Main Article Content
Understanding the biology of health and diseases such as cancer, generating insight into the triggers and potentiators of disease and the development of therapeutic approaches to counter and treat disease requires detailed interrogation of inherited genes, and the dynamic positioning of the transcriptome and proteome. In the last 10 years, significant technological developments and increases in sample throughput capabilities have led to a dramatic increase in the size and complexity of the datasets that can be generated. A key challenge now is to develop robust approaches for analysing and interpreting these, and converting data into biologically- and clinically-relevant information. Herein, we provide an overview of approaches for acquiring, integrating and interpreting complex datasets generated using multiple omic platforms, with a focus on the field of cancer research, and highlight key successful data handling and integration applications.
Downloads month by month
Download data is not yet available.