Construction of a Natural Language Processing (NLP) infrastructure to support domain experts in biomedical discovery over large scientific textual bases (papers and patents).
ABRoad aims to develop an NLP software infrastructure which will support biomedical discovery using large-scale textual interpretation over scientific text (papers and patents). The project will use state-of-the-art methods in Deep Learning based text representation, such as transformers and graph neural networks, to support specialised inferences over large-scale corpora.
The project aims to provide a universal (embeddings-based) textual interpretation platform to support the identification of new hypotheses in the life science space. The platform will integrate two main data modalities: textual and molecular representations. More specific target scenarios include support for drug discovery (e.g. drug repurposing), the determination of bioequivalent substances and the identification of novel antibiotics.