Cing! Thank you for very flattering comment. Obviously, this is database only paper. Please bare in mind, the vast majority, or perhaps even >95% of protein structure prediction methods deal with canonical secondary structure classes. We want to provide a coherent data set as a benchmark + source of information.
We have in "stock" a network (obviously another paper) that will aim at propensity prediction, still in trivial alpha/coil/beta phase space.
Probably rolling out of laughter. You don't need ML to "predict" properties of molecules. Not a single physicist will but ML predicted molecule properties.
I am curious to see what will happen to Tensor Flow. I hope the code will get clean up... I also hope they will eventually pay somebody to do it, as the open source option clearly generates heterogeneous nightmare.
They are for sure! Obviously, all depends on the complexity of the problem and the willingness of programmers to install tests :/
In my company, we are ridiculously pedantic about unit testing, but even with proper level of attention to detail we sometimes fail with getting 100% code coverage.
The biggest pain are log(x)/ln(x) issues in numerical optimization.
The article you link would is about biology, not only that but Wikipedia has to try to be consistent across various fields, unlike mathematics and physics where the natural logarithm is used almost exclusively, so it makes sense to use a more explicit notation.
Sure physics (and sometimes mathematics) do use the notation 'ln' every so often (if only because it's shorter) but you'd be hard pressed to find a reference in anything related to mathematics or physics that uses log as the base 10 logarithm.
Clearly the easiest way to avoid the ambiguity is to only ever use the natural logarithm, which is the choice made by all the programming languages you listed at the end. And since you don't list any references where log should refer to the base-10 logarithm I'll have to conclude that they made the right choice.
I mean in your assertion that `log` must mean `log10`. I have huge sympathy for contending with inconsistent use of ambiguous notation. My pet hate is `gamma` vs. `tgamma`.
I wouldn't dare to suggest that, yet that's the route that physics and all derivatives have adopted!
We are essentially at the crossroad and obviously, programming, which develops nowadays a bit faster than theoretical physics or mathematics, pushes in one direction.
We have in "stock" a network (obviously another paper) that will aim at propensity prediction, still in trivial alpha/coil/beta phase space.