PMID- 22368387
OWN - NLM
STAT- PubMed-not-MEDLINE
DCOM- 20120823
LR  - 20240322
IS  - 0973-2063 (Electronic)
IS  - 0973-2063 (Linking)
VI  - 8
IP  - 3
DP  - 2012
TI  - Evaluation of data integration strategies based on kernel method of clinical and 
      microarray data.
PG  - 147-50
AB  - The cancer classification problem is one of the most challenging problems in 
      bioinformatics. The data provided by Netherland Cancer Institute consists of 295 
      breast cancer patient; 101 patients are with distant metastases and 194 patients 
      are without distant metastases. Combination of features sets based on kernel 
      method to classify the patient who are with or without distant metastases will be 
      investigated. The single data set will be compared with three data integration 
      strategies and also weighted data integration strategies based on kernel method. 
      Least Square Support Vector Machine (LS-SVM) is chosen as the classifier because 
      it can handle very high dimensional features, for instance, microarray data. The 
      experiment result shows that the performance of weighted late integration and the 
      using of only microarray data are almost similar. The data integration strategy 
      is not always better than using single data set in this case. The performance of 
      classification absolutely depends on the features that are used to represent the 
      object.
FAU - Noviyanto, Ary
AU  - Noviyanto A
AD  - Faculty of Computer Science, Universitas Indonesia.
FAU - Wasito, Ito
AU  - Wasito I
LA  - eng
PT  - Journal Article
DEP - 20120203
PL  - Singapore
TA  - Bioinformation
JT  - Bioinformation
JID - 101258255
PMC - PMC3283887
EDAT- 2012/03/01 06:00
MHDA- 2012/03/01 06:01
PMCR- 2012/01/01
CRDT- 2012/02/28 06:00
PHST- 2012/01/19 00:00 [received]
PHST- 2012/01/20 00:00 [accepted]
PHST- 2012/02/28 06:00 [entrez]
PHST- 2012/03/01 06:00 [pubmed]
PHST- 2012/03/01 06:01 [medline]
PHST- 2012/01/01 00:00 [pmc-release]
AID - 97320630008147 [pii]
AID - 10.6026/97320630008147 [doi]
PST - ppublish
SO  - Bioinformation. 2012;8(3):147-50. doi: 10.6026/97320630008147. Epub 2012 Feb 3.