Motivations for Computational Modeling

The book "Catalyzing Inquiry at the Interface of Computing and Biology" was collected in 2005 by the National Research Council Committee on Frontiers at the Interface of Computing and Biology as J.C. Wooley JC and H.S. Lin as editors. Even though the book is already several years old, the motivations listed for computational modeling are still very relevant. In the chapter Computational Modeling and Simulation as Enablers for Biological Discovery, the following motivations are listed:

• models provide a coherent framework for interpreting data,
• models highlight basic concepts of wide applicability,
• models uncover new phenomena or concepts to explore,
• models identify key factors or components of a system,
• models can link levels of detail,
• models enable the formalization of intuitive understandings,
• models can be used as a tool for helping to screen unpromising hypotheses,
• models inform experimental design,
• models can predict variables inaccessible to measurement,
• models can link what is known to what is yet unknown,
• models can be used to generate accurate quantitative predictions, and
• models expand the range of questions that can meaningfully be asked

Even though the article focuses on biological systems, the list is general and applicable also to cognitive and social systems.