Cell lines became an essential asset for biomedical research through the numerous practical advantages they offer over other types of cell cultures. They are used in a wide range of experiments in the different omics fields, which entered in a high-throughput era in recent years with the emergence of new technology and instrumentation. Cell line cross-contamination and misidentification is however known to impede the reliability and reproducibility of experimental results. The large-scale generation of biological data also raises many bioinformatics challenges mainly spanning issues of formats, storage, representation, and interpretation. This thesis focuses on the development of bioinformatics software to address these problems, providing tools for the analysis and interpretation of omics data to the scientific community. Three distinct applications were developed in the course of this thesis, which led to the publication of four related scientific articles.