[dekhn]

Personally I think a major part of the secret sauce is Google's internal compute infrastructure. When I was an academic, 50% of my time went to building infra to do my science. At Google, petabytes of storage, millions of cores, algorithms, and brains were all easily tappable within a common software repo and cluster infrastructure. That immediately translates to higher scientific productivity.

[MaxBarraclough]

Has cloud computing changed this?

[dekhn]

Mostly? I left google to work at a biotech startup working in a related area and found that the big three cloud providers have built systems that greatly improve computational science. That said, it's still a lot of work to get productive, many in the field are really resistant to changes like version control, continuous integration, testing, and architecting distributed systems for handling complex lab production environments.

Here's an exemplar of how I think it evolved well in a cloud world: https://gnomad.broadinstitute.org/

that project adopts many concepts from google and others and greatly improved our analytic capabilities for large-scale genomics.

[asah]

Having recently experienced both, 1000x this.

[t_serpico]

You hit the nail on the head here.