The challenge is no longer how to generate these vast bodies of genomic data, but rather in how to best collect, manage, and analyze the data.
by John Quackenbush
Changing these algorithms (used to convert spot flurescence to gene-expression estimates.) can make a difference, and you can turn an experiement that looks just so-so into something that looks powerful and precise.
by Rafael S. Irizarry
We are facing too many options for analyzing the same data set, and there has not been adequate scientific vetting of the capabilities and and limitations of available methods.
by Leming Shi
High-quality samples and high-tech instrumentation alone won't save the microarray experiment. Some of the most fundamental challenges lie in gleaning biological signicance from mounds of data and designing experiments with a statistically sound foundation
by Michael Eisenstein