Analyzing Data for Systems Biology: Working at the Intersection of Thermodynamics and Data Analytics

Abstract

Many challenges in systems biology have to do with analyzing data within the framework of molecular phenomena and cellular pathways. How does this relate to thermodynamics that we know govern the behavior of molecules? Making progress in relating data analysis to thermodynamics is essential in systems biology if we are to build predictive models that enable the field of synthetic biology. This report discusses work at the crossroads of thermodynamics and data analysis, and demonstrates that statistical mechanical free energy is a multinomial log likelihood. Applications to systems biology are presented.