Despite huge progress in gene sequencing, we still don’t fully understand how biology works

[B]iology has become a victim of its success. Today we can sequence genomes much faster than we can understand them. We can measure electrochemical signals from neurons much more efficiently than we can understand their function. We can model the spread of populations of viruses and populations much more rapidly than we can understand their origins or interactions. Moore’s Law may apply to computer chips and sequencing speeds, but it does not apply to human comprehension.

[C]ompared to the speed with which we can now gather and process biological data, the theoretical framework which goes into understanding data as well as the understanding which come out from the other end are severely impoverished. What is more serious is a misguided belief that data equals understanding. The philosopher of technology Evgeny Morozow calls this belief “technological solutionism”, the urge to use a certain technology to address a problem simply because you can.

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Consider a field like cancer where gene sequencing has come to play a dominant role…The problem is that if you sequence a typical cell from, say, a lung cancer patient, you will find literally hundreds of genes which are mutated…It is even more difficult to know which genes to target if we want to keep the cancer from growing. For doing this it is important to have a better theory for understanding exactly what genes would be mutated in a cancer cell and why….

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The failure of reductionist technology to understand emergent biology is why technology will not save the biological sciences…[W]hat we need most is an integrated view of biological organisms that moves away from a strict focus on looking at these organisms as collections of particles, fields and molecules.

The GLP aggregated and excerpted this blog/article to reflect the diversity of news, opinion, and analysis. Read full, original post: Why Technology Won’t Save Biology

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