It is intriguing that two very different objective criteria for defining hubs agree well for networks that have a balance of error-free and unbiased interactions.
We propose a model for the role of MutSα at the immunoglobulin locus where the local balance of error-free and error-prone repair has an impact in the spectrum of mutations introduced during Phase 2 of SHM.
In any case, the balance of error tends to tip in the opposite direction, i.e., it is more common to diagnose women with respiratory symptoms of asthma than of COPD [ 20, 25], in the same way as among non-smokers [ 26].
However, whilst the financial balance of these errors remains in equilibrium, it seems that PbR can operate successfully with less-than-perfect data quality.
With an iterative procedure to examine the class-imbalance within the training sample it was furthermore possible to compensate spurious effects of class-imbalance and class-overlap on the balance of the error rates.
This observation may be explained by the fact that PI results, on the one hand, in a higher distribution volume and, on the other hand, in an increased transit time of the indicator; both of these factors have opposite effects on CO calculations, thus possibly leading to a balance of either error.
Using the constraints from the METAFoR analysis, it was not necessary to include redox cofactor mass balances in the mass balance constraints in C MFA. Cofactor mass balances are sources of errors since the correct balancing requires detailed knowledge of the relative activities of different isoenzymes and the enzyme cofactor specificities on a cell wide scale.
The common feature of all these methods is the error equation that allows a transparent balancing of all errors.
Cofactor mass balances are sources of errors since the correct balancing requires detailed knowledge of the relative activities of different isoenzymes and the enzyme cofactor specificities on a cell wide scale.
"In this type of automated analysis you have to balance two types of errors - errors where you miss whales, and errors where you misidentify whales.
In addition to its discriminative nature, its training criteria also balance the reduction of errors on the training data and the generalization on the unseen data.
