Xmipp is an open-source software package consisting of multiple programs for processing data originating from electron microscopy and electron tomography, designed and managed by the Biocomputing Unit of the Spanish National Center for Biotechnology, although with contributions from many other developers over the world. During its 25 years of existence, Xmipp underwent multiple changes and updates. While there were many publications related to new programs and functionality added to Xmipp, there is no single publication on the Xmipp as a package since 2013. In this article, we give an overview of the changes and new work since 2013, describe technologies and techniques used during the development, and take a peek at the future of the package.

Departament de Física Aplicada Universitat de Barcelona Martí i Franquès 1 08028 Barcelona Spain

Departamento de Óptica Universidad Complutense de Madrid Plaza de Ciencias 1 28040 Madrid Spain

Faculty of Informatics Masaryk University Botanická 68a 60200 Brno Czech Republic

IMPMC UMR 7590 CNRS Sorbonne Université Muséum National d'Histoire Naturelle 4 Place Jussieu 75005 Paris France

Institute of Computer Science Masaryk University Botanická 68a 60200 Brno Czech Republic

Oxford Protein Informatics Group Department of Statistics University of Oxford Oxford OX1 3LB UK

Spanish National Centre for Biotechnology Spanish National Research Council Calle Darwin 3 28049 Madrid Spain

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de la Rosa-Trevín J.M., Quintana A., del Caño L., Zaldívar A., Foche I., Gutiérrez J., Gómez-Blanco J., Burguet-Castell J., Cuenca-Alba J., Abrishami V., et al. Scipion: A software framework toward integration, reproducibility and validation in 3D electron microscopy. J. Struct. Biol. 2016;195:93–99. doi: 10.1016/j.jsb.2016.04.010. PubMed DOI

de la Rosa-Trevín J.M., Otón J., Marabini R., Zaldívar A., Vargas J., Carazo J.M., Sorzano C.Ó.S. Xmipp 3.0: An improved software suite for image processing in electron microscopy. J. Struct. Biol. 2013;184:321–328. doi: 10.1016/j.jsb.2013.09.015. PubMed DOI

Bendory T., Bartesaghi A., Singer A. Single-Particle Cryo-Electron Microscopy: Mathematical Theory, Computational Challenges, and Opportunities. IEEE Signal Process. Mag. 2019;37:58–76. doi: 10.1109/MSP.2019.2957822. PubMed DOI PMC

Vargas J., Franken E., Sorzano C.Ó.S., Gomez-Blanco J., Schoenmakers R., Koster A., Carazo J.M. Foil-hole and data image quality assessment in 3DEM: Towards high-throughput image acquisition in the electron microscope. J. Struct. Biol. 2016;196:515–524. doi: 10.1016/j.jsb.2016.10.006. PubMed DOI

Abrishami V., Vargas J., Li X., Cheng Y., Marabini R., Sorzano C.Ó.S., Carazo J.M. Alignment of direct detection device micrographs using a robust Optical Flow approach. J. Struct. Biol. 2015;189:163–176. doi: 10.1016/j.jsb.2015.02.001. PubMed DOI

Střelák D., Filipovič J., Jiménez-Moreno A., Carazo J.M., Sorzano C.Ó.S. FlexAlign: An Accurate and Fast Algorithm for Movie Alignment in Cryo-Electron Microscopy. Electronics. 2020;9:1040. doi: 10.3390/electronics9061040. DOI

Sorzano C.Ó.S., Fernández-Giménez E., Peredo-Robinson V., Vargas J., Majtner T., Caffarena G., Otón J., Vilas J.L., de la Rosa-Trevín J.M., Melero R., et al. Blind estimation of DED camera gain in Electron Microscopy. J. Struct. Biol. 2018;203:90–93. doi: 10.1016/j.jsb.2018.03.007. PubMed DOI

