New research tools are too complex for easy answers, resea...(Clarke said. Everything is going on in a...),Health

We need to discover what specific genes perform which function. If we knew the rules what genes are involved in which process we should be able to understand some of the questions we have, but we are not there yet, he said.

Despite the lack of understanding, many studies have been published that link specific biomarkers −genes, mRNA or proteins − with an aspect of cancer development or treatment, and the results often appear to be statistically valid, Clarke said. But it is not clear that that solution is complete or is necessarily correct. It may be partly right and may be intuitively pleasing because you are getting what you expected to see from an experiment. That could be a trap, a self-fulfilling prophecy.

And while the findings may fit in the tumor samples they are tested in, they may not if other tumor tissue is studied, and many times researchers dont take that extra step, the researchers said in their article. The lack of rigorous validation is a problem that currently plagues cancer research, Clarke added.

Another pitfall in using the new technology is the curse of multi-dimensionality, Clarke said. You have a lot of measurements, and the statistical model gets very complicated. So sometimes you dont have enough computing power to derive the right answer or you get an answer that is only true for part of the data.

In other words, scientists dont always know what they dont know when looking at multi-dimensional data sets.

We still dont always have enough knowledge to know whether we have the answers right or not.