Establishing a conceptual framework for holistic cell states and state transitions

Area of Science:

• Cell Biology
• Computational Biology
• Bioinformatics

Background:

• Traditionally, cell states were defined by morphology, location, and function.
• The post-genomic era shifted focus to molecular definitions of cell states.
• Rapid advancements in single-cell imaging and data science necessitate new approaches.

Purpose of the Study:

• To propose a conceptual framework for defining holistic cell states.
• To integrate spatiotemporal and molecular observables for a comprehensive cell state definition.
• To enable data-driven, practical, and integrative analyses and modeling across diverse data types.

Main Methods:

• Leveraging large-scale, systematic cell image datasets.
• Applying quantitative image-based data science methods.
• Developing a data-driven conceptual framework for holistic cell states.

Main Results:

• Anticipation of evolving observables for defining cell states.
• Identification of a key moment for integrating physical and molecular data.
• Proposal of a framework for holistic cell states and transitions.

Conclusions:

• A holistic cell state concept integrating physical and molecular data is crucial.
• The proposed framework facilitates integrative analyses and modeling.
• This approach is essential for advancing cell biology research in the post-genomic era.