Journal
GIGASCIENCE
Volume 8, Issue 10, Pages -Publisher
OXFORD UNIV PRESS
DOI: 10.1093/gigascience/giz127
Keywords
multicellular systems biology; data-driven; challenges; multidisciplinary; open source; open data; data standards; big data; simulations; machine learning
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Funding
- Breast Cancer Research Foundation
- Jayne Koskinas Ted Giovanis Foundation for Health and Policy
- National Science Foundation [1720625]
- National Cancer Institute [U01-CA232137-01, 1R01CA180149, 5U54CA143907]
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Increasingly sophisticated experiments, coupled with large-scale computational models, have the potential to systematically test biological hypotheses to drive our understanding of multicellular systems. In this short review, we explore key challenges that must be overcome to achieve robust, repeatable data-driven multicellular systems biology. If these challenges can be solved, we can grow beyond the current state of isolated tools and datasets to a community-driven ecosystem of interoperable data, software utilities, and computational modeling platforms. Progress is within our grasp, but it will take community (and financial) commitment.
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