It's not about being an expert at everything or hiring more people. These aren't particularly hard problems, it's not difficult to find biologists who are incredibly adept at using python, R or C. It's about thinking about how science gets funded and how it gets implemented. I've written here before about the difference between "grant work" and "grunt work", and how too computer touching tends to get looked down upon at a certain level.

If you're deciding who gets a large-scale computational biology grant, and you're choosing between a senior researcher with 5000 publications with a broad scope, and a more junior researcher with 500 publications and a more compuationally focused scope, most committees choose the senior researcher. However, the senior researcher might not know anything about computers, or they may have been trained in the 70's or 80's where the problems of computing were fundamentally different.

So you get someone leading a multi-million dollar project who fundamentally knows nothing about the methods of that project. They don't know how to scope things, how to get past roadblocks, who to hire, etc.