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Published Erratum
. 2022 Nov 8;18(11):e1010644.
doi: 10.1371/journal.pcbi.1010644. eCollection 2022 Nov.

Correction: cytoNet: Spatiotemporal network analysis of cell communities

PLOS Computational Biology
Published Erratum

Correction: cytoNet: Spatiotemporal network analysis of cell communities

PLOS Computational Biology. PLoS Comput Biol. .

Abstract

[This corrects the article DOI: 10.1371/journal.pcbi.1009846.].

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Figures

Fig 1
Fig 1. cytoNet workflow.
(a) The cytoNet pipeline begins with masks and optionally microscope images, which can be static immunofluorescence images or calcium image sequences. (b) Spatial proximity is determined either by measuring shared pixels between cell pairs–type I networks, or by comparing the distance between cell centroids to a threshold distance–type II networks (right panel). Functional networks are estimated from correlations in calcium time series data. (c) Cell community descriptors provide information on local neighborhood characteristics of individual cells, like degree and centrality measures, and global neighborhood characteristics like modularity and path lengths.
See this image and copyright information in PMC

Erratum for

  • cytoNet: Spatiotemporal network analysis of cell communities.
    Mahadevan AS, Long BL, Hu CW, Ryan DT, Grandel NE, Britton GL, Bustos M, Gonzalez Porras MA, Stojkova K, Ligeralde A, Son H, Shannonhouse J, Robinson JT, Warmflash A, Brey EM, Kim YS, Qutub AA. Mahadevan AS, et al. PLoS Comput Biol. 2022 Jun 13;18(6):e1009846. doi: 10.1371/journal.pcbi.1009846. eCollection 2022 Jun. PLoS Comput Biol. 2022. PMID: 35696439 Free PMC article.

References

    1. Mahadevan AS, Long BL, Hu CW, Ryan DT, Grandel NE, et al.. (2022) cytoNet: Spatiotemporal network analysis of cell communities. PLOS Computational Biology 18(6): e1009846. 10.1371/journal.pcbi.1009846 - DOI - PMC - PubMed

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