rapid Outpatient Diagnostic Program for Patients with Suspected Lung Cancer
<b><i>Background:</i></b> The diagnostic evaluation of patients presenting with possible lung cancer is often complex and time consuming. A rapid outpati...
Model Selection and Model Averaging in Phylogenetics: Advantages of Akaike Information Criterion and Bayesian Approaches Over Likelihood Ratio Tests
Model selection is a topic of special relevance in molecular phylogenetics that affects many, if not all, stages of phylogenetic inference. Here we discuss some fundamental conc...
Federated Learning: Challenges, Methods, and Future Directions
Federated learning involves training statistical models over remote devices or siloed data centers, such as mobile phones or hospitals, while keeping data localized. Training in...
Report 9: Impact of non-pharmaceutical interventions (NPIs) to reduce COVID19 mortality and healthcare demand
The global impact of COVID-19 has been profound, and the public health threat it represents is the most serious seen in a respiratory virus since the 1918 H1N1 influenza pandemi...
Bayesian phylogenetic and phylodynamic data integration using BEAST 1.10
The Bayesian Evolutionary Analysis by Sampling Trees (BEAST) software package has become a primary tool for Bayesian phylogenetic and phylodynamic inference from genetic sequenc...
Superconductivity of Metals and Alloys
Drawn from the author's introductory course at the University of Orsay, Superconductivity of Metals and Alloys is intended to explain the basic knowledge of superconductivity fo...
Evolutionary-scale prediction of atomic-level protein structure with a language model
Recent advances in machine learning have leveraged evolutionary information in multiple sequence alignments to predict protein structure. We demonstrate direct inference of full...
To saturate or not to saturate? Questioning data saturation as a useful concept for thematic analysis and sample-size rationales
The concept of data saturation, defined as 'information redundancy' or the point at which no new themes or codes 'emerge' from data, is widely referenced in thematic analysis (T...