Marabini R., Carragher B., Chen S., Chen J., Cheng A., Downing K.H., Frank J., Grassucci R.A., Bernard Heymann J., Jiang W., et al. CTF Challenge: Result summary. J. Struct. Biol. 2015;190:348–359. doi: 10.1016/j.jsb.2015.04.003. PubMed DOI PMC

Vargas J., Otón J., Marabini R., Jonić S., de la Rosa-Trevín J.M., Carazo J.M., Sorzano C.Ó.S. FASTDEF: Fast defocus and astigmatism estimation for high-throughput transmission electron microscopy. J. Struct. Biol. 2013;181:136–148. doi: 10.1016/j.jsb.2012.12.006. PubMed DOI

Abrishami V., Zaldívar-Peraza A., de la Rosa-Trevín J.M., Vargas J., Otón J., Marabini R., Shkolnisky Y., Carazo J.M., Sorzano C.Ó.S. A pattern matching approach to the automatic selection of particles from low-contrast electron micrographs. Bioinformatics. 2013;29:2460–2468. doi: 10.1093/bioinformatics/btt429. PubMed DOI

Vilas J.L., Navas J., Gómez-Blanco J., de la Rosa-Trevín J.M., Melero R., Peschiera I., Ferlenghi I., Cuenca J., Marabini R., Carazo J.M., et al. Fast and automatic identification of particle tilt pairs based on Delaunay triangulation. J. Struct. Biol. 2016;196:525–533. doi: 10.1016/j.jsb.2016.10.007. PubMed DOI

Vargas J., Abrishami V., Marabini R., de la Rosa-Trevín J.M., Zaldivar A., Carazo J.M., Sorzano C.Ó.S. Particle quality assessment and sorting for automatic and semiautomatic particle-picking techniques. J. Struct. Biol. 2013;183:342–353. doi: 10.1016/j.jsb.2013.07.015. PubMed DOI

Sánchez-García R., Segura J., Maluenda D., Carazo J.M., Sorzano C.Ó.S. Deep Consensus, a deep learning-based approach for particle pruning in cryo-electron microscopy. IUCrJ. 2018;5:854–865. doi: 10.1107/S2052252518014392. PubMed DOI PMC

Sánchez-García R., Segura J., Maluenda D., Sorzano C.Ó.S., Carazo J.M. MicrographCleaner: A python package for cryo-EM micrograph cleaning using deep learning. J. Struct. Biol. 2020;210:107498. doi: 10.1016/j.jsb.2020.107498. PubMed DOI

Sorzano C.Ó.S., Vargas J., de la Rosa-Trevín J.M., Zaldívar-Peraza A., Otón J., Abrishami V., Foche I., Marabini R., Caffarena G., Carazo J.M. Outlier Detection for Single Particle Analysis in Electron Microscopy; Proceedings of the IWBBIO 2014; Granada, Spain. 7–9 April 2014; pp. 950–959.

Vargas J., Álvarez Cabrera A.L., Marabini R., Carazo J.M., Sorzano C.Ó.S. Efficient initial volume determination from electron microscopy images of single particles. Bioinformatics. 2014;30:2891–2898. doi: 10.1093/bioinformatics/btu404. PubMed DOI

Sorzano C.Ó.S., Alcorlo M., de la Rosa-Trevín J.M., Melero R., Foche I., Zaldívar-Peraza A., del Caño L., Vargas J., Abrishami V., Otón J., et al. Cryo-EM and the elucidation of new macromolecular structures: Random Conical Tilt revisited. Sci. Rep. 2015;5:14290. doi: 10.1038/srep14290. PubMed DOI PMC

Sorzano C.Ó.S., Vargas J., de la Rosa-Trevín J.M., Otón J., Álvarez Cabrera A., Abrishami V., Sesmero E., Marabini R., Carazo J.M. A statistical approach to the initial volume problem in Single Particle Analysis by Electron Microscopy. J. Struct. Biol. 2015;189:213–219. doi: 10.1016/j.jsb.2015.01.009. PubMed DOI

Sorzano C.Ó.S., Vargas J., Vilas J.L., Jiménez-Moreno A., Mota J., Majtner T., Maluenda D., Martínez M., Sánchez-García R., Segura J., et al. Swarm optimization as a consensus technique for Electron Microscopy Initial Volume. Appl. Anal. Optim. 2018;2:299–313.

