Single-cell morphological data reveals signaling network architecture

[摘要] (cont.) Next, we focus on RhoGTPases and RhoGTPase Activating Proteins (RhoGAPs) in Drosophila., where by using basic knowledge of network architecture we apply our techniques to detect signaling relationships. 3) To integrate expression data with high-throughput morphological data to study the mechanisms for determination of cell morphology. We utilize morphological and microarray data from fly screens. By comparing expression data between control treatment conditions and treatment conditions displaying morphological phenotypes (e.g. high population variability), we identify genes and pathways correlated with this class distinction, thereby validating our previous studies and providing further insight into the determination of morphology. A key challenge in systems biology is to analyze emerging high-throughput image-based data to understand how cellular phenotypes are genetically encoded. Our work makes significant contributions to the literature on high-throughput morphological study and describes a path for future investigation.

[发布机构] Massachusetts Institute of Technology