Figure 1.

Schematic representation of the path collective variable and Bayesian formalism for cryo-BIFE. The main goal of our methodology is to determine the posterior probability distribution of free-energy profiles G(s) over a given configuration space path X(s), given a set of noisy cryo-EM particle (projection) images $w=\{w_i\}$ from $i=1,\dots ,I$. The green graphs on the right show independent samples drawn from this posterior, and the blue curve their mean. The black curve represents the true free-energy profile. Variation between sampled free energy surfaces arises from a detailed Bayesian model of imaging noise. The path $0\le s\le 1$ is discretized using M nodes.