Name
Abstract | ||
|---|---|---|
In this study we analyze microarray data sets which monitor the gene expression levels of human peripheral blood cells during differentiation from monocytes to macrophages. We show that matrix decomposition techniques are able to identify relevant signatures in the deduced matrices and extract marker genes from these gene expression profiles. With these marker genes corresponding test; data sets call then easily be classified into related diagnostic categories. The latter correspond to either monocytes vs macrophages or healthy vs Niemann Pick C diseased patients. Our results demonstrate that. these methods are able to identify suitable marker genes which call be used to classify the type of cell lines investigated. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1007/978-3-540-85861-4_17 | 2ND INTERNATIONAL WORKSHOP ON PRACTICAL APPLICATIONS OF COMPUTATIONAL BIOLOGY AND BIOINFORMATICS (IWPACBB 2008) |
Keywords | Field | DocType |
gene expression,microarray analysis,microarray data,cell line,knowledge base,matrix decomposition,matrix factorization | Gene,Biology,Pattern recognition,Matrix (mathematics),Matrix decomposition,Gene expression,Microarray analysis techniques,Non-negative matrix factorization,Independent component analysis,Artificial intelligence,Test data | Conference |
Volume | ISSN | Citations |
49 | 1615-3871 | 0 |
PageRank | References | Authors |
0.34 | 7 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Reinhard Schachtner | 1 | 17 | 3.10 |
| Dominik Lutter | 2 | 158 | 9.67 |
| Ana Maria Tomé | 3 | 163 | 30.42 |
| Gerd Schmitz | 4 | 40 | 2.30 |
| Pedro Gómez Vilda | 5 | 289 | 52.48 |
| Elmar Wolfgang Lang | 6 | 260 | 36.10 |