Analyzing the locomotory gaitprint of Caenorhabditis elegans on the basis of empirical mode decomposition.

ABSTRACT: The locomotory gait analysis of the microswimmer, Caenorhabditis elegans, is a commonly adopted approach for strain recognition and examination of phenotypic defects. Gait is also a visible behavioral expression of worms under external stimuli. This study developed an adaptive data analysis method based on empirical mode decomposition (EMD) to reveal the biological cues behind intricate motion. The method was used to classify the strains of worms according to their gaitprints (i.e., phenotypic traits of locomotion). First, a norm of the locomotory pattern was created from the worm of interest. The body curvature of the worm was decomposed into four intrinsic mode functions (IMFs). A radar chart showing correlations between the predefined database and measured worm was then obtained by divi

SUBMITTER: Lin LC 

PROVIDER: S-EPMC5524362 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature