Several techniques are employed in data manipulation for cancer research. Statistical methods are commonly used to identify significant patterns and associations. [Machine learning](#) algorithms can predict outcomes and classify patient data. Bioinformatics tools are used to analyze genomic and proteomic data, while natural language processing (NLP) can extract relevant information from clinical notes and literature. Data visualization tools help in interpreting complex datasets and communicating findings effectively.