Vargas J., Otón J., Marabini R., Carazo J.M., Sorzano C.Ó.S. Particle alignment reliability in single particle electron cryomicroscopy: A general approach. Sci. Rep. 2016;6:21626. doi: 10.1038/srep21626. PubMed DOI PMC

Vargas J., Melero R., Gómez-Blanco J., Carazo J.M., Sorzano C.Ó.S. Quantitative analysis of 3D alignment quality: Its impact on soft-validation, particle pruning and homogeneity analysis. Sci. Rep. 2017;7:6307. doi: 10.1038/s41598-017-06526-z. PubMed DOI PMC

Abrishami V., Bilbao-Castro J., Vargas J., Marabini R., Carazo J.M., Sorzano C.Ó.S. A fast iterative convolution weighting approach for gridding-based direct Fourier three-dimensional reconstruction with correction for the contrast transfer function. Ultramicroscopy. 2015;157:79–87. doi: 10.1016/j.ultramic.2015.05.018. PubMed DOI

Střelák D., Sorzano C.Ó.S., Carazo J.M., Filipovič J. A GPU acceleration of 3-D Fourier reconstruction in cryo-EM. Int. J. High Perform. Comput. Appl. 2019;33:948–959. doi: 10.1177/1094342019832958. DOI

Sorzano C.Ó.S., Vargas J., de la Rosa-Trevín J.M., Jiménez-Moreno A., Maluenda D., Melero R., Martínez M., Ramírez-Aportela E., Conesa P., Vilas J.L., et al. A new algorithm for high-resolution reconstruction of single particles by electron microscopy. J. Struct. Biol. 2018;204:329–337. doi: 10.1016/j.jsb.2018.08.002. PubMed DOI

Heymann J.B., Marabini R., Kazemi M., Sorzano C.Ó.S., Holmdahl M., Mendez J.H., Stagg S.M., Jonić S., Palovcak E., Armache J.P., et al. The first single particle analysis Map Challenge: A summary of the assessments. J. Struct. Biol. 2018;204:291–300. doi: 10.1016/j.jsb.2018.08.010. PubMed DOI PMC

Marabini R., Kazemi M., Sorzano C.Ó.S., Carazo J.M. Map challenge: Analysis using a pair comparison method based on Fourier shell correlation. J. Struct. Biol. 2018;204:527–542. doi: 10.1016/j.jsb.2018.09.009. PubMed DOI

Jiménez-Moreno A., Střelák D., Filipovič J., Carazo J.M., Sorzano C.Ó.S. DeepAlign, a 3D alignment method based on regionalized deep learning for Cryo-EM. J. Struct. Biol. 2021;213:107712. doi: 10.1016/j.jsb.2021.107712. PubMed DOI

Nogales-Cadenas R., Jonić S., Tama F., Arteni A.A., Tabas-Madrid D., Vázquez M., Pascual-Montano A., Sorzano C.Ó.S. 3DEM Loupe: Analysis of macromolecular dynamics using structures from electron microscopy. Nucleic Acids Res. 2013;41:W363–W367. doi: 10.1093/nar/gkt385. PubMed DOI PMC

Jin Q., Sorzano C.Ó.S., de la Rosa-Trevín J.M., Bilbao-Castro J., Núñez-Ramírez R., Llorca O., Tama F., Jonić S. Iterative Elastic 3D-to-2D Alignment Method Using Normal Modes for Studying Structural Dynamics of Large Macromolecular Complexes. Structure. 2014;22:496–506. doi: 10.1016/j.str.2014.01.004. PubMed DOI

