I think you should have some point to compare.

See the following article from 1974.

http://sci-hub.cc/10.2307/2412942

In 2012 another paper was published/ It considered a different classfification problem.

A Classification of Bioinformatics Algorithms from the Viewpoint of Maximizing Expected Accuracy (MEA)

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3342518/

Its abstract citation: "Many estimation problems in bioinformatics are formulated as point estimation problems in a high-dimensional discrete space. In general, it is difficult to design reliable estimators for this type of problem, because the number of possible solutions is immense, which leads to an extremely low probability for every solution—even for the one with the highest probability. Therefore, maximum score and maximum likelihood estimators do not work well in this situation although they are widely employed in a number of applications. Maximizing expected accuracy (MEA) estimation, in which accuracy measures of the target problem and the entire distribution of solutions are considered, is a more successful approach. In this review, we provide an extensive discussion of algorithms and software based on MEA. "

I meant this is infinite question. Almost everything in the world has its own classification.

Transcription factors:

http://dbtbs.hgc.jp/ver1/tfactable.html

Classification of human genomic regions based on experimentally determined binding sites of more than 100 transcription-related factors

https://genomebiology.biomedcentral.com/articles/10.1186/gb-2012-13-9-r48

etc...

Could you expand on what you mean with site classification problems? I don't think I understand. I see Natasha has some links for you, but I can't see how those are related to something like the classification of transcription sites in your example.