The main goal of the project is to generate new hypotheses for the understanding and treatment of thyroid cancer with the help of Text Mining and Logical Modelling. Text Mining is used to extract information related to the molecular interactions for thyroid cancer from the biomedical literature (based on BioContext). The second step is to use the extracted information to construct a logical model for thyroid cancer and use it to make predictions about medically useful pathways or drug targets; the hypotheses formed in the second phase will be validated experimentally in the third year. This work is part of Chengkun’s PhD, with J-M. Schwartz, G. Brabant and G. Nenadic as supervisors.