Strengths of artificial neural networks in modelling complex plant processes

被引:25
作者
Gago, Jorge [1 ]
Landin, Mariana [2 ]
Pablo Gallego, Pedro [1 ]
机构
[1] Univ Vigo, Fac Biol, Appl Plant & Soil Biol, Vigo, Spain
[2] Univ Santiago, Dept Pharm & Pharmaceut Technol, Fac Pharm, Santiago De Compostela, Spain
关键词
ANNs; artificial intelligence; predicting; optimization; plant model; plant tissue culture;
D O I
10.4161/psb.5.6.11702
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
Commonly, simple mathematical models can not be used to describe exactly the biological processes due to their higher complexity. In fact, most biological interactions cannot be elucidated by a simple stepwise algorithm or a precise formula, particularly when the data are complex or noisy. ANNs allows an accurate description of those kind of biological processes in plant science, offering new advantages over traditional treatments as the possibility of a model, prediction and optimize results. Different kind of data can be analyzed using a unique and "easy to use" technology. Researchers with a highly specialized mathematical background are not required and ANNs offer the possibility of achieving the whole view of the experimental study with a limited number of experiments and costs. Additionally, it is possible to add new inputs and outputs to the database to reach a new understanding.
引用
收藏
页码:743 / 745
页数:3
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