CellPD: Cell Phenotype Digitizer
CellPD responds to the need of user-friendly and open source software in the (computational & systems) biology community. Particularly, CellPD allows for automatic quantification of key parameters of cell phenotype such as cell growth rate and doubling time.
CellPD aims to facilitate the use of computational biology techniques and allow scientits who are not trainied in computer programming to leverage mathematical modeling. The design parameters for CellPD can be found in CellPD's paper and are sumarized here:
- Utility for experimental biologists: CellPD allows for quantification of key parameters of cell phenotype. Among the possible uses for CellPD are quality control, comparison of cell cultures, and generation of experimental results databases.
- Ease of learning and ease of use: CellPD can be learned to use in a few minutes and it only requires familirarity with spreadsheets (such as Microsoft Excel). We provide a tutorial in each download of CellPD.
- Robustness to sparsity in data: CellPD can estimate parameters of time series data with as few as two samples. Additionally, CellPD was designed to handle data points measured at irregular time intervals.
- Accessibility and Shareability: CellPD's source code is freely available via SourceForge. CellPD is open source and anyone may modify it, provided they follow the terms of the (unrestrictive) MIT licence.
- Extensibility: CellPD has been designed to be easily extendable, we have planned a series of extensions to CellPD's functinality. Because CellPD is open source it may also be modiffied by anyone who follows the MIT licence.
- Portability: In addition to the Python source code of CellPD, we provide executable files for Windows and OSX (no installation required for those).
What's New Back to top
December 12, 1015: The CellPD software paper is now publicly available (free and open access) at BMC Systems Biology.
E.F. Juarez et al. Quantifying differences in cell line population dynamics using CellPD. BMC Systems Biology, 2016.
Open access download: click here.
Method Back to top
We use the Levenberg-Marquardt Algorithm (LMA) to perform nonlinear estimation of parameters for various mathematical models of cell population dynamics. Further technical details can be found in CellPD's manuscript, Juarez et al. (2016).
Examples Back to top
Examples are included as a tutorial, which is included in every CellPD download. Comparison to to other tools as well as using CellPD for quality control and to analize pharmacological effects of (simulated) unknown drugs can be found in Juarez et al. (2016). More details will be included here in the near future.
Licensing and disclaimers Back to top
CellPD is an academic/scientific code, and it should not be used as the basis for individual medical decisions. (That's what peer review, clinical trials, and FDA oversight are for!) Always consult your physician when making medical decisions.
Downloads Back to top
CellPD is available for download at SourceForge. Each download includes a tutorial and exmaples.
Most recent versions
|Version||Release Date||Download link|
|1.0.1||26 September 2016||https://goo.gl/7CA9ss [sf.net]|
|Notes: Minor text fixes. No effect on scientific results.|
|1.0.0||16 January 2016||https://goo.gl/FPBtIS [sf.net]|
|Notes: First public release|
- CellPD Software Paper:
- Juarez et al. (2016) published the original version of CellPD.
- A user tutorial with several examples is included with every CellPD download.
We anticipate writing further tutorials and walk-throughs on the MathCancer blog over the next few months.
Support Back to top
If you plan to use CellPD in a grant proposal, please consider including Paul Macklin as a consultant for more dedicated support.
How to Cite CellPD Back to top
If you use CellPD in your project, please cite CellPD and the version number, such as below:
We fit the data to several growth models using CellPD (Version 1.0.1), which uses the Levenberg-Marquardt algorithm to perform a least-squares fit of several mathematical models to data .
 Juarez, E. F., et al. (2016). Quantifying differences in cell line population dynamics using CellPD. BMC systems biology 10(1): 1-12.DOI: 10.1186/s12918-016-0337-5.
The paper can be downloaded (free, open access) at BMC Systems Biology. To import the paper into your citation manager click here:
Some Publications and Projects that cite CellPD
Nothing just yet. :-)
Additional topics Back to top
- BioFVM: Our lab's finite volume solver for biological problems.
Link: More information is available here.
- PhysiCell: Our lab's physics-based agent-based simulator uses CellPD for simulating the microenvironment.
- MultiCellDS: CellPD uses the MultiCellDS data format to create Digigal Cell Lines.