By Richard A Friesner; I Prigogine; Stuart Alan Rice; Wiley InterScience (Online service)

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Consequently, we did the following. We shuffled the values of each secondary descriptor (other than c=n) 10 times and then trained neural networks to predict log kf as for the actual data. Averages and standard deviations of the correlation coefficients are reported in Table VII. 0 observed log kf (d) Figure 2. Comparison of observed and calculated values of log kf for selected models. (a and b) c=nðÞ; c=n and ÁG=n (&); and c=n; ÁG=n and pe ð4Þ. (c and d) c=nðÞ; c=n and nc (&); and c=n; nc ; and ÁGð4Þ.

Negative values of rcv indicate that the accuracy of the network is lower than that which would be obtained from random guesses. If a network fails in this way when confronted with novel test data, it has derived a spurious relationship by memorizing the information in the training set at the expense of learning more general rules. The highest rcv do correspond to the highest rtrn , but overall the cross-validated coefficients are much lower. The large differences between rtrn and rcv in many cases (Table I) make clear that the former is a relatively indiscriminate statistic for such a small database.

There are three disulfide bonds in this protein: Cys5–Cys55 shown in red, Cys14–Cys38 shown in black, and Cys30–Cys51 shown in blue. The corresponding Cys residues are in the ball-and-stick representation and are labeled. The two helices (residues 2–7 and 47–56) are shown in green. Figure 8. ) (a) The ground-state conformation of the two-dimensional model sequence with M ¼ 23 beads and four covalent (S) sites. The red, green, and black circles represent, respectively, the hydrophobic (H), polar (P), and S sites.

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