Moment-based metrics for molecules computable from cryo-EM images
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arXiv
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| Main Authors: | , , , , , , |
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| Format: | Preprint |
| Published: |
2024
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| _version_ | 1866914655425789952 |
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| author | Zhang, Andy Mickelin, Oscar Kileel, Joe Verbeke, Eric J. Marshall, Nicholas F. Gilles, Marc Aurèle Singer, Amit |
| author_facet | Zhang, Andy Mickelin, Oscar Kileel, Joe Verbeke, Eric J. Marshall, Nicholas F. Gilles, Marc Aurèle Singer, Amit |
| contents | Single particle cryogenic electron microscopy (cryo-EM) is an imaging technique capable of recovering the high-resolution 3-D structure of biological macromolecules from many noisy and randomly oriented projection images. One notable approach to 3-D reconstruction, known as Kam's method, relies on the moments of the 2-D images. Inspired by Kam's method, we introduce a rotationally invariant metric between two molecular structures, which does not require 3-D alignment. Further, we introduce a metric between a stack of projection images and a molecular structure, which is invariant to rotations and reflections and does not require performing 3-D reconstruction. Additionally, the latter metric does not assume a uniform distribution of viewing angles. We demonstrate uses of the new metrics on synthetic and experimental datasets, highlighting their ability to measure structural similarity. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2401_15183 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Moment-based metrics for molecules computable from cryo-EM images Zhang, Andy Mickelin, Oscar Kileel, Joe Verbeke, Eric J. Marshall, Nicholas F. Gilles, Marc Aurèle Singer, Amit Biomolecules Image and Video Processing Single particle cryogenic electron microscopy (cryo-EM) is an imaging technique capable of recovering the high-resolution 3-D structure of biological macromolecules from many noisy and randomly oriented projection images. One notable approach to 3-D reconstruction, known as Kam's method, relies on the moments of the 2-D images. Inspired by Kam's method, we introduce a rotationally invariant metric between two molecular structures, which does not require 3-D alignment. Further, we introduce a metric between a stack of projection images and a molecular structure, which is invariant to rotations and reflections and does not require performing 3-D reconstruction. Additionally, the latter metric does not assume a uniform distribution of viewing angles. We demonstrate uses of the new metrics on synthetic and experimental datasets, highlighting their ability to measure structural similarity. |
| title | Moment-based metrics for molecules computable from cryo-EM images |
| topic | Biomolecules Image and Video Processing |
| url | https://arxiv.org/abs/2401.15183 |