The Biological Data Analysis Laboratories at IUSCC and Purdue University
Processed samples will undergo lipidomic, oxidative stress, and SNP analysis at the IU Simon Cancer Center and global proteomic, glycoproteomic and metabolomic analysis at Purdue University.
These analyses are a major focus of the CCE project. They will serve as the basis for the statistical modeling that will provide the molecular signatures to be rapidly tested in the IUSCC clinics, identifying those that can accurately predict CRC susceptibility and treatment outcomes for diagnosed CRC patients.
We will integrate OMIC data from four disparate datasets: Genomic (SNP), Biological assays, Mass Spectrometry (MS), and Nuclear Magnetic Resonance (NMR). While the data integration effort will be a significant challenge, the integration is also the great promise of the CCE project.
The power of the iterative approach we propose is that
- More patient and control data will continually be accrued and added to the CCE system
- Novel technologies to generate additional OMIC data will continue to emerge and will be rapidly applied
- As additional data is supplied to the system, models will continue to improve in their predictive ability.
Researchers should cite this work as follows:
(2008), "Biological Data Analysis Laboratories," http://ccehub.org/resources/103.