ArticleComputer analysis of images and patterns : proceedings of the ... International Conference on Automatic Image Processing. International Conference on Automatic Image Processing2015
Efficient Extraction of Macromolecular Complexes from Electron Tomograms Based on Reduced Representation Templates.
Article in Computer analysis of images and patterns : proceedings of the ... International Conference on Automatic Image Processing. International Conference on Automatic Image Processing, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
6 citing papers in PubMed, 15 citations in OpenAlex.
- Deciphering the molecular mechanisms of actin cytoskeleton regulation in cell migration using cryo-EM.Biochemical Society transactions · 2023Review
- Quantitative Cryo-Electron Tomography.Frontiers in molecular biosciences · 2022Review
- High Rac1 activity is functionally translated into cytosolic structures with unique nanoscale cytoskeletal architecture.Proceedings of the National Academy of Sciences of the United States of America · 2019Article
- Improved deep learning-based macromolecules structure classification from electron cryo-tomograms.Machine vision and applications · 2018Article
- A convolutional autoencoder approach for mining features in cellular electron cryo-tomograms and weakly supervised coarse segmentation.Journal of structural biology · 2018Article
- Nano-scale actin-network characterization of fibroblast cells lacking functional Arp2/3 complex.Journal of structural biology · 2017Article
Corrections and comments
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
Abstract
Electron tomography is the most widely applicable method for obtaining 3D information by electron microscopy. In the field of biology it has been realized that electron tomography is capable of providing a complete, molecular resolution three-dimensional mapping of entire proteoms. However, to realize this goal, information needs to be extracted efficiently from these tomograms. Owing to extremely low signal-to-noise ratios, this task is mostly carried out manually. Standard template matching approaches tend to generate large amounts of false positives. We developed an alternative method for feature extraction in biological electron tomography based on reduced representation templates, approximating the search model by a small number of anchor points used to calculate the scoring function. Using this approach we see a reduction of about 50% false positives with matched-filter approaches to below 5%. At the same time, false negatives stay below 5%, thus essentially matching the performance one would expect from human operators.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.