Particle picking is a crucial first step in the computational pipeline of single-particle cryo-electron microscopy (cryo-EM). Selecting particles from the micrographs is difficult especially for small particles with low contrast. As high-resolution reconstruction typically requires hundreds of thousands of particles, manually picking that many particles is often too time-consuming. 

While semi-automated particle picking is currently a popular approach, it may suffer from introducing manual bias into the selection process. In addition, semi-automated particle picking is still somewhat time-consuming. A popular approach to semi-automated particle picking is template matching using the cross-correlation function. In this talk I will show that information gathered from the cross-correlation function is useful even in the absence of templates. Specifically, when given  an automatically selected homogenous set of windows from the micrograph, this function can be utilized in order to determine the content of any query window in the micrograph. This insight led to the APPLE picker (Heimowitz, Andén and Singer) which is a fast, fully automatic (template-free) particle picker