Data integration in genomics involves combining and analyzing different types of data to create a unified framework. This can include:
DNA sequencing data to identify mutations and structural variations. RNA sequencing data to study gene expression profiles. Epigenetic data to understand DNA methylation and histone modifications. Proteomic data to analyze protein expression and post-translational modifications.
Advanced computational tools and algorithms are employed to integrate and analyze these diverse datasets, revealing complex interactions and pathways involved in cancer.
