In the Literome project, we have developed an automatic curation system to extract genomic knowledge from PubMed articles and make this knowledge available on this website to facilitate browsing, searching, and reasoning.
Currently, Literome focuses on two types of knowledge most pertinent to genomic medicine:
- Directed genic interactions (such as pathways) and the nature of the interactions. Users can also search for interactions involving an intermediary gene inferred from published data. E.g. even if there is no published interaction A ➞ B, Literome will look for any gene X where there are published interactions A ➞ X and X ➞ B which may imply A ➞ X ➞ B.
- Genotype-phenotype associations; i.e. diseases or drugs associated with a SNP or gene. Users can also search for indirect connections between two entities. E.g. a gene and a disease might be linked because an interacting gene is associated with a related disease.
Both of these databases can also be accessed through web services.
More details on Literome can be found in these publications:
"Literome: PubMed-Scale Genomic Knowledge Base in the Cloud"
Hoifung Poon, Chris Quirk, Charlie DeZiel, David Heckerman
In Bioinformatics 30.19 (2014), 2840-2842.
"Distant Supervision for Cancer Pathway Extraction from Text"
Hoifung Poon, Kristina Toutanova, Chris Quirk
In Proceedings of the Pacific Symposium on Biocomputing, 2015.