Gender: Its about more than just gonads.
Phillip Lord (Newcastle)
He begins with a story – what does LGBTQIA+? How do you define this in an ontology? Perhaps start with something simpler… This is about social modelling. Modelling this is a challenge because it is important, and complicated, and sensitive.
First you need to consider gender versus sex. Newcastle has one of the 7 gender dysphoria clinics in the UK. ICD-10 has a classification of disease called “trans-sexual” which has been removed in ICD-11 because it is not a disease. You also have PATO, which describes gender – among other things. PATO’s male and female definitions has its own issues. These definitions are based on gametes, which is problematic – if you are a infertile man you are both female and male (and so on and so forth). Intact, and Castrated and other aspects of the PATO definitions have problems. The definition of Castrated Male contradicts the definition of Male.
The beginning of Phil’s ontology is Birth Assigned Gender. Other terms include Affirmed, Man, Woman, pronouns, legal gender and biological gender (biological gender will be dropped). Man and Woman are defined based on your affirmed gender, not your assigned gender.
He’s also started modelling sexuality. The entire area is difficult to model, and is critical for many IT systems, and is very interesting.
SyBiOnt: The Synthetic Biology Ontology
Christian Atallah (Newcastle), James McLaughlin (Newcastle), James Skelton(Newcastle), Goksel Misirli (Keele) and Anil Wipat (Newcastle)
Synthetic Biology: the use of engineering principles for the development of novel biological applications. The classic build -> test -> learn -> design -> build. Synthetic biology is very modular and includes many different types of biological parts. SBOL is used to visualize and build synthetic biology designs. SyBiOntKB is an example of using the ontology. You can mine SyBiOntKB to get synthetic biology parts. http://sybiont.org
SBOL-OWL: The Synthetic Biology Open Language Ontology
Goksel Misirli (Keele), Angel Goni-Moreno (Newcastle), James McLaughlin(Newcastle), Anil Wipat (Newcastle) and Phillip Lord (Newcastle)
Reproducibility of biological system designs is very important. SBOL has been adopted by over 30 universities and 14 companies worldwide as well as ACS Synthetic Biology. The designs are hierarchical and can be grouped into modules. In order to understand SBOL you need to read the User Guide – it isn’t available computationally. Validation rules are in the appendix, and SBOL refers to external ontologies and CVs to provide definitions. So, how should you formally define this? Provide an ontological representation of SBOL data model – SBOL-OWL.
Example query – return a list of ComponentDefinitions that are promoters and of type DNARegion and that have some Components.
SBOL-OWL allows computational validation of verification rules, and allows automated comparison of incremental SBOL Specifications. It provides a machine-accessible description of SBOL entities. You can annotate genetic circuit designs with rich semantics, which would allow you to use logical axioms for reasoning over design information.
Please note that this post is merely my notes on the presentations. I may have made mistakes: these notes are not guaranteed to be correct. Unless explicitly stated, they represent neither my opinions nor the opinions of my employers. Any errors you can assume to be mine and not the speaker’s. I’m happy to correct any errors you may spot – just let me know!