TY - JOUR
T1 - Comparison of data-merging methods with SVM attribute selection and classification in breast cancer gene expression
AU - Bevilacqua, Vitoantonio
AU - Pannarale, Paolo
AU - Abbrescia, Mirko
AU - Cava, Claudia
AU - Paradiso, Angelo
AU - Tommasi, Stefania
PY - 2012/5/8
Y1 - 2012/5/8
N2 - Background: DNA microarray data are used to identify genes which could be considered prognostic markers. However, due to the limited sample size of each study, the signatures are unstable in terms of the composing genes and may be limited in terms of performances. It is therefore of great interest to integrate different studies, thus increasing sample size.Results: In the past, several studies explored the issue of microarray data merging, but the arrival of new techniques and a focus on SVM based classification needed further investigation. We used distant metastasis prediction based on SVM attribute selection and classification to three breast cancer data sets.Conclusions: The results showed that breast cancer classification does not benefit from data merging, confirming the results found by other studies with different techniques.
AB - Background: DNA microarray data are used to identify genes which could be considered prognostic markers. However, due to the limited sample size of each study, the signatures are unstable in terms of the composing genes and may be limited in terms of performances. It is therefore of great interest to integrate different studies, thus increasing sample size.Results: In the past, several studies explored the issue of microarray data merging, but the arrival of new techniques and a focus on SVM based classification needed further investigation. We used distant metastasis prediction based on SVM attribute selection and classification to three breast cancer data sets.Conclusions: The results showed that breast cancer classification does not benefit from data merging, confirming the results found by other studies with different techniques.
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U2 - 10.1186/1471-2105-13-S7-S9
DO - 10.1186/1471-2105-13-S7-S9
M3 - Article
C2 - 22595006
AN - SCOPUS:84871305967
VL - 13
JO - BMC Bioinformatics
JF - BMC Bioinformatics
SN - 1471-2105
IS - SUPPL.7
M1 - S9
ER -