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Area of Science:

  • Integrative systems biology
  • Philosophy of science
  • Cognitive science

Background:

  • Systems biology relies on computational modeling and simulation for complex biological problems.
  • The role of human cognitive resources in computational modeling remains underexplored.
  • Existing philosophical accounts acknowledge but do not fully detail cognitive contributions.

Purpose of the Study:

  • To investigate the specific roles of human cognition in computational modeling within systems biology.
  • To analyze how modelers use cognitive tools to manage complexity in biological systems.
  • To understand how cognitive processes influence model-building and representational choices.

Main Methods:

  • Focus on the practices of systems biology modelers.
  • Analysis of how cognitive complexity is handled through simulation and other tools.
  • Examination of simulative mental modeling processes.

Main Results:

  • Human cognition, especially simulative mental modeling, is central to model-building in systems biology.
  • Cognitive processes shape and constrain representational choices in what is modeled.
  • These constraints help explain the nature of problem-solving and its limitations in the field.

Conclusions:

  • Cognitive resources are indispensable for computational modeling in systems biology.
  • Understanding cognitive roles clarifies the scope and limitations of current problem-solving strategies.
  • This perspective can rationalize why results may not always meet expectations.