Methods | Definition of conformationally variable residue positions | |
The D2 coding | Positions where different D2 codes are assigned | |
The PB coding | Positions where different Protein Blocks are assigned | |
The ANGL (or KUZ1) coding | Positions where a change in dihedral angles, PHI or PSI, is greater than or equal to 30° | |
The KUZ2 coding | Positions where changes in both PHI and PSI are greater than or equal to 30° | |
The DSSP coding | Positions where different DSSP states are assigned |
Name | Definition of conformationally variable residue positions | |
Dihedral
Angle Patterns-2 (ANGL_CORE or ANG2) |
Residue
positions
which satisfy either (1) or (2), where (1) Difference of PHI angle >= 100° or Difference of PSI angle >= 100° (2) Difference of PHI angle >= 30° and Difference of PSI angle >= 30° |
|
Dihedral
Angle Patterns-1 (ANGL or ANG1) |
Residue
positions
which satisfy the following condition: Difference of PHI angle >= 30° or Difference of PSI angle >= 30° |
|
Dihedral
Angle Patterns-3 (ANGL_SUPP or CNST) |
Residue positions which satisfy either
(Difference of PHI angle is not equal
to 0°) or (Difference of PSI angle is not equal to 0°) |
|
Flexible
Regions (FLEX) |
Flexible residue positions detected by either FATCAT, FlexProt, RAPIDO, or DynDom. |
Metrics | Definition | Description | |
Accuracy (ACC) |
(TP + TN) / (TP + FP + TN + FN) | The
proportion of true results in the population. 100% means that the test identifies all positive and negative result correctly. |
|
Sensitivity (SN) |
TP / (TP + FN) | The proportion of actual positives which are
correctly identified as positive. It measures the ability of a test to correctly identify the presence of a positive sample. A highly sensitive test helps rule out negative samples. |
|
Specificity
(SP) |
TN / (TN + FP) | The proportion of actual negatives which are
correctly identified as negative. It measures the ability of a test to correctly identify the absence of positive samples. A positive result of a hightly specific test can be used to confirm the presence of positive samples. |
|
Matthews Correlation Coefficient (CC) |
(TP·TN - FP·FN) / sqrt{(TP+FN)(TP+FP)(TN+FP)(TN+FN)} |
A measure of the quality of binary
classifications. It returns a value between -1 and +1: +1 represents a perfect prediction (always right), 0 an random guess, and -1 an inverse prediction (always wrong). |
|
Selectivity (SL) |
Sensitivity / (1 - Specificity) | (= true positive rate / false positive rate) |