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Key challenges facing data-driven multicellular systems biology

Authors
  • Macklin, Paul
Type
Preprint
Publication Date
Sep 27, 2019
Submission Date
Jun 12, 2018
Identifiers
DOI: 10.1093/gigascience/giz127
Source
arXiv
License
Green
External links

Abstract

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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