Name
Abstract | ||
|---|---|---|
Classification is a major task in the gene sequence analysis. Based on the general principle of artificial immune system, this paper first constructed a classifier which inducted antibody-antigen identification, immune colonel reproduction, hypermutation, affinity mature and the network suppression, by simulating how the antigens stimulate the immune network and how the immune network responds. Then, a "leave-one-out" method was adopted to test the classifier's performance, applying 1-20th DNA sequences of Art-model-data with class attribute. Its accuracy was up to 90%. At last, a well-pleasing result was got on the prediction of 21-40th DNA sequences of Art-model-data. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1109/FSKD.2008.126 | FSKD (2) |
Keywords | Field | DocType |
immune evolution network,class attribute,network suppression,immune colonel reproduction,general principle,antibody-antigen identification,dna sequence,major task,gene sequence analysis,artificial immune system,immune network,dna sequences classification,amino acids,classification algorithms,genetic algorithms,sequence analysis,dna,artificial immune systems,biology,immune system,hypermutation,artificial intelligence,dna sequences,data mining,classification | Artificial immune system,Somatic hypermutation,Gene,Antigen,Pattern recognition,Computer science,Artificial intelligence,DNA sequencing,Statistical classification,Classifier (linguistics),Sequence analysis | Conference |
Citations | PageRank | References |
0 | 0.34 | 4 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Lianhong Wang | 1 | 0 | 0.34 |
| Jing Zhang | 2 | 40 | 7.49 |
| Xiaofeng Huang | 3 | 0 | 0.34 |
| Gufeng Gong | 4 | 0 | 0.34 |