Powered by OpenAIRE graph
Found an issue? Give us feedback
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ ZENODOarrow_drop_down
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Preprint . 2024
License: CC BY
Data sources: ZENODO
ZENODO
Preprint . 2024
License: CC BY
Data sources: Datacite
ZENODO
Preprint . 2024
License: CC BY
Data sources: Datacite
versions View all 2 versions
addClaim

A review of computational reconstruction of interaction in superresolution microscopy: from colocalization to closing the multichannel gap

Authors: Cardoen, Ben; Ben Yedder, Hanene; Nabi, Ivan Robert; Hamarneh, Ghassan;

A review of computational reconstruction of interaction in superresolution microscopy: from colocalization to closing the multichannel gap

Abstract

AbstractCellular function is defined by pathways that, in turn, are determined by distance-mediated interactions between and within subcel-lular organelles, protein complexes, and macromolecular structures. Multichannel Super Resolution Microscopy (SRM) is uniquelyplaced to quantify distance-mediated interactions at the nanometer scale with its ability to label individual biological targets withindependent markers that fluoresce in different spectra. We review novel computational methods that quantify interaction from mul-tichannel SRM data in both point-cloud and voxel form to meet the increasing adoption of multichannel SRM in life sciences. SRMspecific factors that can compromise interaction analysis are discussed in detail. Different classes of interactions are decomposedbased on distinct representative cell biology use cases, the underappreciated non-linear physics of their scale, and the developmentof specialized methods for those use case. An abstract mathematical model is introduced to facilitate the comparison and evaluationof interaction reconstruction methods and to quantify the computational bottlenecks. We discuss the different strategies for valida-tion of interaction analysis results with sparse or incomplete ground truth data. Finally, evolving trends and future directions arepresented, highlighting the ‘multichannel gap’, where interaction analysis is trailing behind the rapid increase in novel multichannelSRM acquisitions.This preprint was submitted to Cell Press Patterns 10/10/2024, it is derived in part from work published in the first author's thesis (see pdf).

Keywords

Confocal microscopy, Microscopy, Super resolution microscopy, Electron microscopy, Statistics and probability, Superresolution Microscopy, Colocalization, Biological interactions, Unsupervised learning, Clustering

  • BIP!
    Impact byBIP!
    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    0
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Average
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Average
Powered by OpenAIRE graph
Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green