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Graph technology Mrs May doesn’t know about that could help beat complex diseases?


Last month, Prime Minister Theresa May set a national health and technology ‘Grand Challenge’: that by 2030, the United Kingdom will use data, Artificial Intelligence and innovation to transform the prevention, early diagnosis and treatment of diseases like cancer, diabetes, heart disease and dementia.

Organisation’s head of Data and Knowledge Management, Alexander Jarasch, what he thought of Mrs May idea, receiving this pretty positive reaction.

Jarasch knows this as his responsibility at the DZD is data infrastructure – putting together the right databases and other IT infrastructure to help his colleague’s scientific or bioinformatics analysis. And he is also starting to be convinced classic research has gone as far as it can, so scientists need to combine data or connect data better to find new answers.

DZD also wants to use natural language processing to help it analyse huge amounts of medical literature more rapidly, doing things like scanning hundreds of unknown diabetes-related texts for commonly-occurring keywords (i.e. gene names, or protein names) linked with diabetes, or other diabetes related phenotypes.

The way he has found to do this is a combination of the Neo4j graph database and its associated Cypher graph query language. Its first application: connecting up large amounts of metadata from DZD’s clinical studies and then trying to connect them on a genetic level, with one project already encoding millions of nodes representing different metabolites in these metabolic pathways.

Jarasch says it is still early days for graph at his institution, but developments like the Bloom Cypher NL interface will make it even easier for non-database specialists to start working with the kind of data they want to, he predicts.

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