Towards Automatic Pathway Generation from Biological Full-Text Publications

We introduce an approach to the automatic generation of biological pathway diagrams from scientific literature. It is composed of the automatic extraction of single interaction relations which are typically found in the full text (rather than the abstract) of a scientific publication, and their subsequent integration into a complex pathway diagram. Our focus is here on relation extraction from full-text documents. We compare the performance of automatic full-text extraction procedures with a manually generated gold standard in order to validate the extracted data which serve as input for the pathway integration procedure.