DTU uses TigerGraph’s advanced graph analytics to improve acute lymphoblastic leukemia treatment

— TigerGraph, provider of the leading graph analytics platform, has announced that the Technical University of Denmark (DTU) is using TigerGraph’s advanced graph analytics with machine learning and AI techniques to improve treatment of acute lymphoblastic leukemia.

Researchers at DTU are part of a major project across Denmark and Sweden to map genetic material for everyone with childhood cancer, according to a statement.

As part of a larger collaboration through the EU-funded iCOPE (Interregional Childhood Oncology Precision Medicine Exploration), the process starts with patient blood tests that through Whole Genome Sequencing paired with RNA-seq expression data are used to find aberrant expression patterns correlated or possibly caused by enhancer mutations.

The long term goal of iCOPE is to improve diagnostics, treatment, cure rates, and the overall life situation of children with cancer.

This process generates enormous amounts of data that using TigerGraph will be linked together with various other data points about the patient’s life, illness, and treatment in order to understand to a much greater extent why children get cancer, provide earlier diagnosis and far more effective treatment.

DTU is in the final stages of bringing the full system online and it is already being used in a specific project that combines the fields of AI, machine learning and translational bioinformatics to create models that can predict the risk of relapse and toxicity within acute lymphoblastic leukemia treatments.

TigerGraph’s upcoming Graph + AI Summit, the industry’s only open conference for accelerating analytics, AI, and machine learning with graph, will feature customer use case sessions and speakers from the world’s largest companies and most innovative startups and universities.

Source: BERNAMA News Agency

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