@article {49087,
	title = {cisTEM, User-friendly software for single-particle image processing.},
	journal = {eLife},
	volume = {7},
	year = {2018},
	month = {2018 Mar 07},
	abstract = {<p>We have developed new open-source software calledTEM (computational imaging system for transmission electron microscopy) for the processing of data for high-resolution electron cryo-microscopy and single-particle averaging.TEM features a graphical user interface that is used to submit jobs, monitor their progress, and display results. It implements a full processing pipeline including movie processing, image defocus determination, automatic particle picking, 2D classification, ab-initio 3D map generation from random parameters, 3D classification, and high-resolution refinement and reconstruction. Some of these steps implement newly-developed algorithms; others were adapted from previously published algorithms. The software is optimized to enable processing of typical datasets (2000 micrographs, 200k - 300k particles) on a high-end, CPU-based workstation in half a day or less, comparable to GPU-accelerated processing. Jobs can also be scheduled on large computer clusters using flexible run profiles that can be adapted for most computing environments.TEM is available for download from cistem.org.</p>
},
	issn = {2050-084X},
	doi = {10.7554/eLife.35383},
	author = {Grant, Timothy and Rohou, Alexis and Grigorieff, Nikolaus}
}
@article {46998,
	title = {CTFFIND4: Fast and accurate defocus estimation from electron micrographs.},
	journal = {Journal of Structural Biology},
	volume = {192},
	year = {2015},
	month = {2015 Aug 13},
	pages = {216-21},
	abstract = {<p>CTFFIND is a widely-used program for the estimation of objective lens defocus parameters from transmission electron micrographs. Defocus parameters are estimated by fitting a model of the microscope{\textquoteright}s contrast transfer function (CTF) to an image{\textquoteright}s amplitude spectrum. Here we describe modifications to the algorithm which make it significantly faster and more suitable for use with images collected using modern technologies such as dose fractionation and phase plates. We show that this new version preserves the accuracy of the original algorithm while allowing for higher throughput. We also describe a measure of the quality of the fit as a function of spatial frequency and suggest this can be used to define the highest resolution at which CTF oscillations were successfully modeled.</p>
},
	issn = {1095-8657},
	doi = {10.1016/j.jsb.2015.08.008},
	author = {Rohou, Alexis and Grigorieff, Nikolaus}
}
