title: Generalized analysis of experimental data for interrelated biological measurements.
abstract: Important biological mechanisms, such as signal transduction and gene expression, are mediated by numerous interacting multifunctional molecules, whose expression and activation are tightly regulated in space and time in response to stimuli. In order to describe the network of functional inter-relationships that govern such mechanisms, we use simple algorithms to interpret multiple variable measurements, identify the prominent participants, evaluate their interactions and obtain a 'functional fingerprint' of cell behaviour. Dynamic measurements of responses yield hierarchical information about causal relations in the underlying pathway. As a proof of principles we apply this approach to phosphorylation assays in protein gels, probing hormone and insulin signalling.
authors.affiliation: Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot 76100, Israel. zvi.kam@weizmann.ac.il
authors.forename: Zvi
authors.initials: Z
authors.lastname: Kam
mesh_terms: D000465:Algorithms; D003627:Data Interpretation, Statistical; D015180:Electrophoresis, Gel, Two-Dimensional; D066246:ErbB Receptors / Q000737:chemistry; D007328:Insulin / Q000737:chemistry; D008954:Models, Biological; D015999:Multivariate Analysis; D016571:Neural Networks, Computer; D010766:Phosphorylation; D015398:Signal Transduction
chemical_list: D007328:Insulin; D066246:ErbB Receptors