Abstract   Computation is often seen as information processing. Many biological systems may be investigated in terms of information storage, signaling, and data processing networks. Much of this data processing activity is embodied in structural transformations in spatial scales ranging from the molecular to cellular networks. The biomedical sciences make use of an increasingly powerful arsenal of tools and technologies for obtaining structural data as well as details of mass transport and the chemical and electrical signals that underlie these fundamental biological processes. For example, new staining techniques combined with computer-based electron microscope tomography, permit the clear imaging of chromatin filaments in the cell nucleus and filament networks in the cytoplasmic and extracellular space via the electron microscope. The application of tomographic reconstruction software developed at the National Center for Microscopy and Imaging Research (NCMIR) enables detailed 3D reconstructions of the relevant biological structures and processes. In order to deal with fundamental issues related to information processing in biological systems, new data processing methods as well as advances in chemically sensitive probes and imaging technology must be applied across a wide range of spatial and temporal scales. One class of increasingly useful tools for modeling biological systems, evaluating imaging technologies and characterizing the fidelity of digital processing has its roots in theoretical investigations in statistical mechanics, which arise from the concepts of information and entropy. We review how concepts of information and entropy may give new perspectives on the flow of information within biological systems, as well as our instrumentation and computer processing.
['Albert Lawrence', 'Tsvi Katchalski', 'Alex Perez', 'Varda Lev-Ram', 'Daniela Boassa', 'Thomas J. Deerinck', 'Sebastien Phan', 'Steven T. Peltier', 'Mark H. Ellisman']
Biological Systems through the Informational Lens