Modern biology is evolving quickly, as new genomic and imaging methods are giving us new windows into basic biology across multiple scales and modalities. But if we want to make our science more robust, more scalable, and more reproducible, the major bottleneck is computation. Making progress will require new tools, and new cultural practices focused on data sharing, interdisciplinary collaboration, modular analysis, and open knowledge dissemination. Jeremy Freeman offers an overview of a growing ecosystem of solutions to this challenge—many of which involve Jupyter—in the context of exciting scientific projects past, present, and future.
Jeremy Freeman is manager of computational biology at the Chan Zuckerberg Initiative, where he is helping develop efforts to support and accelerate basic research with tools for analysis, visualization, and collaborative sharing of data and knowledge. Previously, he ran a neuroscience research lab for several years. A scientist at the intersection of biology and technology, Jeremy wants to understand how biological systems work and use that understanding to benefit both human health and the design of intelligent systems. He is passionate about open source and open science and bringing scientists and engineers together across a range of fields.
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