SMAUG: Analyzing single-molecule tracks with nonparametric Bayesian statistics
نویسندگان
چکیده
منابع مشابه
Analyzing single-molecule time series via nonparametric Bayesian inference.
The ability to measure the properties of proteins at the single-molecule level offers an unparalleled glimpse into biological systems at the molecular scale. The interpretation of single-molecule time series has often been rooted in statistical mechanics and the theory of Markov processes. While existing analysis methods have been useful, they are not without significant limitations including p...
متن کاملLectures on Nonparametric Bayesian Statistics
Notes for the course by Bas Kleijn, Aad van der Vaart, Harry van Zanten (Text partly extracted from a forthcoming book by S. Ghosal and A. van der Vaart) version 4-12-2012 UNDER CONSTRUCTION 1 Introduction Why adopt the nonparametric Bayesian approach for inference? The answer lies in the simultaneous preference for nonparametric modeling and desire to follow a Bayesian procedure. Nonparametric...
متن کاملPractical Nonparametric and Semiparametric Bayesian Statistics
Imagine that you get such certain awesome experience and knowledge by only reading a book. How can? It seems to be greater when a book can be the best thing to discover. Books now will appear in printed and soft file collection. One of them is this book practical nonparametric and semiparametric bayesian statistics. It is so usual with the printed books. However, many people sometimes have no s...
متن کاملAnalyzing single-molecule manipulation experiments.
Single-molecule manipulation studies can provide quantitative information about the physical properties of complex biological molecules without ensemble artifacts obscuring the measurements. We demonstrate computational techniques which aim at more fully utilizing the wealth of information contained in noisy experimental time series. The "noise" comes from multiple sources e.g., inherent therma...
متن کاملBayesian Nonparametric and Parametric Inference
This paper reviews Bayesian Nonparametric methods and discusses how parametric predictive densities can be constructed using nonparametric ideas.
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Methods
سال: 2020
ISSN: 1046-2023
DOI: 10.1016/j.ymeth.2020.03.008