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Image Search Results
Journal: PLoS ONE
Article Title: Protein-Protein Interaction Site Predictions with Three-Dimensional Probability Distributions of Interacting Atoms on Protein Surfaces
doi: 10.1371/journal.pone.0037706
Figure Lengend Snippet: The y-axis of matrix shows the atom type index ( i = 30 protein atom types shown in ) and the x-axis shows the j index for the 32 A i,j features, where j = 1,31 represents the 31 interacting atom types shown in and the 32 nd feature reflects the local geometry of the protein surface. The matrix element ( j,i ) shows the Mann-Whitney U-test p-value in color-code for the two groups of A i,j : one group of A i,j was calculated for the attribute type j around the surface atom type i in the known PPI sites on proteins in the S432 dataset and the other group was calculated for the same attribute type around the non-PPI site atom type i in the same dataset. The p-values were calculated with the Mann-Whitney U-test implemented as the function ranksum in MATLAB. Two sets of data were input to the function and the output p-value is the probability for the two distributions of data to be statistically indistinguishable. The plus(+) sign in the matrix element indicates that the averaged feature value for the PPI site atoms is larger than the averaged feature value for the non-PPI site atoms and the negative(−) is the opposite. The panel on the right-hand-side of the matrix shows the distributions of protein surface atoms in PPI sites (blue) and non-PPI protein surfaces (red) against protein atom type. The data were derived from proteins in S432.
Article Snippet: The Mann-Whitney U-tests were carried out with the
Techniques: MANN-WHITNEY, Derivative Assay
Journal: Sensors (Basel, Switzerland)
Article Title: A Survey on Applications of Artificial Intelligence for Pre-Parametric Project Cost and Soil Shear-Strength Estimation in Construction and Geotechnical Engineering
doi: 10.3390/s21020463
Figure Lengend Snippet: Artificial intelligence for project cost estimation.
Article Snippet: The whole implementation of the ANN-based model was done using the
Techniques: Software, Produced, Construct