“Like Fisher you have worked in both statistics and genetics. How do you see the relationship between them, both in your own work and more generally?
Edwards responded in part:
Genetical statistics has changed fundamentally too: our problem was the paucity of data, especially for man, leading to an emphasis on elucidating correct principles of statistical inference. Modern practitioners have too much data and are engaged in a theory-free reduction of it under the neologism ‘bioinformatics’.
This elicited a strong response from ‘godless capitalist,’ a computational biologist himself:
In other words, they did a lot of math that was unconnected to reality, aka “it is a capital mistake to theorize in the absence of data”. You can see the results in the pages of the journal Genetics today, or in something like Gillespie’s book — written in 2004! — which doesn’t even mention genome sequencing.
This issue re: theorizing in the absence of data is particularly salient in population genetics, where basic phenomena like recombination (and its impact on evolution) could not be well modeled because of the sheer extent of fine-scale recombination variation — an extent which has only recently been apprehended and quantified.”