We investigate the transition processes between the emitting (ON) and non-emitting (OFF) states of fluorescent molecules using a machine-learning approach. In fluorescently labeled DNA, continuous ...

In a regulated process that involves post-translational modifications on specific proteins called histones, different protein complexes will interact with histones organized into what is called the ...

Although there are many measures of variability for qualitative variables, they are little used in social research, nor are they included in statistical software. The aim of this article is to present ...

Institute for Chemical Reaction Design and Discovery (WPI-ICReDD), Hokkaido University, Sapporo, Hokkaido 001-0021, Japan ERATO Maeda Artificial Intelligence for Chemical Reaction Design and Discovery ...

LaDyBUGS is an efficient alchemical free energy method for computing free energy differences between two or more chemical states. LaDyBUGS uses Gibbs sampling to sample alchemical transformations ...

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. Article Views are the COUNTER-compliant sum of full text article downloads since ...

In 2004, Skilling introduced the nested sampling algorithm 1,2 in the context of Bayesian inference and computation (Box 1). The nested sampling algorithm solves otherwise challenging, ...

Purpose: Bayesian calibration is generally superior to standard direct-search algorithms in that it estimates the full joint posterior distribution of the calibrated parameters. However, there are ...

In most applications, functional materials operate at finite temperatures and are in contact with a reservoir of atoms or molecules (gas, liquid, or solid). In order to understand the properties of ...

Bayesian Networks are graphical models useful for various applications, including time series prediction and anomaly detection. Bayesian inference offers a robust set of tools for modelling ...