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SAM Method as an Approach to Select Candidates for Human Prostate Cancer Markers

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Advances in Bioinformatics and Computational Biology (BSB 2005)

Part of the book series: Lecture Notes in Computer Science ((LNBI,volume 3594))

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Abstract

In order to select gene markers among differentially expressed transcripts identified from tumoral prostate, we have applied a filter and Significance Analysis of Microarrays (SAM) as the feature selection method on a previously normalized dataset of DNA microarray experiments reported by Reis et al., 2004 (Oncogene 23:6684-6692). Twenty seven samples with different degrees of tumor differentiation (Gleason scores) were analyzed. SAM was run using either two-class, unpaired data analysis with Gleason 5-6 and Gleason 9-10 samples, or multiclass response analysis with an additional category of Gleason 7-8. Both strategies revealed a promising set of transcripts associated with the degree of differentiation of prostate tumors.

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© 2005 Springer-Verlag Berlin Heidelberg

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Simoes, A.C.Q., da Silva, A.M., Verjovski-Almeida, S., Reis, E.M. (2005). SAM Method as an Approach to Select Candidates for Human Prostate Cancer Markers. In: Setubal, J.C., Verjovski-Almeida, S. (eds) Advances in Bioinformatics and Computational Biology. BSB 2005. Lecture Notes in Computer Science(), vol 3594. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11532323_23

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  • DOI: https://doi.org/10.1007/11532323_23

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-28008-8

  • Online ISBN: 978-3-540-31861-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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