Information science for biology

Description logic never got me a date

I am no expert in description logic.

I just put that on the advert to get a girlfriend.

However it is interesting to hear about the limitations of representing biological knowledge in OWL-DL which, though powerful for implementing machine reasoning, can struggle with particular ways of thinking in biology such as:

• Similarity and ‘fuzziness’ : biology is grounded in the idea of similarity – similarity between molecules, between organisms, between functions. HOW similar two biological features may be is sometimes hard to describe (how similar are dogs and cats? how similar is DNA sequence A and DNA sequence B?) Indeterminacy like this is difficult to capture in description logic.
• Prototypes and exception : biologists often regard entities as prototypical, such that a human eye might be considered a prototype of all eyes even though something like an insectile compound, although totally different, is still in many senses related. Furthermore, exceptions to rules are quite normal in biology, so an enzyme class which catalyses transcription will always catalyse transcription, unless it is doing something else.
• Complex property restrictions : for example a transcription factor binds to a promoter and activates gene transcription – the biological process ‘gene transcription’ is a property of the factor + promoter complex
• Expressive datatypes : capturing in description logic the idea of a number ranging meaning ‘this is lots’ or dimensions translating to mean ‘this is a big cell’ – again, this type of thinking is rife in biology

The authors below give other examples and discuss just how some of these conceptual tools in biology might be captured in OWL-DL.

Stevens, R., Aranguren, E. M., Wolstencroft, K., Sattler, U., Drummond, N., Horridge, M., and Rector, A. (2007). Using owl to model biological knowledge. International Journal of Human-Computer Studies, 65(7):583-594.

dx doi 10.1016/j.ijhcs.2007.03.006 and Full text here