The contemporary life science research paradigm is undergoing a major transformation. Along with the continuous integration between biotechnology and information technology, the evolution of research beliefs, methods, and cultures have jointly promoted the paradigm shift of life science research: research beliefs have shifted from reductionism to holism, and the dialectical integration of the two has been realized with the help of network thinking; the rise of deep learning has led to the realization of double leaps in efficiency and precision of computational simulation and modeling methods under the strong coupling of data, algorithms, and computing power; and the organization and management modes have gradually become data-centric, platform-based, and ecological, awakening the advocacy and support of an open scientific culture. The new paradigm of data-driven life science research has accelerated the process of scientific discovery and expanded the scope of scientific discovery, and at the same time brought about many biotechnological and ethical challenges.