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BioSig: an imaging bioinformatics system for phenotypic analysis.

B Parvin¹, Qing Yang, G Fontenay

¹Lawrence Berkeley Nat. Lab., CA, USA.

IEEE Transactions on Systems, Man, and Cybernetics. Part B, Cybernetics : a Publication of the IEEE Systems, Man, and Cybernetics Society

|February 2, 2008

Summary

BioSig catalogs cellular responses to experimental conditions, creating a hierarchical data model for cell phenome mapping. This system integrates experimental and informatics protocols for exploring cellular morphology and organization.

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Area of Science:

Cell biology
Bioinformatics
Data science

Background:

Organisms exhibit cell-specific gene expression, leading to diverse cellular phenotypes (phenomes).
Understanding organismal responses to stimuli requires mapping cell phenomes under various experimental conditions.
Current data representation lacks integration of experimental and informatics protocols.

Purpose of the Study:

To develop BioSig, a system for cataloging cellular responses to specific experimental conditions.
To create a data model for capturing experimental variables and mapping them to image collections.
To establish a hierarchical representation of cellular data from tissues to organelles.

Main Methods:

Developed a data model to capture experimental variables and map them to image collections.
Implemented a hierarchical data representation spanning tissues, cells, and organelles.
Utilized attributed graphs to represent cellular morphology, protein localization, and organization.
Built a Web-based multilayer informatics architecture for guided content exploration.

Main Results:

Established a foundation for cataloging cellular responses under diverse conditions.
Created a hierarchical data model linking experimental variables to image data and computed representations.
Enabled representation of cellular features at multiple biological scales using attributed graphs.
Provided a Web-based architecture for exploring complex cellular datasets.

Conclusions:

BioSig offers an integrated approach to cataloging and exploring cell phenome data.
The developed data model and architecture facilitate the study of cellular responses.
This system supports detailed analysis of cellular morphology, protein localization, and organization.