Table 3 |
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|
CGP performance on anaerobic mixed-acid fermentation genes (Escherichia coli K-12, 4131 genes). Prioritisation (AUC) of anaerobic mixed-acid fermentation genes in Escherichia coli K-12 |
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|
Statistical CGP |
Inductive CGP |
|||
|
|
|
|||
|
Scoring function |
AUC |
( |
Algorithm |
AUC |
|
|
||||
|
sens |
0.634 |
(1.2/1.8) |
NB |
0.695 |
|
spec |
0.464 |
(0.8/1.5) |
LR |
0.796 |
|
ppv |
0.519 |
(1.1/2.0) |
ADTree |
0.780 |
|
npv |
0.594 |
(1.8/11.0) |
IBk |
0.860 |
|
amss |
0.578 |
(2.4/96.6) |
J48 |
0.663 |
|
hmss |
0.628 |
(2.4/95.1) |
SMO/Poly |
0.848 |
|
OR |
0.537 |
(1.2/2.3) |
SMO/RBF |
0.782 |
|
chisq |
0.767 |
(3.2/109) |
||
|
bchisq |
0.585 |
(2.5/109) |
||
|
F |
0.698 |
(2.5/69.9) |
||
|
|
||||
|
Thirty-eight known genes were labelled as known (out of 4131 genes of the EC-K12 genome). The AUC in inductive CGP were calculated using stratified 10-fold cross-validation. Abbreviations: sens: sensitivity; spec: specificity; ppv: positive predictive value; npv: negative predictive value; amss: arithmetic mean of sensitivity and specificity; hmss: harmonic mean of sensitivity and specificity; OR: odds ratio; chisq: chi-square; bchisq: signed chi-square; F: F-measure; NB: naïve Bayes classifier; LR: logistic regression; ADTree: alternating decision tree; IBk: k-nearest neighbour classifier; J48: J48 decision tree; SMO: support vector machine trained by sequential minimal optimisation algorithm; Poly: polynomial kernel; RBF: radial basis function kernel. |
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|
Lin et al. BMC Bioinformatics 2009 10:86 doi:10.1186/1471-2105-10-86 |
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/ηmax)
