Overview of Cancer Gene Diagnosis

Shuichi Shinmura ()
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Shuichi Shinmura: Seikei University

Chapter Chapter 2 in High-dimensional Microarray Data Analysis, 2019, pp 45-93 from Springer

Abstract: Abstract This chapter explains the cancer gene diagnosis using all Small Matryoshkas (SMs) of six microarrays found in 2016. Section 2.2 explains the different role of cancer gene analysis and cancer gene diagnosis because these technical terms are our original ones. Section 2.3 shows the analysis of 64 SMs obtained by RIP using Alon’s microarray. Section 2.4 shows the usefulness of 64RIP discriminant scores (RipDSs) and new data made by 64 RipDSs instead of 2,000 genes. Thus, we consider RipDSs new data is signal instead of 64 SM. Section 2.5 shows the same analysis of 130 BGSs of Alon’s microarray found by LINGO Program4 in 2016. BGS is as same as the Yamanaka’s four genes in iPS research. Section 2.6 shows the cancer gene diagnosis of other five microarrays those are analyzed in the same way as Alon. Section 2.7 is the conclusion. Alon and Singh’s microarrays consist of cancer and normal classes. Other four microarrays consist of two different types of cancer classes. It is vital for us that six results are almost the same. Thus, we expect another microarray’s result is as same as our results if medical researchers control two classes strictly.

Keywords: Gene diagnosis; Malignant indicators; Small Matryoshka (SM); Basic gene subspace (BGS); Discriminant scores (DSs); RatioSV of RIP and PCA (search for similar items in EconPapers)
Date: 2019
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DOI: 10.1007/978-981-13-5998-9_2

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