Understanding biological systems The two faces of systems biology Sndor Pongor Protein Structure and Bioinformatics, ICGEB, Trieste What are systems? n Any part of reality that can be separated from the environment (boundary). A community in an environment. n Consist of interacting parts n Interact with the environrment (inputs, outputs) n System models are generalizations of reality. n Have a structure that is defined by parts and processes n Parts have functional as well as structural relationships between each other. Reading in an unknown language Molecular biology Systems biology Traditional wet lab methods High throughput technologies Approaches based on data collection Traditional wet lab methods High throughput technologies Approaches based on data collection Holistic models Topological models Dynamic models (flux, transport) Face 1: Bioinformatics n Cluster data and build recognizers for clusters n Interpret raw data with recognizers n Combine recognizer outputs using ontologies, higher order descriptions n Mark unidentified data for human evaluation Face 2: Systems models n Robust against failure (resilience) n Change upon environmental conditions (evolution and learning) n Gracious decay and sudden collapse The strength of simple models I. Turing, Minsky, Rosenblatt, Hopfield, Kohonen etc etc The strength of simple models I. Turing, Minsky, Rosenblatt, Hopfield, Kohonen etc etc The strength of simple models I. Turing, Minsky, Rosenblatt, Hopfield, Kohonen etc etc The strength of simple models I. Turing, Minsky, Rosenblatt, Hopfield, Kohonen etc etc The strength of simple models II. Jean-Louis Deneubourg, Marco Dorigo The strength of simple models II. Jean-Louis Deneubourg, Marco Dorigo The strength of simple models II. Jean-Louis Deneubourg, Marco Dorigo The strength of simple models II. Jean-Louis Deneubourg, Marco Dorigo The strength of simple models II. Jean-Louis Deneubourg, Marco Dorigo Bacterium communities n What is the simplest model that imitates communities? signal1 Signal emitter Sensor Metabolism, swarming n What is the simplest model that imitates community behaviour? n Density sensing n Signal tracking The changing faces of systems biology n Not a method but a paradigm (general approach of thinking) n It builds on new methods and has created new methods n The bottom up approach builds on high throughput data and bioinformatics n The top down approach builds on brutally simplified models. n There is a big gap between the two n Even unrealistic models can have technical applications n There is no free lunch: everything in biology has to be confirmed by experiment