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As microscopy methods for studying biology in living samples advance and demand for them grows, assessment of light damage caused by imaging becomes increasingly important.
By incorporating an image-classification task into an online video game, the Human Protein Atlas project unlocks the gaming community as a citizen science force.
By coupling multiplex iterative indirect immunofluorescence imaging with computer vision methods, researchers can detect at least 40 different proteins with subcellular resolution.
A new article by Pandarinath et al. describes an artificial neural network model that captures some key aspects of the activity of populations of neurons in the primary motor cortex.
A new detector built for X-ray free-electron lasers provides unprecedented speed and accuracy for macromolecular crystallography at synchrotron radiation facilities—and finally allows crystallographers to harness the full capabilities of those sources.
A computational and analytical framework enables multicolor 3D particle reconstruction of protein complexes from 2D images. The authors demonstrate the power of the approach by reconstructing native proteins within the human centriole.
An all-to-all registration approach allows for improved, high-resolution, template-free single-particle reconstruction from localization microscopy data under realistic experimental conditions such as low labeling density.
Wang et al. demonstrate that the effects of aberrations and scattering caused by the mouse skull can be reduced with three-photon microscopy. Their approach allows structural and functional imaging of the brain through an intact skull.
Reducing the length of time that protein particles spend on a sample grid prior to freezing mitigates deleterious effects caused by particle adsorption to the air–water interface in single-particle cryo-EM.
The Qiita web platform provides access to large amounts of public microbial multi-omic data and enables easy analysis and meta-analysis of standardized private and public data.
A charge-integrating pixel-array detector called JUNGFRAU enables the collection of highly accurate X-ray crystallography data at synchrotron sources at unprecedented speeds.
LFADS, a deep learning method for analyzing neural population activity, can extract neural dynamics from single-trial recordings, stitch separate datasets into a single model, and infer perturbations, for example, from behavioral choices to these dynamics.
The synOptopatch approach enables all-optical access to synaptic communication via mutually exclusive expression of an optogenetic actuator and a voltage sensor in pre- and postsynaptic neurons, respectively.