Systems biology offers a holistic perspective where individual proteins are viewed as elements in a network of protein-protein interactions, in which the proteins have contextual functions within functional modules. In order to facilitate the identification and analysis of such modules, we here propose novel approaches that combine knowledge, in terms of Gene Ontology annotation with network topology information. The majority of previous methods for identifying modules in protein interaction networks are based solely on analysing topological features of the networks. In contrast, we propose the use of integrated functionally informed clustering coefficients to identitY biologically plausible network modules. The main part of the thesis is focused on the method named SWEMODE (Semantic WEights for MODule Elucidation), which uses a weighted clustering coefficient to identify network functional modules. We demonstrate that the proposed methods are able to identify the key functional modules in protein interaction networks. We also investigate the functional and topological features of the proteins that are involved in mul~iple modules, as well as their role in the interconnectivity between modules: The -results indicate that the majority of, so called multi-modular proteins are involved in the assembly and arrangement of cell structures, such as the cell wall and cell envelope.