Quantifying cumulative phenotypic and genomic evidence for procedural generation of metabolic network reconstructions
Fig 8
(A) Phenotypic data used to build the model. (B) The final accuracy of the model is 92% with no false positive predictions. The model has an MCC of 0.83. (C) From the Universal Network, 1,746 reactions have Nissle specific genetic evidence associated with them; of those, there are 466 reactions that receive CVs from the CANYUNs pipeline. There are 176 reactions that do not have Nissle-specific genetic evidence, yet receive CVs and are thus included in the final CANYUNs model for Nissle. (D) These reactions received certainty values, but do not have associated genetic evidence; they are candidates for manually finding sequences to add to the reference dataset. (E) There is also a set of 103 reactions with CVs and low bitscores (below 500). Reactions with a high Certainty Value and a bitscore above 200 are likely candidates for direct additions to the sequence-to-reaction dataset.