Abstract: Disclosed are systems, methods, and other implementations, including a method for configuring a machine learning (ML) system. The method includes determining for a layer, l, of the ML system sets of parameters defining one or more statistical distribution models (e.g., lognormal) used for directing the ML system to an optimized configuration. The layer is connected to one or more other layers through weighted connected, and includes configurable ML elements (e.g., neurons) that can be tuned. The method also includes adjusting one or more of, a) weights of the weighted connections of the layer according to parameters defining a first distribution model, b) adjustable parameters defining the first statistical distribution model, c) ML element parameters, defining operations of at least some of the configurable ML elements, according to parameters defining a second distribution model, and/or d) adjustable parameters defining the second distribution model.

Abstract: A method of enhancing the yield of a product is provided. A host organism that is adapted to produce the product as a function of metabolism in the presence of a substrate is selected and a plurality of optimal reaction pathways are determined by searching a database and executing an optimization algorithm. The optimal reaction pathways take place in the host organism to produce the product from the substrate and are ranked and enumerated. The optimization algorithm comprises a flux balance analysis and maximizes the yield of the product.