Research news on Statistical methods

Statistical methods, as a technique, encompass a set of quantitative procedures for collecting, summarizing, modeling, and inferring properties of data under uncertainty. They include techniques for descriptive analysis (e.g., estimation of moments, correlation) and inferential analysis (e.g., hypothesis testing, confidence intervals, regression, and multilevel modeling), typically grounded in probability theory. Statistical methods formalize assumptions about data-generating processes, quantify sampling variability, control error rates, and support model comparison and prediction. They are implemented through parametric, nonparametric, and Bayesian frameworks, often relying on numerical optimization and simulation (e.g., MCMC, bootstrap) to obtain estimates and uncertainty measures in complex models.

AI fast-forwards molecular simulations by 10,000-fold

A new AI model has become so good at predicting how molecules evolve over time that, in the future, it could speed up the costly and time-consuming process of testing new drugs. In the long term, this technology could facilitate ...

Q&A: What AI actually does in diffusion models for drug design

In the search for new drugs, artificial intelligence in the form of diffusion models is being used in drug design. What exactly does AI do in this context? Dr. Andrea Mastropietro and Prof. Dr. Jürgen Bajorath from Life Science ...

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