Exploration of carcinogenesis based on tree models using CGH data
应用CGH数据和树模型探索癌症的发病机理

Comparative genomic hybridization (CGH) can detect chromosomal deletions and amplifications of tumors, and various laboratories and public databases have accumulated a large number of CGH data, providing the opportunity to analyze the molecular mechanism of tumorigenesis in the whole genome. Tree models are generally used to study the history of biological formation and evolution in the field of bioinformatics, and evolutionary relationships between species are usually represented using phylogenetic tree. Tree models are also powerful bioinformatics tools to analyze CGH data and explore carcinogenesis. Two common tree models, the branching tree and the distanced-based tree, as well as their basic principles, methods are introduced detailedly, several technical problems in construction of tree models are discussed, and their applications in cancer research are reviewed systematically in this paper. As a generalization of single path linear model, tree models can more accurately conclude multigene, multistep, multipathway process of tumorigenesis, exploring the molecular mechanism of tumorigenesis from different angels. Apart from CGH data, tree models can be used to analyze various types of data, including high-resolution data (e.g., array-CGH data).