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