Computational Geometric Analysis for <i>C. elegans</i> Trajectories on Thermal and Salinity Gradient

• DOI: 10.4236/ajcm.2020.104033
• Publication Date: 2020-12-17T09:40:08Z
• Authors: Yuetan Chu
• Keywords: 0202 electrical engineering, electronic engineering, information engineering; 02 engineering and technology

Elegans are one of the best model organisms in neural researches, and tropism movement is a typical learning memorizing activity. Based on imaging technique called Fast Track-Capturing Microscope (FTCM), we investigated regulation. Two patterns extracted from various trajectories through analysis turning angle. Then applied this classification trajectory regulation compound gradient field, theoretical results corresponded with experiments well, which can initially verify conclusion. Our breakthrough performed computational geometric trajectories. Several independent features were combined to describe properties by principal composition (PCA) support vector machine (SVM). After normalizing all data sets, no-supervising was processed along some training under certain supervision. The final perfectly, indicates further application such biology researches combining learning.