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Cell Syst. 2018 Aug 22;7(2):180-184.e4. doi: 10.1016/j.cels.2018.06.004. Epub 2018 Aug 1.

The Cell Cycle Browser: An Interactive Tool for Visualizing, Simulating, and Perturbing Cell-Cycle Progression.

Author information

1
Renaissance Computing Institute, University of North Carolina, Chapel Hill, 100 Europa Drive, Suite 540, Chapel Hill, NC 27517, USA.
2
Department of Biochemistry and Biophysics, University of North Carolina, Chapel Hill, 120 Mason Farm Road, Chapel Hill, NC 27599-7264, USA; Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, 120 Mason Farm Road, Chapel Hill, NC 27599-7264, USA.
3
Department of Genetics, University of North Carolina, Chapel Hill, Genetic Medicine Building 5061, CB#7264, 120 Mason Farm Road, Chapel Hill, NC 27599-7264, USA.
4
Department of Genetics, University of North Carolina, Chapel Hill, Genetic Medicine Building 5061, CB#7264, 120 Mason Farm Road, Chapel Hill, NC 27599-7264, USA; Curriculum for Bioinformatics and Computational Biology, University of North Carolina, Chapel Hill, 120 Mason Farm Road, Chapel Hill, NC 27599-7264, USA.
5
Curriculum for Bioinformatics and Computational Biology, University of North Carolina, Chapel Hill, 120 Mason Farm Road, Chapel Hill, NC 27599-7264, USA.
6
Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, 120 Mason Farm Road, Chapel Hill, NC 27599-7264, USA; Department of Genetics, University of North Carolina, Chapel Hill, Genetic Medicine Building 5061, CB#7264, 120 Mason Farm Road, Chapel Hill, NC 27599-7264, USA; Curriculum for Bioinformatics and Computational Biology, University of North Carolina, Chapel Hill, 120 Mason Farm Road, Chapel Hill, NC 27599-7264, USA. Electronic address: jeremy_purvis@med.unc.edu.

Abstract

The cell cycle is driven by precise temporal coordination among many molecular activities. To understand and explore this process, we developed the Cell Cycle Browser (CCB), an interactive web interface based on real-time reporter data collected in proliferating human cells. This tool facilitates visualizing, organizing, simulating, and predicting the outcomes of perturbing cell-cycle parameters. Time-series traces from individual cells can be combined to build a multi-layered timeline of molecular activities. Users can simulate the cell cycle using computational models that capture the dynamics of molecular activities and phase transitions. By adjusting individual expression levels and strengths of molecular relationships, users can predict effects on the cell cycle. Virtual assays, such as growth curves and flow cytometry, provide familiar outputs to compare cell-cycle behaviors for data and simulations. The CCB serves to unify our understanding of cell-cycle dynamics and provides a platform for generating hypotheses through virtual experiments.

KEYWORDS:

cell cycle; computational modeling; data visualization; live-cell imaging; single-cell dynamics

PMID:
30077635
PMCID:
PMC6214685
[Available on 2019-08-22]
DOI:
10.1016/j.cels.2018.06.004

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