RIKEN Research: When it comes to modeling, even unmeasurable data tells us something

Mathematical models for predicting how cancer tumors in mice grow over time can give distorted results if unmeasurable data is ignored, a team that includes two RIKEN researchers has shown1. This finding has important implications when applying mathematical models to medicine.
A self-confessed data geek, Catherine Beauchemin of the RIKEN Center for Interdisciplinary Theoretical and Mathematical Sciences (iTHEMS) specializes in applying the power of math to everything from viruses to supernovae. “I love trying to figure out what data are telling us,” she says.
Seeking new insights into cancer mechanisms, Beauchemin’s team used mathematical models to analyze previously published data of tumor-size measurements over time for ten mice.

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