Explore 204 academic publications
Potential conflict of interest: Dr. Hwang received grants from Merck and Gilead. Dr. Chang advises Arbutus. Dr. Lok received grants from Gilead and Bristol‐Myers Squibb. Dr. Jon...
Developing a mechanistic understanding of the impact of food structure and composition on human health has increasingly involved simulating digestion in the upper gastrointestin...
The Bayesian Evolutionary Analysis by Sampling Trees (BEAST) software package has become a primary tool for Bayesian phylogenetic and phylodynamic inference from genetic sequenc...
Background The coronavirus disease 2019 (COVID-19) outbreak is evolving rapidly worldwide. Objective To evaluate the risk of serious adverse outcomes in patients with COVID-19 b...
While the vast majority of well-structured single protein chains can now be predicted to high accuracy due to the recent AlphaFold [1] model, the prediction of multi-chain prote...
<b>Background:</b> Spirometry is the most common pulmonary function test. It is widely used in the assessment of lung function to provide objective information used in the diagn...
Abstract Multi-epoch radial velocity measurements of stars can be used to identify stellar, substellar, and planetary-mass companions. Even a small number of observation epochs ...
[1st paragraph] At first sight, Bayesian inference with Markov Chain Monte Carlo (MCMC) appears to be straightforward. The user defines a full probability model, perhaps using o...
The possibilities of the Hohenberg-Kohn-Sham local density theory are explored in view of recent advances in the theory of the interacting electron gas. The authors discuss and ...
We introduce the Bayesian skyline plot, a new method for estimating past population dynamics through time from a sample of molecular sequences without dependence on a prespecifi...
Although trust is an underdeveloped concept in sociology, promising theoretical formulations are available in the recent work of Luhmann and Barber. This sociological version co...
article Free AccessFab: content-based, collaborative recommendation Authors: Marko Balabanović Computer Science Department, Stanford University, Stanford, Calif. Computer Scienc...