Biomarker Discovery based on BBHA and AdaboostM1 on Microarray Data for Cancer Classification


PASHAEI E., Ozen M., AYDIN N.

38th Annual International Conference of the IEEE-Engineering-in-Medicine-and-Biology-Society (EMBC), Florida, Amerika Birleşik Devletleri, 16 - 20 Ağustos 2016, ss.3080-3083 identifier identifier identifier

  • Yayın Türü: Bildiri / Tam Metin Bildiri
  • Doi Numarası: 10.1109/embc.2016.7591380
  • Basıldığı Şehir: Florida
  • Basıldığı Ülke: Amerika Birleşik Devletleri
  • Sayfa Sayıları: ss.3080-3083
  • Anahtar Kelimeler: Gene selection, AdaboostM1, binary black hole algorithm, cancer classification
  • Yıldız Teknik Üniversitesi Adresli: Evet

Özet

In this paper, a new approach based on Binary Black Hole Algorithm (BBHA) and Adaptive Boosting version M1 (AdaboostM1) is proposed for finding genes that can classify the group of cancers correctly. In this approach, BBHA is used to perform gene selection and AdaboostM1 with 10-fold cross validation is adopted as the classifier. Also, to find the relation between the biomarkers for biological point of view, decision tree algorithm (C4.5) is utilized. The proposed approach is tested on three benchmark microarrays. The experimental results show that our proposed method can select the most informative gene subsets by reducing the dimension of the data set and improve classification accuracy as compared to several recent studies.