There has been a complexity explosion in biology – the fuse was lit in 1953 when the structure of DNA was discovered, but during the past two decades we have witnessed a dramatic expansion of data pointing to unanticipated levels of complexity. The hype surrounding the Human Genome Project suggested it would give us the blueprint of human biology and, as a consequence, would provide answers to our most probing questions.
“Mina Bissell, a cancer researcher at the Lawrence Berkeley National Laboratory in California, says that during the Human Genome Project, she was driven to despair by predictions that all the mysteries would be solved. “Famous people would get up and say, ‘We will understand everything after this’,” she says. “Biology is complex, and that is part of its beauty.””
In the early days of the revolution, the focus was on genes. This was regarded as the key that would unlock the mysteries of the cell. Genes were the providers of biological information, and the rest of the genome (98% of it) was deemed to be Junk DNA. Since this did not code for genes, the inference was made that it should be interpreted as an evolutionary artefact, unworthy of serious study.
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The level of complexity rose higher and higher as it became apparent that the communication within the cell is not best modelled by signalling pathways but by networks of information flows. The discipline of systems biology was created to make sense of the complexity. The verdict appears to be one of partial success, for even the systems biology approach struggles with the levels of complexity that are found.
“In the heady post-genome years, systems biologists started a long list of projects built on this strategy, attempting to model pieces of biology such as the yeast cell, E. coli, the liver and even the ‘virtual human’. So far, all these attempts have run up against the same roadblock: there is no way to gather all the relevant data about each interaction included in the model.”
The author of this informative feature article on complexity is Erika Check Hayden. As more and more is known, biology does not conform to the reductionist expectation of ultimate simplicity, but instead it appears ever more complex.
“[A]s sequencing and other new technologies spew forth data, the complexity of biology has seemed to grow by orders of magnitude. Delving into it has been like zooming into a Mandelbrot set – a space that is determined by a simple equation, but that reveals ever more intricate patterns as one peers closer at its boundary.”
The Mandelbrot set analogy has some value, but there is a danger to it. As Hayden points out above, the apparent intricacy is actually based on a simple equation. The complexity is in the eye of the beholder. Reductionism is entirely comfortable with the Mandelbrot set. But is biology really like this? The question deserves a much more rigorous analysis. Hayden refers to Davidson’s work in developmental biology and his claim to find simplicity and order. However, reductionism is not the only paradigm that incorporates simplicity and order. The concepts of complex specified information and irreducible complexity are entirely compatible with evidences of simplicity and order, yet are not explained by the reductionist approach. The domain surveyed by Hayden is home territory for the intelligent design paradigm. ID brings a perspective on biological information that takes us in a different direction to the Mandelbrot set analogy for biological complexity. The main problem for ID has nothing to do with relevance, but with its incompatibility with a materialist approach to science. But this also is a philosophical issue deserving of the widest possible discussion within the scientific community.
For more, go here.