Published online by Cambridge University Press: 23 November 2009
DNA microarray technology enables us to monitor the expression levels of thousands of genes simultaneously, and hence helps to obtain a better picture of the interactions between the genes. In order to understand the biological structure underlying these gene interactions, we present here a statistical approach to model the functional relationship between genes and also between genes and disease status. We suggest a hierarchical Bayesian model based on multivariate adaptive regression splines (MARS) to model these complex nonlinear interaction functions. The novelty of the approach lies in the fact that we attempt to capture the complex nonlinear dependencies between the genes which otherwise would have been missed by linear approaches. Owing to the large number of genes (variables) and the complexity of the data, we use Markov Chain Monte Carlo (MCMC) based stochastic search algorithms to choose among models. The Bayesian model is flexible enough to identify significant genes as well as model the functional relationships between them. The effectiveness of the proposed methodology is illustrated using two publicly available microarray data sets: leukemia and hereditary breast cancer.
DNA microarray technology has revolutionized biological and medical research. The use of DNA microarrays allows simultaneous monitoring of the expressions of thousands of genes (Schena et al. 1995; Duggan et al. 1999), and has emerged as a tool for disease diagnosis. This technology promises to monitor the whole genome on a single chip so that researchers can have a better picture of the interactions among thousands of genes simultaneously.
To save this book to your Kindle, first ensure email@example.com is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about saving to your Kindle.
Note you can select to save to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.
Find out more about the Kindle Personal Document Service.
To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Dropbox.
To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Google Drive.