Deep learning is transforming most areas of science and technology, including electron
microscopy. This review paper offers a practical perspective aimed at developers with …

The functions of biological macromolecules are often associated with conformational
malleability of the structures. This phenomenon of chemically identical molecules with …

Abstract 2D classification plays a pivotal role in analyzing single particle cryo-electron
microscopy images. Here, we introduce a simple and loss-less pre-processor that …

Principal component analysis (PCA) is a commonly used statistical tool for dimension
reduction. An important issue in PCA is to determine the rank, which is the number of …

Despite the fact that single particle cryo-EM has become a powerful method of structural
biology, processing cryo-EM images are challenging due to the low SNR, high-dimension …

During my thesis, I developed three methods based on deep learning to extract continuous
conformational variability of biomolecular complexes from single-particle cryo electron …

Here, we propose combining empirical Bayes modeling with recent advances in Markov
chain Monte Carlo filters for hidden Markov models. In doing so, we address long-standing …

Dimension reduction methods for matrix or tensor data have been an active research field in
recent years. Li et al.(2010) introduced the notion of the Kronecker envelope and proposed …

Thanks to GPU-accelerated processing, cryo-EM has become a rapid structure
determination method that permits capture of dynamical structures of molecules in solution …

Cryogenic Electron microscopy (cryo-EM) is one of the most important instruments for
determining the structures of protein complexes in near-atomic resolution, evidenced by the …