Name
Abstract | ||
|---|---|---|
This paper presents our computational and measurement strategy for investigating gene networks from gene expression data using state space model and dynamic Bayesian network model with nonparametric regression. These methods are applied to gene expression data based on gene knockdowns and drug responses for generating large global maps of gene regulation which will light up the geography where drug target pathways lie down. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1007/978-3-642-00727-9_8 | BICoB |
Keywords | Field | DocType |
state space model,large global map,gene networks,gene expression data,measurement strategy,drug response,gene regulation,dynamic bayesian network model,gene network,gene knockdowns,drug target pathway,dynamic bayesian network,drug targeting,nonparametric regression | Gene,Computer science,Nonparametric regression,State-space representation,Gene expression,Regulation of gene expression,Bayesian network,Artificial intelligence,Bioinformatics,Gene regulatory network,Machine learning,Dynamic Bayesian network | Conference |
Volume | ISSN | Citations |
5462 | 0302-9743 | 0 |
PageRank | References | Authors |
0.34 | 9 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Satoru Miyano | 1 | 2406 | 250.71 |
| Rui Yamaguchi | 2 | 180 | 26.49 |
| Yoshinori Tamada | 3 | 203 | 19.46 |
| Masao Nagasaki | 4 | 368 | 26.22 |
| Seiya Imoto | 5 | 975 | 84.16 |