As is typical of contemporary cutting-edge interdisciplinary fields, computational biology touches and impacts many disciplines ranging from fundamental studies in the areas of genomics, proteomics transcriptomics, lipidomics to practical applications such as personalized medicine, drug discovery, and synthetic biology. This editorial examines the multifaceted role computational biology plays. Using the tools of deep learning, it can make powerful predictions of many biological variables, which may not provide a deep understanding of what factors contribute to the phenomena. Alternatively, it can provide the how and the why of biological processes. Most importantly, it can help guide and interpret what experiments and biological systems to study.

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