New tools for automated cryo-EM single-particle analysis in RELION-4.0

We describe new tools for the processing of electron cryo-microscopy (cryo-EM) images in the fourth major release of the RELION software. In particular, we introduce VDAM, a Variable-metric gradient Descent algorithm with Adaptive Moments estimation, for image refinement; a convolutional neural network for unsupervised selection of 2D classes; and a flexible framework for the design and execution of multiple jobs in pre-defined workflows. In addition, we present a stand-alone utility called MDCatch that links the execution of jobs within this framework with metadata gathering during microscope data acquisition. The new tools are aimed at providing fast and robust procedures for unsupervised cryo-EM structure determination, with potential applications for on-the-fly processing and the development of flexible, high-throughput structure determination pipelines. We illustrate their potential on twelve publicly available cryo-EM data sets.

Dynamic Programming as a Scheduling Tool in Multiprogrammed Computing Systems

<p>A potentially parallel iterative algorithm for the solution of the unconstrained N-stage decision problem of Dynamic Programming is developed. This new solution method, known as Variable Metric Dynamic Programming, is based on the use of variable metric minimisation techniques to develop quadratic approximations to the optimal cost function for each stage. The algorithm is applied to various test problems, and a comparison with an existing similar algorithm proves favourable. The Variable Metric Dynamic Programming solution method is used in the implementation of an adaptive highlevel scheduling mechanism on a multiprogrammed computer in a university environment. This demonstrates a practical application of the new algorithm. More importantly, the application of Variable Metric Dynamic Programming to a scheduling problem illustrates how Mathematical Programming may be used in complex computer scheduling problems to provide in a natural way the required dynamic feedback mechanisms.</p>

Dynamic Programming as a Scheduling Tool in Multiprogrammed Computing Systems

<p>A potentially parallel iterative algorithm for the solution of the unconstrained N-stage decision problem of Dynamic Programming is developed. This new solution method, known as Variable Metric Dynamic Programming, is based on the use of variable metric minimisation techniques to develop quadratic approximations to the optimal cost function for each stage. The algorithm is applied to various test problems, and a comparison with an existing similar algorithm proves favourable. The Variable Metric Dynamic Programming solution method is used in the implementation of an adaptive highlevel scheduling mechanism on a multiprogrammed computer in a university environment. This demonstrates a practical application of the new algorithm. More importantly, the application of Variable Metric Dynamic Programming to a scheduling problem illustrates how Mathematical Programming may be used in complex computer scheduling problems to provide in a natural way the required dynamic feedback mechanisms.</p>

A New Homotopy Proximal Variable-Metric Framework for Composite Convex Minimization

This paper suggests two novel ideas to develop new proximal variable-metric methods for solving a class of composite convex optimization problems. The first idea is to utilize a new parameterization strategy of the optimality condition to design a class of homotopy proximal variable-metric algorithms that can achieve linear convergence and finite global iteration-complexity bounds. We identify at least three subclasses of convex problems in which our approach can apply to achieve linear convergence rates. The second idea is a new primal-dual-primal framework for implementing proximal Newton methods that has attractive computational features for a subclass of nonsmooth composite convex minimization problems. We specialize the proposed algorithm to solve a covariance estimation problem in order to demonstrate its computational advantages. Numerical experiments on the four concrete applications are given to illustrate the theoretical and computational advances of the new methods compared with other state-of-the-art algorithms.

New tools for automated cryo-EM single-particle analysis in RELION-4.0

We describe new tools for the processing of electron cryo-microscopy (cryo-EM) images in the fourth major release of the RELION software. In particular, we introduce VDAM, a Variable-metric gradient Descent algorithm with Adaptive Moments estimation, for image refinement; a convolutional neural network for unsupervised selection of 2D classes; and a flexible framework for the design and execution of multiple jobs in pre-defined workflows. In addition, we present a stand-alone utility called MDCatch that links the execution of jobs within this framework with metadata gathering during microscope data acquisition. The new tools are aimed at providing fast and robust procedures for unsupervised cryo-EM structure determination, with potential applications for on-the-fly processing and the development of flexible, high-throughput structure determination pipelines. We illustrate their potential on twelve publicly available cryo-EM data sets.