Premium
Recognition of culture state using two‐dimensional gel electrophoresis with an artificial neural network
Author(s) -
Izawa Naoki,
Kishimoto Michimasa,
Konishi Masaaki,
Omasa Takeshi,
Shioya Suteaki,
Ohtake Hisao
Publication year - 2006
Publication title -
proteomics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.26
H-Index - 167
eISSN - 1615-9861
pISSN - 1615-9853
DOI - 10.1002/pmic.200500542
Subject(s) - artificial neural network , biochemical engineering , biological system , yeast , artificial intelligence , computer science , chemistry , microbiology and biotechnology , pattern recognition (psychology) , biology , biochemistry , engineering
Proteomic technologies were applied to the examination of nutrient components in culture broth. In bioprocesses, many types of media have been proposed and used on the commercial scale. Natural nutrients, the chemical components of which cannot be identified completely, are often used in fermentation processes such as in the production of baker's yeast, alcoholic beverages, amino acids, and pharmaceuticals. The catabolic activities of the microorganisms in these processes vary with the species used. We used an artificial neural network (ANN) to recognize the sufficiency of chemical elements based on the protein spots resolved in 2‐DE, and we evaluated this technique using the leave‐one‐out method. We also attempted to reduce the number of input data for spot selection based on sensitivity analysis of the ANN, and the selected data were used to improve accuracy.