Predicting gene regulatory networks by combining spatial and temporal gene expression data in Arabidopsis root stem cells

Proc. Natl. Acad. Sci. USA. GENIST (gene regulatory network inference from spatiotemporal data) is a new algorithm developed by de Luis Balaguer et al to predict new gene interactions and transcriptional regulators (available at The algorithm combines inference of a dynamic Bayesian network (DBN) and clustering using principal component analysis (PCA) using spatial and temporal expression data. In silico testing revealed that GENIST out-performed other methods. GENIST was experimentally validated by the successful prediction of a root stem cell regulator in Arabidopsis. Proc. Natl Acad. Sci. USA 10.1073/pnas.1707566114