The main objective of the Computational Biology Laboratory (DLab) is to produce multiscale computational models to gain insights on the fundamental structures and dynamics underlying complex biological phenomena. To do so, we use and produce computer-based simulation tools by combining advanced mathematical modeling, thermodynamics, physics and chemistry, together with high performance computing (HPC) techniques. Whilst our main goal is to produce a tool for multiscale simulation of biological systems, we also study biological processes at single scales. At the microscale (atomic level), we use tools from molecular modeling and molecular simulations to understand the physicochemical properties that govern intercellular communication mediated by gap-junction channels. At the nanoscale, we study the structure and function of water, and molecular recognition and signal transduction processes mediated by proteins. At the mesoscale (cell level) we use network topology and machine learning techniques to infer and characterize cell signaling networks, gene regulation and neural coordination. At the macroscale (population level) we use modeling based on stochastic rules to study the behavioral adaptation of artificial populations (agents) due to the spread of infectious diseases and information.