Information Transfer in Transcription Networks

Abstract

A common and important feature in biological systems is information transfer, where the information carried by one molecule is transferred to another to control cellular functions, such as in intracellular signal transduction, gene expression regulation, and neurotransmission. Coarse-grain mass and energy balances are insufficient to describe these processes, while fine-grain molecular simulations are often too cumbersome to generate insight. A proper framework for characterizing information transfer is needed. To this end, we defined information flux and the driving force, and developed a method, termed Network Component Analysis (NCA), as a general tool for analyzing information transfer in bi-partite networks. In transcriptional regulation, this approach determines the transcription factor activities from DNA microarray data, and provides information for uncovering further molecular details in signal transduction. NCA also provides insight into the design and evolution of bi-partite networks for information transfer.