How can we quantify the nanoscale distribution of proteins on the cell surface? How can we tell if they are randomly distributed or not? The answer lies in a new data analysis method for single-molecule super-resolution microscopy.
Photon-upconversion nanoparticles that convert two or more low-energy photons to one photon of UV, visible or NIR light enable the detection and imaging of cancer markers without optical background interference.
We have developed a deep learning method for large-scale virtual screening in a fraction of the time required by conventional docking. Deep Docking can be used in conjunction with any docking program and enables the screening of billions of compounds in a fast and efficient way.
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