This webinar is recorded and available on YouTube
To address topics such as precision medicine, full DNA sequencing or digital therapeutics, Life Sciences and Pharma companies need to accelerate their digital transformation journeys and move towards data fabrics built on FAIR Data that offer a modular approach to data integration and knowledge consumption.
In this webinar, Ontotext and metaphacts will highlight the benefits of knowledge graphs for driving digital transformation in the Life Sciences & Pharma industry and will share important lessons learned from numerous customer implementations. We will use examples from a pre-clinical knowledge graph capturing OMICs data (genomics, proteomics, transcriptomics) together with information about pathways, tissues, drugs and diseases. The knowledge graph used in the webinar is built entirely from publicly available datasets, which are semantically mapped to each other and against the common data model. These public datasets include ChEMBL, Ensembl, UniProt, GWAS Catalog and Reactome). We will also outline the process of adding your own data (e.g., in the form of expression data) to the mix.
Such a comprehensive pre-clinical knowledge graph provides highly interlinked information across these various domains, delivering the needed insights, e.g., how to identify targets for new drugs through protein interaction partners or along the pathway.
The webinar will also discuss how a knowledge graph can help answer very specific requests such as: “Give me all interaction partners on human proteins, which are targeted by drugs used for the treatment of endometrial neoplasm, and which can be found in tissue type Uterus and are manually reviewed”. Additionally, the presentation will include details on how this embeds into the existing toolchain of, e.g., the bioinformatician or the chemist, and how data can be imported and exported from the knowledge graph to use in existing, domain-specific tools.
Expected duration:
- 45 minutes presentation
- 15 minutes Q&A session
