title: Using a single neuron as a marker selector: a breast cancer case study.
abstract: The problem of marker selection in DNA microarray analysis has been mostly addressed by linear methods. RFE-SVM is such a representative method where a linear kernel is used as the basic tool to address the problem. On the other hand a single neuron is known to be a linear estimator. In this study we explore such a single neuron to address the problem of marker selection.
authors.affiliation: Technical University of Crete, Department of Electronic and Computer Engineering, University Campus, Chania Crete, Greece. mblazad@ier.forthnet.gr
authors.forename: Michalis E
authors.initials: ME
authors.lastname: Blazadonakis
authors.forename: Aris
authors.initials: A
authors.lastname: Perperoglou
authors.forename: Michalis
authors.initials: M
authors.lastname: Zervakis
mesh_terms: D014408:Biomarkers, Tumor / Q000096:biosynthesis / Q000235:genetics*; D001943:Breast Neoplasms / Q000235:genetics* / Q000378:metabolism; D005260:Female; D020869:Gene Expression Profiling / Q000379:methods*; D015972:Gene Expression Regulation, Neoplastic; D006801:Humans; D016571:Neural Networks, Computer; D009474:Neurons; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods*
chemical_list: D014408:Biomarkers, Tumor