Sun J, Song W Y, Zhu L H, Chen R S
Institute of Biophysics, Academia Sinica, Beijing, People's Republic of China.
J Comput Biol. 1995 Fall;2(3):409-16. doi: 10.1089/cmb.1995.2.409.
The quantitative similarity among tRNA gene sequences was acquired by analysis with an artificial neural network. The evolutionary relationship derived from our results was consistent with those from other methods. A new sequence was recognized to be a tRNA-like gene by a neural network on the analysis of similarity. All of our results showed the efficiency of the artificial neural network method in the sequence analysis for biological molecules.
通过人工神经网络分析获得了tRNA基因序列之间的定量相似性。从我们的结果得出的进化关系与其他方法得出的结果一致。在相似性分析中,一个新序列通过神经网络被识别为类tRNA基因。我们所有的结果都表明了人工神经网络方法在生物分子序列分析中的有效性。