SYSPATHO focuses on the development of novel and generally applicable mathematical methods and algorithms for systems biology. These methods and algorithms will be applied to study the complex interactions of hepatitis C virus (HCV), a human-pathogenic virus of high medical relevance, with its host at the systems level. Using a multidisciplinary, integrative approach, PATHOSYS will (a) develop methods to analyze and integrate a wide variety of data from wet lab experiments, databases and biological literature, (b) develop and apply machine learning tools to reconstruct and study intracellular interaction networks from experimental data, (c) develop new and improve existing algorithms and mathematical methods for bottom-up modelling, to fit models to data, and to analyze the dynamic behaviour of models (d) generate new experimental data to gain novel insights into hepatitis C virus host interactions, and (e) use the newly developed methods and data to model and analyze HCV-host interactions at the systems level. Guided by biological data, PATHOSYS focuses on the design of novel algorithms and mathematical methods for systems biology, with the aim to provide generally applicable tools to elucidate biological processes. Based on developed models and using systems analysis, PATHOSYS will elucidate virus host interactions of Hepatitis C virus at an unprecedented level. As a direct spin-off, models and analysis methods developed in PATHOSYS will lead to the identification of new candidate host cell target genes applicable for the design of novel anti-viral drugs against hepatitis C. Targeting of host cell factors will reduce the likelihood for the development of therapy resistance and increase the chance for broad-spectrum antivirals. Inclusion of two SME partners will ensure exploitation of results generated in PATHOSYS and their transfer into industrial and pharmaceutical applications, thus strengthening economy and health care system in Europe.