Cancer is one of the non-communicable diseases that is affecting the whole world. The application of bioinformatics is expanding in the era of precision medicine and new technologies are being developed to address the challenging diagnosis, treatment, and management of the different types of cancer. The use of bioinformatics is beneficial for clinicians to predict the response of the drug given as treatment, targeting therapies for different types of cancers, development of disease-specific biomarkers and identifying pharmacological targets. The merging of bioinformatics and high-throughput genomic technologies has enabled a thorough tumour profiling, signalling a paradigm change in cancer research. Precision medicine benefits from this integration, which serves as a catalyst for the conversion of massive genetic data into useful insights. This chapter emphasizes the integration of bioinformatics and high throughput data, which serves as a catalyst for the conversion of large genetic data into useful information. The discussion is focused on the use of artificial intelligence and machine learning to identify novel therapeutic targets and novel biomarkers. In order to illustrate how integrated bioinformatics is contributing to precision medicine in clinical practice, this chapter includes a section highlighting its role in stratification, treatment selection, and monitoring therapeutic responses. The chapter concludes with challenges and future directions in integrated bioinformatics, highlighting the need for standardization, interoperability, and ethical considerations.