Sorzano C.Ó.S., de la Rosa-Trevín J.M., Tama F., Jonić S. Hybrid Electron Microscopy Normal Mode Analysis graphical interface and protocol. J. Struct. Biol. 2014;188:134–141. doi: 10.1016/j.jsb.2014.09.005. PubMed DOI

Jonić S., Sorzano C.Ó.S. Coarse-Graining of Volumes for Modeling of Structure and Dynamics in Electron Microscopy: Algorithm to Automatically Control Accuracy of Approximation. IEEE J. Sel. Top. Signal Process. 2016;10:161–173. doi: 10.1109/JSTSP.2015.2489186. DOI

Jonić S., Vargas J., Melero R., Gómez-Blanco J., Carazo J.M., Sorzano C.Ó.S. Denoising of high-resolution single-particle electron-microscopy density maps by their approximation using three-dimensional Gaussian functions. J. Struct. Biol. 2016;194:423–433. doi: 10.1016/j.jsb.2016.04.007. PubMed DOI

Harastani M., Sorzano C.Ó.S., Jonić S. Hybrid Electron Microscopy Normal Mode Analysis with Scipion. Protein Sci. 2020;29:223–236. doi: 10.1002/pro.3772. PubMed DOI PMC

Sorzano C.Ó.S., Alvarez-Cabrera A., Kazemi M., Carazo J.M., Jonić S. StructMap: Elastic Distance Analysis of Electron Microscopy Maps for Studying Conformational Changes. Biophys. J. 2016;110:1753–1765. doi: 10.1016/j.bpj.2016.03.019. PubMed DOI PMC

Harastani M., Eltsov M., Leforestier A., Jonić S. HEMNMA-3D: Cryo Electron Tomography Method Based on Normal Mode Analysis to Study Continuous Conformational Variability of Macromolecular Complexes. Front. Mol. Biosci. 2021;8:663121. doi: 10.3389/fmolb.2021.663121. PubMed DOI PMC

Kazemi M., Sorzano C.Ó.S., Carazo J.M., Georges A.d., Abrishami V., Vargas J. ENRICH: A fast method to improve the quality of flexible macromolecular reconstructions. Prog. Biophys. Mol. Biol. 2021;164:92–100. doi: 10.1016/j.pbiomolbio.2021.01.001. PubMed DOI

Sorzano C.Ó.S., Martín-Ramos A., Prieto F., Melero R., Martín-Benito J., Jonić S., Navas-Calvente J., Vargas J., Otón J., Abrishami V., et al. Local analysis of strains and rotations for macromolecular electron microscopy maps. J. Struct. Biol. 2016;195:123–128. doi: 10.1016/j.jsb.2016.04.001. PubMed DOI

Vilas J.L., Gómez-Blanco J., Conesa P., Melero R., de la Rosa-Trevín J.M., Otón J., Cuenca J., Marabini R., Carazo J.M., Vargas J., et al. MonoRes: Automatic and Accurate Estimation of Local Resolution for Electron Microscopy Maps. Structure. 2018;26:337–344.e4. doi: 10.1016/j.str.2017.12.018. PubMed DOI

Vilas J.L., Otón J., Messaoudi C., Melero R., Conesa P., Ramirez-Aportela E., Mota J., Martínez M., Jiménez-Moreno A., Marabini R., et al. Measurement of local resolution in electron tomography. J. Struct. Biol. X. 2020;4:100016. doi: 10.1016/j.yjsbx.2019.100016. PubMed DOI PMC

Ramírez-Aportela E., Mota J., Conesa P., Carazo J.M., Sorzano C.Ó.S. DeepRes: A new deep-learning- and aspect-based local resolution method for electron-microscopy maps. IUCrJ. 2019;6:1054–1063. doi: 10.1107/S2052252519011692. PubMed DOI PMC

