RESUMEN
Water confined on the scale of 20 Å, is known to have different transport and thermodynamic properties from that of bulk water, and the proton momentum distribution has recently been shown to have qualitatively different properties from that exhibited in bulk water. The electronic ground state of nanoconfined water must be responsible for these anomalies but has so far not been investigated. We show here for the first time, using x-ray Compton scattering and a computational model, that the ground state configuration of the valence electrons in a particular nanoconfined water system, Nafion, is so different from that of bulk water that the weakly electrostatically interacting molecule model of water is clearly inapplicable. We argue that this is a generic property of nanoconfinement. The present results demonstrate that the electrons, and hence the protons as well, of nanoconfined water are in a distinctly different quantum state from that of bulk water. Biological cell function must make use of the properties of this state and cannot be expected to be described correctly by empirical models based on the weakly interacting molecules model.
RESUMEN
MOTIVATION: The large volume of single nucleotide polymorphism data now available motivates the development of methods for distinguishing neutral changes from those which have real biological effects. Here, two different machine-learning methods, decision trees and support vector machines (SVMs), are applied for the first time to this problem. In common with most other methods, only non-synonymous changes in protein coding regions of the genome are considered. RESULTS: In detailed cross-validation analysis, both learning methods are shown to compete well with existing methods, and to out-perform them in some key tests. SVMs show better generalization performance, but decision trees have the advantage of generating interpretable rules with robust estimates of prediction confidence. It is shown that the inclusion of protein structure information produces more accurate methods, in agreement with other recent studies, and the effect of using predicted rather than actual structure is evaluated. AVAILABILITY: Software is available on request from the authors.