Integrative analysis refers to the combination of different data sources, methods, and perspectives in order to gain a more comprehensive understanding of a research topic or problem. This approach involves synthesizing information from diverse fields, such as biology, chemistry, physics, and computer science, to uncover hidden patterns, relationships, and insights that may not be apparent when considering each source of data in isolation. Integrative analysis often involves the use of computational tools and algorithms to process and analyze large and complex datasets. By integrating multiple types of data, researchers can generate more robust and reliable results, leading to new discoveries and breakthroughs in various disciplines. This holistic approach can help researchers to identify novel connections between seemingly unrelated pieces of information and advance our understanding of complex systems and phenomena.