Distributed systems and methods for learning about a bioprocess from redox indicators and local conditions

摘要

The present invention concerns methods and systems for learning about the redox status of a biological process experienced by a biological entity under local conditions by postulating hidden states that are locally inaccessible but are related to the redox status. The learning system uses a reference bioprocess model from which a master learner establishes an observable basis of redox indicators that are real-valued, measureable, and exclude hidden states. Meanwhile, a local learner receives at least a portion of model redox data from the reference bioprocess model, and measured redox data from the biological entity. The learning system runs a distributed learning algorithm using the observable basis established by the master learner to determine an optimal composition of redox data to be included in measured redox data collected under local conditions.