eLifeDevelopmental BiologyPeer-reviewed journal article
MorphoGraphX 2.0: Providing context for biological image analysis with positional information
Soeren StraussiD, Adam RunionsiD, Brendan LaneiD, Dennis EschweileriD, Namrata Bajpai, Nicola TrozziiD, Anne‐Lise Routier‐KierzkowskaiD, Saiko Yoshida, Sylvia Rodrigues da SilveiraiD, Athul VijayaniD, Rachele TofanelliiD, Mateusz MajdaiD, Emillie Echevin, Constance Le GloaneciD, Hana Bertrand-Rakusova, Milad Adibi, Kay SchneitziD, George Bassel, Daniel KierzkowskiiD, Johannes StegmaieriD, Miltos TsiantisiD, Richard S. SmithiD
Abstract
Positional information is a central concept in developmental biology. In developing organs, positional information can be idealized as a local coordinate system that arises from morphogen gradients controlled by organizers at key locations. This offers a plausible mechanism for the integration of the molecular networks operating in individual cells into the spatially-coordinated multicellular responses necessary for the organization of emergent forms. Understanding how positional cues guide morphogenesis requires the quantification of gene expression and growth dynamics in the context of their underlying coordinate systems. Here we present recent advances in the MorphoGraphX software (Barbier de Reuille et al. eLife 2015;4:e05864) that implement a generalized framework to annotate developing organs with local coordinate systems. These coordinate systems introduce an organ-centric spatial context to microscopy data, allowing gene expression and growth to be quantified and compared in the context of the positional information thought to control them.
- assay: imaging
- research focus: cell type annotation
- research focus: spatial domain detection
- research focus: dimensionality reduction
- approach: experimental assay
- Citations
- 124
- FWCI
- 10.74
- Field percentile
- top 1%
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