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Cryo-electron microscopy: mathematical foundations and algorithms

Total Cost €


EC-Contrib. €






Project "CRYOMATH" data sheet

The following table provides information about the project.


Organization address
address: RAMAT AVIV
city: TEL AVIV
postcode: 69978

contact info
title: n.a.
name: n.a.
surname: n.a.
function: n.a.
email: n.a.
telephone: n.a.
fax: n.a.

 Coordinator Country Israel [IL]
 Total cost 1˙751˙250 €
 EC max contribution 1˙751˙250 € (100%)
 Programme 1. H2020-EU.1.1. (EXCELLENT SCIENCE - European Research Council (ERC))
 Code Call ERC-2016-COG
 Funding Scheme ERC-COG
 Starting year 2017
 Duration (year-month-day) from 2017-03-01   to  2022-02-28


Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    TEL AVIV UNIVERSITY IL (TEL AVIV) coordinator 1˙751˙250.00


 Project objective

The importance of understanding the functions of the basic building blocks of life, such as proteins, cannot be overstated (as asserted by two recent Nobel prizes in Chemistry), as this understanding unravels the mechanisms that control all organisms. The critical step towards such an understanding is to reveal the structures of these building blocks. A leading method for resolving such structures is cryo-electron microscopy (cryo-EM), in which the structure of a molecule is recovered from its images taken by an electron microscope, by using sophisticated mathematical algorithms (to which my group has made several key mathematical and algorithmic contributions). Due to hardware breakthroughs in the past three years, cryo-EM has made a giant leap forward, introducing capabilities that until recently were unimaginable, opening an opportunity to revolutionize our biological understanding. As extracting information from cryo-EM experiments completely relies on mathematical algorithms, the method’s deep mathematical challenges that have emerged must be solved as soon as possible. Only then cryo-EM could realize its nearly inconceivable potential. These challenges, for which no adequate solutions exist (or none at all), focus on integrating information from huge sets of extremely noisy images reliability and efficiently. Based on the experience of my research group in developing algorithms for cryo-EM data processing, gained during the past eight years, we will address the three key open challenges of the field – a) deriving reliable and robust reconstruction algorithms from cryo-EM data, b) developing tools to process heterogeneous cryo-EM data sets, and c) devising validation and quality measures for structures determined from cryo-EM data. The fourth goal of the project, which ties all goals together and promotes the broad interdisciplinary impact of the project, is to merge all our algorithms into a software platform for state-of-the-art processing of cryo-EM data.


year authors and title journal last update
List of publications.
2020 Amitay Eldar, Boris Landa, Yoel Shkolnisky
KLT picker: Particle picking using data-driven optimal templates
published pages: 107473, ISSN: 1047-8477, DOI: 10.1016/j.jsb.2020.107473
Journal of Structural Biology 2020-03-05
2019 Gabi Pragier, Yoel Shkolnisky
A common lines approach for ab-initio modeling of cyclically-symmetric molecules
published pages: , ISSN: 0266-5611, DOI: 10.1088/1361-6420/ab2fb2
Inverse Problems 2019-08-29
2019 Rami Katz, Yoel Shkolnisky
Sampling and approximation of bandlimited volumetric data
published pages: 235-247, ISSN: 1063-5203, DOI: 10.1016/j.acha.2018.11.003
Applied and Computational Harmonic Analysis 47/1 2019-08-29
2019 Roy Mitz, Nir Sharon, Yoel Shkolnisky
Symmetric Rank-One Updates from Partial Spectrum with an Application to Out-of-Sample Extension
published pages: 973-997, ISSN: 0895-4798, DOI: 10.1137/18m1172120
SIAM Journal on Matrix Analysis and Applications 40/3 2019-08-29
2019 Yariv Aizenbud, Yoel Shkolnisky
A max-cut approach to heterogeneity in cryo-electron microscopy
published pages: 1004-1029, ISSN: 0022-247X, DOI: 10.1016/j.jmaa.2019.06.064
Journal of Mathematical Analysis and Applications 479/1 2019-08-29
2017 Ido Greenberg, Yoel Shkolnisky
Common lines modeling for reference free Ab-initio reconstruction in cryo-EM
published pages: 106-117, ISSN: 1047-8477, DOI: 10.1016/j.jsb.2017.09.007
Journal of Structural Biology 200/2 2019-05-08
2018 Boris Landa, Yoel Shkolnisky
The Steerable Graph Laplacian and its Application to Filtering Image Datasets
published pages: 2254-2304, ISSN: 1936-4954, DOI: 10.1137/18M1169394
SIAM Journal on Imaging Sciences 11/4 2019-04-18

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