A collection of chapters from carefully chosen experts covering the theory behind the complex mathematical, statistical, and bioinformatics tools needed to extract, handle, and process data and their application to real data.
Molecular understanding of cancer and cancer progression is at the forefront of many research programs today. High-throughput array technologies and other modern molecular techniques produce a wealth of molecular data about the structure, and function of cells, tissues, and organisms. Correctly analyzed and interpreted these data hold the promise of bringing new markers for prognostic and diagnostic use, for new treatment schemes, and of gaining new biological insight into the evolution of cancer and its molecular, pathological, and clinical consequences. Aimed at graduates and researchers, this book discusses novel advances in informatics and statistics in molecular cancer research. Through eight chapters from carefully chosen experts it brings the reader up to date with specific topics in cancer research, how the topics give rise to development of new informatics and statistics tools, and how the tools can be applied. The focus of the book is to give the reader an understanding of key concepts and tools, rather than focusing on technical issues.; A main theme is the extensive use of array technologies in modern cancer research - gene expression and exon arrays, SNP and copy number arrays, and methylation arrays - to derive quantitative and qualitative statements about cancer, its progression and aetiology, and to understand how these technologies on one hand allow us learn about cancer tissue as a complex system and on the other hand allow us to pinpoint key genes and events as crucial for the development of the disease.
PREFACE; 1. Association Studies; 2. Methods for DNA Copy Number Derivations; 3. Methods for Derivation of LOH and Allelic Copy Numbers Using SNP Arrays; 4. Bioinformatics of gene expression and copy number data integration; 5. Analysis of DNA Methylation in Cancer; 6. Pathway Analysis: Pathway Signatures and Classification; 7. Two Methods for Comparing Genomic Data Across Independent Studies in Cancer Research: Meta-analysis and Oncomine Concepts Map; 8. Bioinformatic Approaches to the Analysis of Alternative Splicing Variants in Cancer Biology; INDEX