[Odenwaelder]

In biology, the problem space is extremely vast and very hard to understand. I have a PhD in biology and find computer science relatively logical and simple. You can just look things up. Looking things up for a specific topic is not even easy in biology.

[esel2k]

Funny how you find comp science is simple and logic. Of course on a if else method level yes. But how to have a running system, dependencies, fail safe operations all coupled with tousand / millions lines of code is easily more complicated than a simply thesis about a mode of action of a protein.

I think we need to stop this useless debate as clearly one side has often no clue about the other. This behavior has led to massive failure in my career to successfully launch IVD devices or have a successfully bioinfo software for physicians - talking from experience here.

[goatlover]

The point is that a computer system can be entirely understood from the chips on up. Sure, it gets complex with millions of LOC. But we humans designed computers and wrote the code. Biology is not like that, and there is lack of a completed understanding form the proteins on up. So you get the complexity amplified on all fronts.

[perl4ever]

"You can just look things up"

Not only is documentation pretty scarce these days, but good information on the interactions between pieces of software is much scarcer, due to the exponential number of ways that it can interact.

[vbordo]

> Looking things up for a specific topic is not even easy in biology

How do you find info on bio topics right now?

[mattkrause]

Finding the actual info is not terribly difficult: Google Scholar and Pubmed, maybe with some of the arxivs.

The trick is interpreting it and putting it into context. A paper will report the results of one specific experiment, and it’s very rarely exactly what you want. Understanding how a result will generalize to other conditions is tricky, even for experts: there are tons of weird feedback loops, unusual dynamics, and other traps for the unwary (plus badly designed experiments and the occasional legit Type I error). For example, doubling the amount of a substance almost never doubles its effect, and in some cases, the effects aren’t even monotonic: ~75% alcohol, for example, is a much better disinfectant than 50 or 100%.

With time—-and lots of paper-reading, you do eventually develop a sense for what factors might matter and how you could check.

[Odenwaelder]

Depends on how deep you want to go. You need to find out what people are working on, and you do this by searching on PubMed and talking to people working in that field.