Springer Modern Molecular Biology:: Approaches for Unbiased Discovery in Cancer Research (Applied Bioinformatics and Biostatistics in Cancer Research)

Molecular biology has rapidly advanced since the discovery of the basic flow of information in life, from DNA to RNA to proteins. While there are several important and interesting exceptions to this general flow of information, the importance of these biological macromolecules in dictating the phenotypic nature of living creatures in health and disease is paramount. In the last one and a half decades, and particularly after the completion of the Human Genome Project, there has been an explosion of technologies that allow the broad characterization of these macromolecules in physiology, and the perturbations to these macromolecules that occur in diseases such as cancer. In this volume, we will explore the modern approaches used to characterize these macromolecules in an unbiased, systematic way. Such technologies are rapidly advancing our knowledge of the coordinated and complicated changes that occur during carcinogenesis, and are providing vital information that, when correctly interpreted by biostatistical/bioinformatics analyses, can be exploited for the prevention, diagnosis, and treatment of human cancers. The purpose of this volume is to provide an overview of modern molecular biological approaches to unbiased discovery in cancer research. Advances in molecular biology allowing unbiased analysis of changes in cancer initiation and progression will be overviewed. These include the strategies employed in modern genomics, gene expression analysis, and proteomics. From the Back Cover A convergence of advancements in molecular biology, engineering, computer science, biostatistics and other disciplines has made possible the development of technologies facilitating the massively parallel investigation of the complex biological phenomena driving cancer initiation and progression. Such technologies include DNA microarrays, next generation sequencing, proteomics technologies, and tissue microarrays. In order to properly harness these technologies to imaginatively decipher these complex biological processes, scientists must have an understanding of the underlying technology, be able to adapt these technologies with molecular biology lab approaches, and then be poised to efficiently process and interpret the extremely high dimensional and complex data sets that are generated by these technologies. The primary purpose of this volume is to help bridge the gap between molecular biologists and cancer researchers and the bioinformatics and computational biology researchers by providing an overview of these technologies to those that are not yet familiar with them.