Learning Phenotype Structure Using Sequence Model
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: 2014شناسه الکترونیک: 10.1109/TKDE.2013.31
کلیدواژه(گان): biology computing,computational complexity,data mining,learning (artificial intelligence),molecular biophysics,FINDER algorithm,NP-complete problem,biological significance,expression pattern,expression signature,g*-sequence model,gene expression data sets,gene ordered expression values,microarray data analysis,microarray technologies,phenotype structure discovery,phenotype structure learning,pruning strategies,sequence model,statistical significance,trivial g*-sequences ident
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Learning Phenotype Structure Using Sequence Model
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| contributor author | Yuhai Zhao | |
| contributor author | Guoren Wang | |
| contributor author | Xiang Zhang | |
| contributor author | Yu, Jeffrey Xu | |
| contributor author | Zhanghui Wang | |
| date accessioned | 2020-03-12T18:23:50Z | |
| date available | 2020-03-12T18:23:50Z | |
| date issued | 2014 | |
| identifier issn | 1041-4347 | |
| identifier other | 6522406.pdf | |
| identifier uri | https://libsearch.um.ac.ir:443/fum/handle/fum/957091?locale-attribute=fa | |
| format | general | |
| language | English | |
| publisher | IEEE | |
| title | Learning Phenotype Structure Using Sequence Model | |
| type | Journal Paper | |
| contenttype | Metadata Only | |
| identifier padid | 7989268 | |
| subject keywords | biology computing | |
| subject keywords | computational complexity | |
| subject keywords | data mining | |
| subject keywords | learning (artificial intelligence) | |
| subject keywords | molecular biophysics | |
| subject keywords | FINDER algorithm | |
| subject keywords | NP-complete problem | |
| subject keywords | biological significance | |
| subject keywords | expression pattern | |
| subject keywords | expression signature | |
| subject keywords | g*-sequence model | |
| subject keywords | gene expression data sets | |
| subject keywords | gene ordered expression values | |
| subject keywords | microarray data analysis | |
| subject keywords | microarray technologies | |
| subject keywords | phenotype structure discovery | |
| subject keywords | phenotype structure learning | |
| subject keywords | pruning strategies | |
| subject keywords | sequence model | |
| subject keywords | statistical significance | |
| subject keywords | trivial g*-sequences ident | |
| identifier doi | 10.1109/TKDE.2013.31 | |
| journal title | Knowledge and Data Engineering, IEEE Transactions on | |
| journal volume | 26 | |
| journal issue | 3 | |
| filesize | 2510907 | |
| citations | 0 |