Auto-Adaptive Learning for Life Science Knowledge

Industries and academic research in the field of life science have to deal with massive distributed knowledge from multiple databases with various models. It takes time and lot of collaborations for a life scientist to process, in a secure manner, a project using multi-omic data. We provide an unsupervised auto-adaptive learning system to make available all new knowledge in real-time. We re-engineered the knowledge from these databases to build a distributed symbolic ontology updating in real-time. The system adapts itself to integrate new symbols and consolidate the ontology that may be used directly with natural language.