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Figure 3
A summary of the main experimental results. (a) Scoring and performance evaluation of an image set: (i) images start out unscored with human annotations; (ii) the algorithm scores the set, inducing a rank ordering on it; (iii) an ROC curve is derived from scores and ground truth. (b) The ROC heatmap, a simultaneous view of all individual ROC curves. For the purposes of ROC analysis, we treat diffraction candidates as true-positive examples and discarded trials as false-positive examples. Rows delineate individual curves ordered from top to bottom in descending order of ROC-AUC score. The intensity values of the heatmap represent true positive rates, with an overlay marking the location of images containing the diffraction success in blue. (c) Diffraction successes and their images: representative rectangles are shaded in the same color in (b) and (c) to show position in the heatmap. (i) Crystals of an XisH-family protein from Nostoc punctiforme PCC 73102 at 1.60 Å resolution (PDB code 2inb ). (ii) Crystals of Bacillus cereus ATCC 10987 at 2.10 Å resolution (PDB code 2p1a ). (iii) Crystals of methyltransferase FkbM from Methylobacillus flagellatus KT at 2.20 Å resolution (PDB code 2py6 ). Much of the crystal contours are occluded by precipitant. (iv) Crystals of HD superfamily hydrolase from uncultured Thermotogales bacterium at 1.45 Å resolution (PDB code 2pq7 ). Aside from a telltale line, the rest of the crystal contours are barely visible. (d) An `average' ROC curve (red line) with upper and lower standard deviation bands (green lines). (e) A `worst-case' ROC curve for various confidences p (red for p = 0.05, green for p = 0.10, blue for p = 0.20).

Journal logoBIOLOGICAL
ISSN: 1399-0047
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