Date on Master's Thesis/Doctoral Dissertation


Document Type

Master's Thesis

Degree Name

M. Eng.



Degree Program

JB Speed School of Engineering

Committee Chair

Frieboes, Hermann

Committee Co-Chair (if applicable)

Chen, Joseph

Committee Member

Chen, Joseph

Committee Member

Altiparmak, Nihat

Author's Keywords

MultiCellDS; data standard; digital cell line; digital snapshots; ISA-Tab; bioengineering


The MultiCellular Data Standard (MultiCellDS) is an interdisciplinary effort to create a data standard for sharing multicellular experimental, simulation, and clinical data. The ultimate goal of the overall project is to allow for data sharing that will lead to better analyses and simulations for multicellular biology and predictive medicine in association with the PhysiCell, a software that allows for simulations of large numbers of cells in 3D tissues. Digital cell lines are files that contain a standardized representation of a biological cell line and include phenotypic parameters as well as microenvironmental conditions for use in simulations. A Digital Cell Line is a data model rather than a computational model, meaning that it is based on curated measurements of specific cells in certain conditions. A Digital Snapshot is a recording of the current state of an experiment or simulation within the MultiCellDS software. A snapshot contains metadata, which could include user information, software information, experimental setup, and citation information, and a phenotype dataset, which creates mappings of phenotypic measurements with the cellular microenvironment. Snapshots can also reference digital cell being used to create snapshots that come from simulations.

This Master’s Thesis project is a subset of the larger MultiCellDS effort. The results of this project allow for MultiCellDS Digital Snapshots to be converted to the ISA-Tab data standard, and ISA-Tab data files to be converted to MultiCellDS digital snapshots. The project uses Python code to convert the digital snapshots, which are produced as XML files, to ISA-Tab tab separated text files. All of the information from each file, both data and metadata, is accounted for and transferred to the proper locations in the other file type.

The Python scripts produced this project yield output files that have valid formatting in each data standard and verified contents for all Digital Snapshots currently available in the MultiCellDS Gitlab repository (currently 327 Digital Snapshots)

In the open-source nature of the MultiCellDS, all scripts, spreadsheets, and output files created for this Thesis project will be available on GitHub. The conversion between file types will allow for improved collaboration between researchers by allowing for information to be used in a variety of software packages.