The Analysis of Yeast Cell Morphology Using a Robot Scientist

Author

Liu, Yihui ; Martin, Katherine ; Sparkes, Andrew ; King, Ross D.

Author_Institution

Sch. of Inf. Sci. & Technol., Shandong Inst. of Light Ind., Jinan, China

fYear

2010

fDate

11-14 Dec. 2010

Firstpage

10

Lastpage

14

Abstract

We have developed image analysis methods to analyse the morphology of the budding yeast (Saccharomyces cerevisiae) cell. Experiments were performed on four deletant strains: ΔYLR371w, ΔYDR349c, ΔYLR192c, and ΔYDR414c. Our results show that our image analysis software provides an efficient way to automatically obtain quantitative morphology features of yeast cells. Our research show significant differences from those previously published for these strains. These differences may be due to different growth conditions or the use of unfixed cells. More research is required to understand the complex relationship between genotype and environment in yeast morphology.

Keywords

biology computing; cellular biophysics; control engineering computing; crystal morphology; medical image processing; medical robotics; robot vision; ΔYDR349c strain; ΔYDR414c strain; ΔYLR192c strain; ΔYLR371w strain; Saccharomyces cerevisiae cell; genotype; growth condition; image analysis; robot scientist; yeast cell morphology; Robot Eve; automating analysis; morphology features; yeast cell image;

fLanguage

English

Publisher

ieee

Conference_Titel

Computational Intelligence and Security (CIS), 2010 International Conference on

Conference_Location

Nanning

Print_ISBN

978-1-4244-9114-8

Electronic_ISBN

978-0-7695-4297-3

Type

conf

DOI

10.1109/CIS.2010.10

Filename

5696221