Research

Life involves information processing at its core, both to preserve and evolve its rich functions. My research is toward understanding and harnessing the power of evolutionary and physical self-organization in the construction of information and material processing systems in the natural and technical domains.  This involves a combination of theoretical, constructive and experimental approaches:

  • statistical physical characterisations of fitness landscapes
  • mathematical theory for ion distributions around DNA
  • automata models of emergent functionality in molecular evolution
  • equilibrium structure ensemble computations for RNA
  • spatially resolved molecular evolution theory and experiments
  • reconfigurable computers for large scale spatial molecular evolution
  • microfluidic flow reactors for evolutionary biotechnology
  • synthetic DNA-programmed systems for cooperative evolution
  • spatially resolved single molecule detection for tracking DNA

More recent research achievements since 2000 include

  • simulation of emergence of genetic coding
  • optically programmable DNA computing
  • microfluidic "life support" to complement chemistry for artificial cells
  • genetic self-assembly and multiphase evolution models 
  • multiphase simulations of endocytosis for complex cells (like hepatocytes)
  • efficient computation of discrete molecule stochastic chemical kinetics (PRESS)
  • electronic chemical cells and the concept of electronic genomes
  • reversible attachment of DNA to gels for programmed selective transport
  • autonomous smart CMOS microparticles (lablets) with programmable electrochemistry 
  • nanorobot designs for nanorobotic surgery

Chemical information systems are vital for controlling natural functions in living organisms and are becoming increasingly important at the interface between three rapidly expanding technologies: Information Technology (IT), Biotechnology (BioT) and Nanotechnology (NanoT). 

My research involves theory and experiment into chemical and electronic systems which self-organize and evolve like living systems, processing information to solve complex problems, using a synthetic systems approach. My aim is to develop novel forms of constructive information processing systems based on and extending the core principles of living systems. 

supercap powered lablets on 100µm scale

BioMIP and its projects

See BioMIP Web Pages for my research group 2004-2017 :  John McCaskill 2019