I recently found a poster presentation at PyCon 2013 with the following summary:
We constructed a knowledge-based data model using Django's object-relation mapping (ORM) in which the cancer-related informations from 3 ontologies, i.e. Gene Ontology, Disease Ontology, and ChEBI, and 4 clinical databases, i.e. 1000 Genomes, Comparative Toxicogenomics Database, ClinicalTrials, and DrugBank were utilized and semantically related. Using our data model, the integrated information such as related genes, their mutations, single nucleotide polymorphisms, clinical trials, and related drugs for given cancer types can be retrieved.
I immediately thought this would make a fascinating student presentation provided I was able to construct a similar project (the source code to the aforementioned project was not
provided) using Perl. With that objective in mind, I was wondering if you (collectively) could provide some feedback on what approach you would take? I am considering Catalyst
but I have yet to find a suitable tutorial on either or, more specifically, a book on Catalyst whose reviews inspire confidence. Clearly, such a project is ambitious but I would not need to present the project until April of 2014 and this should provide ample opportunity to develop the necessary skills / knowledge. Since I am completely unfamiliar with both Catalyst
, I would be appreciative if someone could share with me (us) the purpose of these packages. Would either be suitable for the project described above? Do you suggest learning SQL or would an Object Relational Model (ORM) make that action unnecessary?
Thanks for the help.