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Single-shot diffraction data from the Mimivirus particle using an X-ray free-electron laser
- Ekeberg, Tomas;
- Svenda, Martin;
- Seibert, M Marvin;
- Abergel, Chantal;
- Maia, Filipe RNC;
- Seltzer, Virginie;
- DePonte, Daniel P;
- Aquila, Andrew;
- Andreasson, Jakob;
- Iwan, Bianca;
- Jönsson, Olof;
- Westphal, Daniel;
- Odić, Duško;
- Andersson, Inger;
- Barty, Anton;
- Liang, Meng;
- Martin, Andrew V;
- Gumprecht, Lars;
- Fleckenstein, Holger;
- Bajt, Saša;
- Barthelmess, Miriam;
- Coppola, Nicola;
- Claverie, Jean-Michel;
- Loh, N Duane;
- Bostedt, Christoph;
- Bozek, John D;
- Krzywinski, Jacek;
- Messerschmidt, Marc;
- Bogan, Michael J;
- Hampton, Christina Y;
- Sierra, Raymond G;
- Frank, Matthias;
- Shoeman, Robert L;
- Lomb, Lukas;
- Foucar, Lutz;
- Epp, Sascha W;
- Rolles, Daniel;
- Rudenko, Artem;
- Hartmann, Robert;
- Hartmann, Andreas;
- Kimmel, Nils;
- Holl, Peter;
- Weidenspointner, Georg;
- Rudek, Benedikt;
- Erk, Benjamin;
- Kassemeyer, Stephan;
- Schlichting, Ilme;
- Strüder, Lothar;
- Ullrich, Joachim;
- Schmidt, Carlo;
- Krasniqi, Faton;
- Hauser, Günter;
- Reich, Christian;
- Soltau, Heike;
- Schorb, Sebastian;
- Hirsemann, Helmut;
- Wunderer, Cornelia;
- Graafsma, Heinz;
- Chapman, Henry;
- Hajdu, Janos
- et al.
Published Web Location
https://doi.org/10.1038/sdata.2016.60Abstract
Free-electron lasers (FEL) hold the potential to revolutionize structural biology by producing X-ray pules short enough to outrun radiation damage, thus allowing imaging of biological samples without the limitation from radiation damage. Thus, a major part of the scientific case for the first FELs was three-dimensional (3D) reconstruction of non-crystalline biological objects. In a recent publication we demonstrated the first 3D reconstruction of a biological object from an X-ray FEL using this technique. The sample was the giant Mimivirus, which is one of the largest known viruses with a diameter of 450 nm. Here we present the dataset used for this successful reconstruction. Data-analysis methods for single-particle imaging at FELs are undergoing heavy development but data collection relies on very limited time available through a highly competitive proposal process. This dataset provides experimental data to the entire community and could boost algorithm development and provide a benchmark dataset for new algorithms.
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