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Lederman, Roy R; Andén, Joakim; Singer, Amit
Hyper-molecules: on the representation and recovery of dynamical structures for applications in flexible macro-molecules in cryo-EM Journal Article
In: Inverse Problems, vol. 36, no. 4, pp. 044005, 2020, ISSN: 0266-5611, 1361-6420.
Links | BibTeX | Tags: cryo-EM, heterogeneity, HyperMolecules, MCMC, Variational inference
@article{lederman_hyper-molecules_2020,
title = {Hyper-molecules: on the representation and recovery of dynamical structures for applications in flexible macro-molecules in cryo-EM},
author = {Roy R Lederman and Joakim Andén and Amit Singer},
url = {https://iopscience.iop.org/article/10.1088/1361-6420/ab5ede},
doi = {10.1088/1361-6420/ab5ede},
issn = {0266-5611, 1361-6420},
year = {2020},
date = {2020-04-01},
urldate = {2020-08-13},
journal = {Inverse Problems},
volume = {36},
number = {4},
pages = {044005},
keywords = {cryo-EM, heterogeneity, HyperMolecules, MCMC, Variational inference},
pubstate = {published},
tppubtype = {article}
}
Lederman, Roy R; Singer, Amit
Continuously heterogeneous hyper-objects in cryo-EM and 3-Đ movies of many temporal dimensions Technical Report
no. arXiv:1704.02899 [cs], 2017, (arXiv: 1704.02899).
Abstract | Links | BibTeX | Tags: Computer Science - Computer Vision and Pattern Recognition, cryo-EM, heterogeneity, HyperMolecules
@techreport{lederman_continuously_2017,
title = {Continuously heterogeneous hyper-objects in cryo-EM and 3-Đ movies of many temporal dimensions},
author = {Roy R Lederman and Amit Singer},
url = {http://arxiv.org/abs/1704.02899},
year = {2017},
date = {2017-04-01},
urldate = {2020-08-13},
number = {arXiv:1704.02899 [cs]},
abstract = {Single particle cryo-electron microscopy (EM) is an increasingly popular method for determining the 3-D structure of macromolecules from noisy 2-D images of single macromolecules whose orientations and positions are random and unknown. One of the great opportunities in cryo-EM is to recover the structure of macromolecules in heterogeneous samples, where multiple types or multiple conformations are mixed together. Indeed, in recent years, many tools have been introduced for the analysis of multiple discrete classes of molecules mixed together in a cryo-EM experiment. However, many interesting structures have a continuum of conformations which do not fit discrete models nicely; the analysis of such continuously heterogeneous models has remained a more elusive goal. In this manuscript, we propose to represent heterogeneous molecules and similar structures as higher dimensional objects. We generalize the basic operations used in many existing reconstruction algorithms, making our approach generic in the sense that, in principle, existing algorithms can be adapted to reconstruct those higher dimensional objects. As proof of concept, we present a prototype of a new algorithm which we use to solve simulated reconstruction problems.},
note = {arXiv: 1704.02899},
keywords = {Computer Science - Computer Vision and Pattern Recognition, cryo-EM, heterogeneity, HyperMolecules},
pubstate = {published},
tppubtype = {techreport}
}
Single particle cryo-electron microscopy (EM) is an increasingly popular method for determining the 3-D structure of macromolecules from noisy 2-D images of single macromolecules whose orientations and positions are random and unknown. One of the great opportunities in cryo-EM is to recover the structure of macromolecules in heterogeneous samples, where multiple types or multiple conformations are mixed together. Indeed, in recent years, many tools have been introduced for the analysis of multiple discrete classes of molecules mixed together in a cryo-EM experiment. However, many interesting structures have a continuum of conformations which do not fit discrete models nicely; the analysis of such continuously heterogeneous models has remained a more elusive goal. In this manuscript, we propose to represent heterogeneous molecules and similar structures as higher dimensional objects. We generalize the basic operations used in many existing reconstruction algorithms, making our approach generic in the sense that, in principle, existing algorithms can be adapted to reconstruct those higher dimensional objects. As proof of concept, we present a prototype of a new algorithm which we use to solve simulated reconstruction problems.