Overview

This book is a work on cancer pathogenic gene prediction and sample classification algorithms, which comprehensively and systematically elaborates on the latest research achievements in gene association analysis, gene regulatory network reconstruction, cancer pathogenic gene prediction, cancer sample classification, and new class identification. The book consists of 8 chapters, with chapters 1-4 introducing basic knowledge such as gene expression data and applications, analysis platforms and algorithms, and gene expression data preprocessing; Chapters 5 to 8 respectively elaborate on the four thematic achievements of cancer gene expression data analysis. Chapter 5 is a gene association analysis algorithm for gene regulatory networks, Chapter 6 is a cancer pathogenic gene prediction algorithm based on differential co expression adjacency networks, Chapter 7 is a Bayesian network disease sample classification algorithm based on gene association analysis, and Chapter 8 introduces a new class recognition algorithm for cancer gene expression data based on pattern similarity.

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