English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

The proper functional development of a multicellular organism depends on an intricate network of interacting genes that are expressed in accurate temporal and spatial patterns across different tissues. Complex inhibitory and excitatory interactions among genes control the territorial differences that explain specialized cell fates, embryo polarization and tissues architecture in metazoans. Given the nature of the regulatory gene networks, similarity of expression patterns can identify genes with similar roles. The inference and analysis of the gene interaction networks through complex network tools can reveal important aspects of the biological system modeled. Here we suggest an image analysis pipeline to quantify co-localization patterns in in situ hybridization images of Drosophila embryos and, based on these patterns, infer gene networks. We analyze the spatial dispersion of the gene expression and show the gene interaction networks for different developmental stages. Our results suggest that the inference of developmental networks based on spatial expression data is biologically relevant and represents a potential tool for the understanding of animal development.

A methodology to infer gene networks from spatial patterns of expression – an application to fluorescence in situ hybridization images