Ramírez-Aportela E., Vilas J.L., Glukhova A., Melero R., Conesa P., Martínez M., Maluenda D., Mota J., Jiménez-Moreno A., Vargas J., et al. Automatic local resolution-based sharpening of cryo-EM maps. Bioinformatics. 2019;36:765–772. doi: 10.1093/bioinformatics/btz671. PubMed DOI PMC

Vilas J.L., Tagare H.D., Vargas J., Carazo J.M., Sorzano C.Ó.S. Measuring local-directional resolution and local anisotropy in cryo-EM maps. Nat. Commun. 2020;11:55. doi: 10.1038/s41467-019-13742-w. PubMed DOI PMC

Fernández-Giménez E., Martínez M., Sánchez-García R., Marabini R., Ramírez-Aportela E., Conesa P., Carazo J.M., Sorzano C.Ó.S. Cryo-EM density maps adjustment for subtraction, consensus and sharpening. J. Struct. Biol. 2021;213:107780. doi: 10.1016/j.jsb.2021.107780. PubMed DOI

Sorzano C.Ó.S., Vargas J., Otón J., Abrishami V., de la Rosa-Trevín J.M., del Riego S., Fernández-Alderete A., Martínez-Rey C., Marabini R., José M.C. Fast and accurate conversion of atomic models into electron density maps. AIMS Biophys. 2015;2:8–20. doi: 10.3934/biophy.2015.1.8. DOI

Martínez M., Jiménez-Moreno A., Maluenda D., Ramírez-Aportela E., Melero R., Cuervo A., Conesa P., del Caño L., Fonseca Y., Sánchez-García R., et al. Integration of Cryo-EM Model Building Software in Scipion. J. Chem. Inf. Model. 2020;60:2533–2540. doi: 10.1021/acs.jcim.9b01032. PubMed DOI

Ramírez-Aportela E., Maluenda D., Fonseca Y., Conesa P., Marabini R., Heymann J.B., Carazo J.M., Sorzano C.Ó.S. FSC-Q: A CryoEM map-to-atomic model quality validation based on the local Fourier shell correlation. Nat. Commun. 2021;12:42. doi: 10.1038/s41467-020-20295-w. PubMed DOI PMC

Bharat T., Zbaida D., Eisenstein M., Frankenstein Z., Mehlman T., Weiner L., Sorzano C.Ó.S., Barak Y., Albeck S., Briggs J., et al. Variable Internal Flexibility Characterizes the Helical Capsid Formed by Agrobacterium VirE2 Protein on Single-Stranded DNA. Structure. 2013;21:1158–1167. doi: 10.1016/j.str.2013.04.027. PubMed DOI

Fribourg P.F., Chami M., Sorzano C.Ó.S., Gubellini F., Marabini R., Marco S., Jault J.M., Lévy D. 3D Cryo-Electron Reconstruction of BmrA, a Bacterial Multidrug ABC Transporter in an Inward-Facing Conformation and in a Lipidic Environment. J. Mol. Biol. 2014;426:2059–2069. doi: 10.1016/j.jmb.2014.03.002. PubMed DOI

Condezo G.N., Marabini R., Ayora S., Carazo J.M., Alba R., Chillón M., San Martín C. Structures of Adenovirus Incomplete Particles Clarify Capsid Architecture and Show Maturation Changes of Packaging Protein L1 52/55k. J. Virol. 2015;89:9653–9664. doi: 10.1128/JVI.01453-15. PubMed DOI PMC

Ljubetič A., Lapenta F., Gradišar H., Drobnak I., Aupič J., Strmšek Ž., Lainšček D., Hafner-Bratkovič I., Majerle A., Krivec N., et al. Design of coiled-coil protein-origami cages that self-assemble in vitro and in vivo. Nat. Biotechnol. 2017;35:1094–1101. doi: 10.1038/nbt.3994. PubMed DOI

