CellPD

CellPD quantifies cell population dynamics by fitting mathematical models to cell growth data to relate phenotypic changes to molecular alterations.


Key Features:

  • Parameter estimation and outputs: Generates parameter estimation reports, high-quality plots, and minable XML files.
  • Robust estimation and validation: Validates estimates against cellGrowth and Microsoft Excel built-in functions and demonstrates superior robustness to data sparsity compared to cellGrowth.
  • Growth rate decomposition: Estimates net growth rates and drug-dependent birth and death rates of cell cultures.
  • Cytostatic versus cytotoxic quantification: Quantifies and distinguishes cytostatic (growth-inhibiting) and cytotoxic (cell-killing) effects of compounds.
  • Mathematical model fitting: Fits mathematical models to cell growth data for parameter inference.
  • High-content screening analysis: Analyzes synthetic high content screening datasets for drug effect quantification.
  • Functional genomics support: Supports analysis of gene knockout experiments by quantifying resulting phenotypic changes.
  • Data quality control and integration: Facilitates data quality control and integrates experimental data with computational models to generate minable big data.

Scientific Applications:

  • Drug Discovery and Development: Quantifies the effects of drug compounds on cell growth to inform mechanisms of action and therapeutic optimization.
  • Functional Genomics: Analyzes phenotypic consequences of gene knockout experiments.
  • Data Integration and Modeling: Integrates experimental measurements with computational models to support predictive modeling and hypothesis testing.

Methodology:

Computational methods explicitly include fitting mathematical models to cell growth data, parameter estimation of net growth and drug-dependent birth/death rates, validation against cellGrowth and Microsoft Excel functions, quantification of cytostatic versus cytotoxic effects, analysis of synthetic high content screening datasets, data quality control, and export of results as parameter reports, plots, and minable XML files.

Topics

Details

License:
MIT
Tool Type:
library
Operating Systems:
Linux, Windows, Mac
Programming Languages:
Python
Added:
8/18/2018
Last Updated:
11/25/2024

Operations

Publications

Juarez EF, Lau R, Friedman SH, Ghaffarizadeh A, Jonckheere E, Agus DB, Mumenthaler SM, Macklin P. Quantifying differences in cell line population dynamics using CellPD. BMC Systems Biology. 2016;10(1). doi:10.1186/s12918-016-0337-5. PMID:27655224. PMCID:PMC5031291.

PMID: 27655224
PMCID: PMC5031291
Funding: - National Institutes of Health: 1R01CA180149, 5U54CA143907 - Breast Cancer Research Foundation: (Not applicable)

Documentation