Design of Classifier to Automate the Evaluation of Protein Crystallization States

– This paper presents a method for designing classifier to automate an evaluation process of protein crystallization growth states. The classifier is designed by binary decision tree and its classification sequence is decided in descending order of classification accuracy. Furthermore, for applying to automated crystallization system, some functions reducing mis-classification are appended to the classifier. The performance of this method has been evaluated by comparing classification result by using proposed method with the result by manual classification.

• Type: Conference
• Year: 2006
• Where: ICRA
• Authors: Kanako Saitoh, Kuniaki Kawabata, Hajime Asama, Taketoshi Mishima, Mitsuaki Sugahara
• Keywords: Binary Decision Tree, Classification Sequence, ICRA 2006, Protein Crystallization Growth, Robotics