Dna Microarray Technology And Data Analysis In Cancer Research
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Dna Microarray Technology And Data Analysis In Cancer Research
DNA microarray technology has become a useful technique in gene expression analysis for the development of new diagnostic tools and for the identification of disease genes and therapeutic targets for human cancers. Appropriate control for DNA microarray experiment and reliable analysis of the array data are key to performing the assay and utilizing the data correctly. The most difficult challenge has been the lack of a powerful method to analyze the data for all genes (more than 30,000 genes) simultaneously and to use the microarray data in a decision-making process. In this book, the authors describe DNA microarray technology and data analysis by pointing out current advantages and disadvantages of the technique and available analytical methods. Crucially, new ideas and analytical methods based on the authors' own experience in DNA microarray study and analysis are introduced. It is believed that this new way of interpreting and analyzing microarray data will bring us closer to success in decision-making using the information obtained through the DNA microarray technology.
High-Dimensional Data Analysis in Cancer Research
Author: Xiaochun Li
language: en
Publisher: Springer Science & Business Media
Release Date: 2008-12-19
Multivariate analysis is a mainstay of statistical tools in the analysis of biomedical data. It concerns with associating data matrices of n rows by p columns, with rows representing samples (or patients) and columns attributes of samples, to some response variables, e.g., patients outcome. Classically, the sample size n is much larger than p, the number of variables. The properties of statistical models have been mostly discussed under the assumption of fixed p and infinite n. The advance of biological sciences and technologies has revolutionized the process of investigations of cancer. The biomedical data collection has become more automatic and more extensive. We are in the era of p as a large fraction of n, and even much larger than n. Take proteomics as an example. Although proteomic techniques have been researched and developed for many decades to identify proteins or peptides uniquely associated with a given disease state, until recently this has been mostly a laborious process, carried out one protein at a time. The advent of high throughput proteome-wide technologies such as liquid chromatography-tandem mass spectroscopy make it possible to generate proteomic signatures that facilitate rapid development of new strategies for proteomics-based detection of disease. This poses new challenges and calls for scalable solutions to the analysis of such high dimensional data. In this volume, we will present the systematic and analytical approaches and strategies from both biostatistics and bioinformatics to the analysis of correlated and high-dimensional data.
Cancer Diagnostics with DNA Microarrays
Authored by an international authority in the field,Cancer Diagnostics with DNA Microarrays is a complete reference work on the rapidly growing use of DNA microarray data in the diagnosis of and treatment planning for a large number of human cancers. Uniquely deals with direct clinical application of microarray data to oncology diagnosis, leading to more effective diagnosis of and clearer treatment regimens for a wide range of human cancers Offers clinicians summary presentation of state-of-the-art science of DNA microarrays Each chapter includes bibliographic and further reading suggestions Easily accessible, assuming no special training in statistics or bioinformatics Replete with examples and mini-cases, Cancer Diagnostics with DNA Microarrays offers cancer researchers in private, pharmacologic, and governmental institutions, biomedical statisticians, and practicing oncologists concise, thoughtfully authored guidance on the use of microarray data and analysis as clinical tools. The text carefully addresses the needs of end users – researchers and physicians – using microarrays as a tool to be applied in common clinical situations, and is of interest for students in medicine and biology and professionals in health care as well.