When faced with extracting biological meaning from complex and noisy ‘omics data, practicing the art of Zen biology can pay dividends.
Noise, variability and lots of it: that is the nature of biological research. Once biomolecules are removed from the living cell, they become vulnerable, unstable, transient. Aggregation, contamination, degradation, dissociation, fragmentation, oxidation, and precipitation, are a just few sources of noise-causing instability worth serious meditation. Then layer in biological complexity and variation due to genetic factors: mutation, recombination, translocation, etc. Next, pile on noise from sample processing, instrument platform, detection method, and then just try to make sense of it all. It is quite easy to see why biological research is often called “more art than science” – and it’s a bit of a wonder that discoveries are made at all.
“Biology is the science of exceptions,” a colleague of mine recently noted. Now what if a disease-driver gene shows just a hint of differential expression, or a disease-causing allele is present at only a very low frequency? It will likely get buried in the noise. This experimental “chaos” also takes an enormous toll on researchers. It can wreck an experiment, lead them down a rabbit hole, require repeating an experiment, cause disparity in the literature, or destroy a shot at publication or a grant. Often, it means an outlier might accidentally get tossed out, even when it could have led to a researcher’s most important discovery. So rather than accepting experimental chaos, biologists must continually battle it in their quest for meaning. And yet no handy users guide can tell a biologist how to do this. Finding something novel and important within an extremely complex system really does involve a good deal of art.
Sometimes “Zen Biology” may be the only way that meaningful biological insights can be made with any confidence. Practicing Zen Biology—the art of quieting biological noise— allows important, even subtle, changes to rise above the fray and be more easily noticed. While special tools and methods can help, how these are used together to uncover something novel does require an artist’s touch. Some factors can be controlled by statistically sound experimental design and lab best practices. Comparing data generated using independent methodologies can also help. With the proliferation of ‘omics technologies, the possibilities for cross-platform validation are extensive.
IPA’s multi-omics approach can help researchers validate and corroborate findings and thereby have more confidence in even tiny experimental observations surfacing in large-scale experiments. With IPA, researchers can compare results from more than one experiment, including datasets generated on different ‘omics platforms. For example, researchers can compare gene expression microarray data with real-time PCR data. They can also compare gene expression results with protein expression results, or results from two instrument platforms to make sure that differences are due to biology instead of technology. In addition, researchers can cross-validate their datasets with public databases, or simply compare public data from two different papers. These are all masterful tools for the art of complex biology.
Researchers can also interact with their results to filter out unimportant information. For example, they can remove uninteresting molecules from complex molecular networks to make them more tractable. They can also drill right down to original references to figure out whether or not to remove information from the results if they don’t trust it or feel it is irrelevant. Sets of filters in IPA also help researchers remove other types of irrelevant information that may cloud the interpretation of their experiment. IPA provides deep biological context, extensive comparison tools, powerful filters, and the ability to exclude findings as a researcher sees fit. Together this helps them narrow in on what is important so they can best interpret their experiments. While IPA is not a panacea for removing experimental noise and filtering out irrelevant data, it offers a host of tools that can help. Practicing Zen biology, researchers increase their chance of making those fine observations that might otherwise be lost in the complexity and noise of biology, but which can be crucial to important insights and discovery.
Go to the Ingenuity website