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=en&show=full | |
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 | |