Skip to main content


Fig. 2 | BMC Biology

Fig. 2

From: WorMachine: machine learning-based phenotypic analysis tool for worms

Fig. 2

Success rates in classifying the worms’ sex as a function of the number of worms used for training. Shown are results when the fluorescence of a reporter expressed in sex-specific neurons was taken into account (dark blue, dots) and when only morphological and brightness features were considered (light blue, triangles). The classification is based on these morphological features: head BF, tail BF, area, length, midwidth, thickness, tail ratio, and on the following fluorescent features: peak number (count), corrected total worm fluorescence (CTWF), and mean peak intensity. The training set included 30–2000 worms, while the test set included 200 worms, 100 of each sex, randomly selected and excluded in advance

Back to article page