Thesis #8 This complex genomic foundation for adaptation in turn produces a still more complex network of interacting molecules that sustain survival, health, fertility, and function.

Arising from the genetic complexity of healthy function is a still more complex set of interacting products of DNA sequences:  all the RNAs transcribed from DNA and all the proteins that are made from RNAs.  These in turn interact with each other, with other molecules that make up cells, and even with the DNA from whence they came.

So the genomic complexity of the DNA that underlies health is just the simplest dimension of healthy function.  What is erected from the linear strands of DNA that make up our genomes is three-dimensional, and teeming with a fury of interactions.  Many of these interactions happen quickly, while others proceed only slowly.  But this network is all in motion and in interaction.

It has been the long-standing, indeed hubristic, conceit of molecular and reductionist biology that this vast three-dimensional matrix of furiously interacting gene-products can be understood using such simple linear paradigms as their concept of pathways.

It is indeed correct that there are some major channels that weave their way through the hurly-burly within cells, and among cells within organisms.  But focusing solely on these major channels of biological causation would be like an attempt to understand the population and economy of Los Angeles in terms of its interstate freeways alone.  Yes, cutting these freeways, or diverting them wholesale, has a major impact on the economy of the Southern California conurbation.  But determining the impact of such wholesale disruptions is very different from a satisfactory analysis of the complexity of this urban region’s economy.

Thus, in developing a useful understanding of this complex three-dimensional web of cellular and organismal function, we need to use conceptual tools that are adequate to the task.  Unfortunately, the reductionist toolkit of traditional 20^th Century molecular and cell biology simply is not adequate, in strictly scientific terms.  It isn’t just crude and mechanical.  It is wrong.

Instead, we must look to such open-ended intellectual tools as population genetics, quantitative genetics, and systems biology to make sense of the explosive complexity of biological function.  And such tools are inherently mathematical and computational.