Name
Abstract | ||
|---|---|---|
DNA sequences of several bacteria were classified using artificial neural network model. The “dinucleotides compositions” method was used to characterize the DNA sequences which transform every DNA sequence to a 16-dimension vector. Back-propagation artificial neural network was developed and trained using “leave-one-out” method. Results showed that the accuracy of classification was 84.3%, which proved that the model was satisfactory in summary. However, the author stated that the applicability of the characterization strategy needs to be improved. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1109/ISCID.2009.244 | ISCID (2) |
Keywords | Field | DocType |
16-dimension vector,back-propagation artificial neural network,dna sequence,dinucleotides composition,characterization strategy,dinucleotide compositions,artificial neural network model,data mining,artificial neural networks,back propagation,neural nets,biotechnology,dna,microorganisms,bacteria,artificial neural network,accuracy,bioinformatics,data analysis,backpropagation,genomics | Artificial neural network model,Pattern recognition,Computer science,Genomics,DNA,DNA sequencing,Artificial intelligence,Backpropagation,Artificial neural network,Machine learning | Conference |
Citations | PageRank | References |
1 | 0.36 | 2 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Wei You | 1 | 11 | 4.20 |
| Kun Wang | 2 | 36 | 10.73 |
| Huixiao Li | 3 | 1 | 0.69 |
| Yang Jia | 4 | 1 | 0.36 |
| Xiaoqin Wu | 5 | 1 | 0.69 |
| Yaning Du | 6 | 1 | 0.69 |