Lucy Ham, Taylor E Woodward, Megan A Coomer, Michael P H Stumpf
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Mapping, Modeling, and Reprogramming Cell-Fate Decision-Making Systems.
Many cellular processes involve information processing and decision-making. We can probe these processes at increasing molecular detail. The analysis of heterogeneous data remains a challenge that requires new ways of thinking about cells in quantitative, predictive, and mechanistic ways. We discuss the role of mathematical models in the context of cell-fate decision-making systems across the tree of life. Complex multicellular organisms have been a particular focus, but single-celled organisms also have to sense and respond to their environment. We center our discussion around the idea of design principles that we can learn from observations and modeling and exploit in order to (re)-design or guide cellular behavior.
期刊介绍:
The Annual Review of Biomedical Data Science provides comprehensive expert reviews in biomedical data science, focusing on advanced methods to store, retrieve, analyze, and organize biomedical data and knowledge. The scope of the journal encompasses informatics, computational, artificial intelligence (AI), and statistical approaches to biomedical data, including the sub-fields of bioinformatics, computational biology, biomedical informatics, clinical and clinical research informatics, biostatistics, and imaging informatics. The mission of the journal is to identify both emerging and established areas of biomedical data science, and the leaders in these fields.