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

• 作者: Yuetan Chu
• 来源期刊: 美国计算数学期刊(英文)
• 学科: 工学
• 关键词: C. elegans TROPISM Trajectories Classification Computational Geometric Analysis PCA
• 年，卷（期）: 2020,（4）
• 页码范围: 578-590
• 页数: 13页
• 分类号: TP3

摘要

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