Albanese P., Melero R., Engel B.D., Grinzato A., Berto P., Manfredi M., Chiodoni A., Vargas J., Sorzano C.Ó.S., Marengo E., et al. Pea PSII-LHCII supercomplexes form pairs by making connections across the stromal gap. Sci. Rep. 2017;7:10067. doi: 10.1038/s41598-017-10700-8. PubMed DOI PMC

Alvarez-Cabrera A.L., Delgado S., Gil-Carton D., Mortuza G.B., Montoya G., Sorzano C.Ó.S., Tang T.K., Carazo J.M. Electron Microscopy Structural Insights into CPAP Oligomeric Behavior: A Plausible Assembly Process of a Supramolecular Scaffold of the Centrosome. Front. Mol. Biosci. 2017;4:17. doi: 10.3389/fmolb.2017.00017. PubMed DOI PMC

Silva S.T.N., Brito J.A., Arranz R., Sorzano C.Ó.S., Ebel C., Doutch J., Tully M.D., Carazo J.M., Carrascosa J.L., Matias P.M., et al. X-ray structure of full-length human RuvB-Like 2–mechanistic insights into coupling between ATP binding and mechanical action. Sci. Rep. 2018;8:13726. doi: 10.1038/s41598-018-31997-z. PubMed DOI PMC

Peschiera I., Giuliani M., Giusti F., Melero R., Paccagnini E., Donnarumma D., Pansegrau W., Carazo J.M., Sorzano C.Ó.S., Scarselli M., et al. Structural basis for cooperativity of human monoclonal antibodies to meningococcal factor H-binding protein. Commun. Biol. 2019;2:241. doi: 10.1038/s42003-019-0493-4. PubMed DOI PMC

Melero R., Sorzano C.Ó.S., Foster B., Vilas J.L., Martínez M., Marabini R., Ramírez-Aportela E., Sánchez-García R., Herreros D., del Caño L., et al. Continuous flexibility analysis of SARS-CoV-2 spike prefusion structures. IUCrJ. 2020;7:1059–1069. doi: 10.1107/S2052252520012725. PubMed DOI PMC

Lapenta F., Aupič J., Vezzoli M., Strmšek Ž., Da Vela S., Svergun D.I., Carazo J.M., Melero R., Jerala R. Self-assembly and regulation of protein cages from pre-organised coiled-coil modules. Nat. Commun. 2021;12:939. doi: 10.1038/s41467-021-21184-6. PubMed DOI PMC

Sorzano C.Ó.S., Marabini R., Vargas J., Otón J., Cuenca-Alba J., Quintana A., de la Rosa-Trevín J.M., Carazo J.M. Computational Methods for Three-Dimensional Microscopy Reconstruction. Springer; New York, NY, USA: 2013. Interchanging Geometry Conventions in 3DEM: Mathematical Context for the Development of Standards; pp. 7–42. DOI

Sorzano C.Ó.S., Vargas J., Otón J., de la Rosa-Trevín J.M., Vilas J.L., Kazemi M., Melero R., del Caño L., Cuenca J., Conesa P., et al. A Survey of the Use of Iterative Reconstruction Algorithms in Electron Microscopy. BioMed Res. Int. 2017;2017:6482567. doi: 10.1155/2017/6482567. PubMed DOI PMC

Sorzano C.Ó.S., Vargas J., Otón J., Abrishami V., de la Rosa-Trevín J.M., Gómez-Blanco J., Vilas J.L., Marabini R., Carazo J.M. A review of resolution measures and related aspects in 3D Electron Microscopy. Prog. Biophys. Mol. Biol. 2017;124:1–30. doi: 10.1016/j.pbiomolbio.2016.09.005. PubMed DOI

