In anything that is true, if you can't describe it to funders what you are hoping to accomplish in laymans terms then you will not get funded. Funders understand that particle physics searches for new particles no need to understand the nitty gritty, they can even ask interesting questions "can a new particle cause us any sort of worry that we might destroy ourselves?" etc. You apparently argue that we can't even string together high level concepts into causal sequences when we enter the realm of medical biology. How is that even a science?
I don't want to argue with you; you can choose to ignore what I said. but the funders who pay for molecular biology typically are scientists who understand, or wealthy people who hire people who understand, that medical biology, while scientific, is not like the highly quantitative physical sciences, nor is it easily appreciated by novices.
Everything about causation in biology works differently than in other sciences.
Unfortunately I must resort to novice assertions to get any understanding. I'm not really sure I understand how causation in biology is fundamentally different. Apart from that you can certainly encapsulate biological events into some sort of locality and apply normal causative analysis to rule out specific scenarios, really that is what I am talking about here. I think we can agree that there are infectious molecules tumbling through space and time and work from there or is that not how molecular biology works?
The molecules are not infectious, but specific assemblies of them are. But more importantly, here's a great example: the molecules which form an assembly do so spontaneously. It's like putting all the pieces of a jigsaw puzzle in a bag, shaking it, and every time, the puzzle comes out completely solved, even if the chances of that happening randomly are unbelievably small. We only observe the statistical average of enormous numbers of these things, which are all happening simultaneously, with complex effects.
Many biological papers don't work with mechanisms at all- they just deal with statistical associations between entities- and treat them as complex black boxes.
Here's another exmaple. Why do people grow to the heights they do? Well, originally people thought there were maybe 1-2 genes, with a few specific mutations, and the results all sort of added up linearly. Nope! Instead, we've learned that about 50% of total height variation is explained by genetics, and even then, there are hundreds of different genes that contribute to height, with all sorts of different variations in and between genes causing nonlinear effects (typically ignored in genetics, but considered strongly in evo-devo) that are extremely hard to explain in a detailed causal way.
In short: biology is highly nonlinear with huge numbers of variables, along with active feedback mechanisms and other complex systems that work to maintain homeostasis against entropy and protection against constantly evolving infectious agents. The basic concepts of causality, like "entity A causes event B which leads to outcome C" really do apply, but they're fully probabilistic and massively tensorial.
