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This work offers unique insight into how biology is evolving to meet the needs of data-intensive science. It examines the history of computational science and lessons learned, discusses the evolution of biology into a data-driven science, and addresses the challenges and complexities of modern, data-driven biology. Exploring the core technological and scientific challenges, including algorithmic and infrastructural requirements, the book analyzes common themes and differences between biology and other data-intensive sciences and highlights the future directions of the field and the skill sets that will be critical for future success.