Sorzano C.Ó.S., Jiménez-Moreno A., Mota J., Vilas J.L., Maluenda D., Martínez M., Ramírez-Aportela E., Majtner T., Segura J., Sánchez-García R., et al. Survey of the analysis of continuous conformational variability of biological macromolecules by electron microscopy. Acta Crystallogr. Sect. Struct. Biol. Commun. 2019;75:19–32. doi: 10.1107/S2053230X18015108. PubMed DOI PMC

Maluenda D., Majtner T., Horvath P., Vilas J.L., Jiménez-Moreno A., Mota J., Ramírez-Aportela E., Sánchez-García R., Conesa P., del Caño L., et al. Flexible workflows for on-the-fly electron-microscopy single-particle image processing using Scipion. Acta Crystallogr. Sect. D Struct. Biol. 2019;75:882–894. doi: 10.1107/S2059798319011860. PubMed DOI PMC

Vilas J.L., Vargas J., Martínez M., Ramirez-Aportela E., Melero R., Jiménez-Moreno A., Garduño E., Conesa P., Marabini R., Maluenda D., et al. Re-examining the spectra of macromolecules. Current practice of spectral quasi B-factor flattening. J. Struct. Biol. 2020;209:107447. doi: 10.1016/j.jsb.2020.107447. PubMed DOI

Vilas J.L., Heymann J., Tagare H.D., Ramirez-Aportela E., Carazo J.M., Sorzano C.Ó.S. Local resolution estimates of cryoEM reconstructions. Curr. Opin. Struct. Biol. 2020;64:74–78. doi: 10.1016/j.sbi.2020.06.005. PubMed DOI PMC

Sorzano C.Ó.S., Carazo J.M. Principal component analysis is limited to low-resolution analysis in cryoEM. Acta Crystallogr. Sect. D Struct. Biol. 2021;77:835–839. doi: 10.1107/S2059798321002291. PubMed DOI PMC

Sorzano C.Ó.S., Semchonok D., Lin S.C., Lo Y.C., Vilas J.L., Jiménez-Moreno A., Gragera M., Vacca S., Maluenda D., Martínez M., et al. Algorithmic robustness to preferred orientations in single particle analysis by CryoEM. J. Struct. Biol. 2021;213:107695. doi: 10.1016/j.jsb.2020.107695. PubMed DOI

Sorzano C.Ó.S., Jiménez-Moreno A., Maluenda D., Ramírez-Aportela E., Martínez M., Cuervo A., Melero R., Conesa J.J., Sánchez-García R., Střelák D., et al. Image Processing in Cryo-Electron Microscopy of Single Particles: The Power of Combining Methods. Struct. Proteom. 2021;2305:257–289. doi: 10.1007/978-1-0716-1406-8_13. PubMed DOI

Jiménez-Moreno A., del Caño L., Martínez M., Ramírez-Aportela E., Cuervo A., Melero R., Sánchez-García R., Střelák D., Fernández-Giménez E., de Isidro-Gómez F., et al. Cryo-EM and Single-Particle Analysis with Scipion. J. Vis. Exp. 2021;171:e62261. doi: 10.3791/62261. PubMed DOI

Petrovič F., Střelák D., Hozzová J., Ol’ha J., Trembecký R., Benkner S., Filipovič J. A benchmark set of highly-efficient CUDA and OpenCL kernels and its dynamic autotuning with Kernel Tuning Toolkit. Future Gener. Comput. Syst. 2020;108:161–177. doi: 10.1016/j.future.2020.02.069. DOI

Střelák D., Filipovič J. Performance Analysis and Autotuning Setup of the CuFFT Library; Proceedings of the 2nd Workshop on Autotuning and Adaptivity Approaches for Energy Efficient HPC Systems (ANDARE ’18); Limassol, Cyprus. 4 November 2018; New York, NY, USA: Association for Computing Machinery; 2018. DOI

Performance and Quality Comparison of Movie Alignment Software for Cryogenic Electron Microscopy

Scipion3: A workflow engine for cryo-electron microscopy image processing and structural biology