Inferring Microarray Relevance By Enrichment Of Chemotherapy Resistance-Based MicroRNA Sets

Acici K., Ogul H.

19th IEEE International Conference on Intelligent Engineering Systems (INES), Bratislava, Slovakya, 3 - 05 Eylül 2015, ss.389-393 identifier identifier

  • Yayın Türü: Bildiri / Tam Metin Bildiri
  • Doi Numarası: 10.1109/ines.2015.7329740
  • Basıldığı Şehir: Bratislava
  • Basıldığı Ülke: Slovakya
  • Sayfa Sayıları: ss.389-393
  • Anahtar Kelimeler: microRNA, information retrieval, content-based search, gene expression database, EXPRESSION PROFILES, GENE-EXPRESSION, RETRIEVAL, GENOMICS, DATABASE
  • Ankara Üniversitesi Adresli: Hayır

Özet

Inferring relevance between microarray experiments stored in a gene expression repository is a helpful practice for biological data mining and information retrieval studies. In this study, we propose a knowledge-based approach for representing microarray experiment content to be used in such studies. The representation scheme is specifically designed for inferring a disease-associated relevance of microRNA experiments. A group of annotated microRNA sets based on their chemotherapy resistance are used for a statistical enrichment analysis over observed expression data. A query experiment is then represented by a single dimensional vector of these enrichment statistics, instead of raw expression data. According to the results, new representation scheme can provide a better retrieval performance than traditional differential expression-based representation.