Finding differentially expressed genes for pattern generation

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Date

2005-02-15

Author

Abul, O
Alhajj, R
Polat, Faruk
Barker, K

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Motivation: It is important to consider finding differentially expressed genes in a dataset of microarray experiments for pattern generation. Results: We developed two methods which are mainly based on the q-values approach; the first is a direct extension of the q-values approach, while the second uses two approaches: q-values and maximum-likelihood. We present two algorithms for the second method, one for error minimization and the other for confidence bounding. Also, we show how the method called Patterns from Gene Expression (PaGE) (Grant et al., 2000) can benefit from q-values. Finally, we conducted some experiments to demonstrate the effectiveness of the proposed methods; experimental results on a selected dataset (BRCA1 vs BRCA2 tumor types) are provided

Subject Keywords

Statistics and Probability, Computational Theory and Mathematics, Biochemistry, Molecular Biology, Computational Mathematics, Computer Science Applications

URI

https://hdl.handle.net/11511/48041

Journal

BIOINFORMATICS

DOI

https://doi.org/10.1093/bioinformatics/bti189

Collections

Department of Computer Engineering, Article

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Citation Formats

O. Abul, R. Alhajj, F. Polat, and K. Barker, “Finding differentially expressed genes for pattern generation,” BIOINFORMATICS, pp. 445–450, 2005, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/48041.