Figure 1 .

The effectiveness of neighbor images in reconstructing GRNs on the simulated data. A. The distribution of false positives from CNNC. B. The false positives of the two models with primary () and augmented () images as inputs due to randomness and transitive interactions. C and D. Two examples that demonstrate both of the models can correctly identify the direct interactions (C: , D: ). E and F. Two examples that demonstrate the model trained by augmented images can recognize and eliminate the false positives caused by the transitive edges (E: , F: ). denotes the confidence scores from CNNC with primary () or augmented images () as inputs. The values in the correlation matrices are Pearson correlation coefficients for the gene pairs in the corresponding entries. The primary images are highlighted in the red squares.