Understanding protein functions is crucial to unlocking the value of genomic data for biomedical research and innovation. Delivering personalized health and precision medicine requires a detailed understanding of the consequences of sequence variants in proteins and their impact on phenotype. The widening gap between known proteins and their functions has encouraged the development of methods to automatically infer annotations. Artificial intelligence and machine learning hold a large repertoire of algorithms and methodologies to discover and infer prediction models. Coupled with the new big data technologies for interactive analytics and data transformation, the AI/ML methods represent valuable assets that could enhance the discovery of protein functions.
This tutorial will help you understanding how to use Spark and Interactive Analytics to make sense of protein data and build Machine Learning models to infer their functions.
Scientists and bioinformaticians with an interest in protein functions, machine learning and modelling.