Publication type: Conference paper
Type of review: Not specified
Title: Quality assessment of Affymetrix GeneChip data using the EM algorithm and a naïve Bayes classifier
Authors: Howard, Brian E.
Sick, Beate
Perera, Imara
Im, Yang Ju
Winter-Sederoff, Heike
Heber, Steffen
DOI: 10.1109/BIBE.2007.4375557
Proceedings: 2007 IEEE 7th International Symposium on BioInformatics and BioEngineering
Conference details: 7th International Conference on BioInformatics and BioEngineering, Boston, USA, 14-17 October 2007
Issue Date: 2007
Publisher / Ed. Institution: IEEE
ISBN: 1-4244-1509-8
978-1-4244-1509-0
Language: English
Subjects: Quality assessment; Classification; Microarray
Subject (DDC): 570: Biology
Abstract: Recent research has demonstrated the utility of using supervised classification systems for automatic identification of low quality microarray data. However, this approach requires annotation of a large training set by a qualified expert. In this paper we demonstrate the utility of an unsupervised classification technique based on the Expectation-Maximization (EM) algorithm and naive Bayes classification. On our test set, this system exhibits performance comparable to that of an analogous supervised learner constructed from the same training data.
URI: https://digitalcollection.zhaw.ch/handle/11475/14001
Fulltext version: Published version
License (according to publishing contract): Licence according to publishing contract
Departement: School of Engineering
Organisational Unit: Institute of Data Analysis and Process Design (IDP)
Appears in collections:Publikationen School of Engineering

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