Centralizing data to unlock whole-cell models. Issue 27 (September 2021)

• Record Type: Journal Article
• Authors: Chew, Yin Hoon; Karr, Jonathan R.
• Is Part Of: Current opinion in systems biology. Issue 27(2021)
• Publication Date: 2021-09
• Subjects: Whole-cell model -- Integrative model -- Data integration -- Data warehouse -- Computational biology -- Systems biology; Systems biology -- Periodicals; 570
• DOI: 10.1016/j.coisb.2021.06.004
• Languages: English
• ISSNs: 2452-3100

Abstract

Abstract: Despite substantial potential to transform bioscience, medicine, and bioengineering, whole-cell models remain elusive. One of the biggest challenges to whole-cell models is assembling the large and diverse array of data needed to model an entire cell. Thanks to rapid advances in experimentation, much of the necessary data is becoming available. Furthermore, investigators are increasingly sharing their data because of growing recognition of the importance of research that is transparent and reproducible to others. However, the scattered organization of this data continues to hamper modeling. Toward more predictive models, we highlight the challenges to assembling the data needed for whole-cell modeling and outline how we can overcome these challenges by working together to build a central data warehouse. Graphical abstract: Image 1 Highlights: Whole-cell models require data about each molecule and molecular interaction. Data are increasingly available, but their scattered organization hinders modeling. A central database of data and knowledge would accelerate whole-cell modeling. Such a database requires collaboration and standardization. New experimental methods and automation are also needed to broaden and deepen our data.