Template-based 3D model fitting using dual-domain relaxation

DiffFit: Visually-Guided Differentiable Fitting of Molecule Structures to a Cryo-EM Map

We introduce DiffFit, a differentiable algorithm for fitting protein atomistic structures into an experimental reconstructed Cryo-Electron Microscopy (cryo-EM) volume map. In structural biology, this process is necessary to semi-automatically composite large mesoscale models of complex protein assemblies and complete cellular structures that are based on measured cryo-EM data. The current approaches require manual fitting in three dimensions to start, resulting in approximately aligned structures followed by an automated fine-tuning of the alignment. The DiffFit approach enables domain scientists to fit new structures automatically and visualize the results for inspection and interactive revision. The fitting begins with differentiable three-dimensional (3D) rigid transformations of the protein atom coordinates followed by sampling the density values at the atom coordinates from the target cryo-EM volume. To ensure a meaningful correlation between the sampled densities and the protein structure, we proposed a novel loss function based on a multi-resolution volume-array approach and the exploitation of the negative space. This loss function serves as a critical metric for assessing the fitting quality, ensuring the fitting accuracy and an improved visualization of the results. We assessed the placement quality of DiffFit with several large, realistic datasets and found it to be superior to that of previous methods. We further evaluated our method in two use cases: automating the integration of known composite structures into larger protein complexes and facilitating the fitting of predicted protein domains into volume densities to aid researchers in identifying unknown proteins. We implemented our algorithm as an open-source plugin (github.com/nanovis/DiffFit) in ChimeraX, a leading visualization software in the field. All supplemental materials are available at osf. io/5tx4q.

An Approach for Generating an Average Bone Template With Semantic Parameters

To facilitate the design of the serialized implants and to satisfy the requirements of the population, a novel method is put forward for constructing an average bone model (ABM) with semantic parameters as a template. First, the ABM is created from the existing bone models, among which each bone has an equal contribution to the ABM. Second, combined with medical semantics, some characteristic points and semantic parameters are defined on the ABM, and then, parameter values for each bone can be automatically obtained through its registration and deformation to the ABM. Finally, an average bone template (ABT) is constructed by configuring the semantic parameters and by building the constraints between parameters. Taking 100 femur models as samples, we construct the ABT, and the template can be easily extended to generate a new average template through the given average equation.

Interactive applications for sketch-based editable polycube map

In this paper, we propose a sketch-based editable polycube mapping method that, given a general mesh and a simple polycube that coarsely resembles the shape of the object, plus sketched features indicating relevant correspondences between the two, provides a uniform, regular, and user-controllable quads-only mesh that can be used as a basis structure for subdivision. Large scale models with complex geometry and topology can be processed efficiently with simple, intuitive operations. We show that the simple, intuitive nature of the polycube map is a substantial advantage from the point of view of the interface by demonstrating a series of applications, including kit-basing, shape morphing, painting over the parameterization domain, and GPU-friendly tessellated subdivision displacement, where the user is also able to control the number of patches in the base mesh by the construction of the base polycube.

Efficient optimization of common base domains for cross parameterization

Given a set of corresponding user-specified anchor points on a pair of models having similar features and topologies, the cross parameterization technique can establish a bijective mapping constrained by the anchor points. In this paper, we present an efficient algorithm to optimize the complexes and the shape of common base domains in cross parameterization for reducing the distortion of the bijective mapping. The optimization is also constrained by the anchor points. We investigate a new signature, Length-Preserved Base Domain (LPBD), for measuring the level of stretch between surface patches in cross parameterization. This new signature well balances the accuracy of measurement and the computational speed. Based on LPBD, a set of metrics are studied and compared. The best ones are employed in our domain optimization algorithm that consists of two major operators, boundary swapping and patch merging. Experimental results show that our optimization algorithm can reduce the distortion in cross parameterization efficiently.