Centralizing data to unlock whole-cell models

TL;DR

This paper discusses the importance of centralizing diverse biological data in a shared warehouse to facilitate the development of comprehensive whole-cell models, which are crucial for advances in bioscience and medicine.

Contribution

It proposes creating a centralized data repository to overcome data scattering and enhance the assembly of comprehensive datasets for whole-cell modeling.

Findings

Data sharing is increasing due to reproducibility efforts.

Scattered data hampers whole-cell model development.

Centralized data warehouses can improve model accuracy.

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 due to increased emphasis on reproducibility. 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.