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Updated: Jan 21, 2026

Bridging the Bio-Electronic Interface with Biofabrication
Published on: June 6, 2012
Finite-sample bias in free energy bridge estimators
1Theoretical and Computational Biophysics Group, NIH Center for Macromolecular Modeling and Bioinformatics, Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, Illinois, 61801-2325, USA.
Abstract:
In practical free energy estimation, the bias is often neglected once it has been shown to vanish in the large-sample limit. Yet finite-sample bias always exists and ought to be considered in any rigorous study. This work develops a metric for bias in a broad class of free energy "bridge estimators" (e.g., Bennett's method). The framework complements existing variance estimation methods and provides a means for comparing systematic and statistical errors. Examples show that, contrary to what is often assumed, the bias can be quite substantial when the sample size is modest.
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