Scientific Sense Podcast

Sunday, February 24, 2013

Algorithmic discovery

Recent research (1) from USC that demonstrates how predictive algorithms can propel discovery in many areas including medicine and astronomy is further indication that applied mathematics is coming of age. Misguided attempts at rules based Artificial Intelligence kept a lid on more productive empiricism – something engineers and economists have known for many decades. Life sciences has been notoriously backward in the application of mathematics in predictions and decisions. Many have argued that biological systems represent complex interacting uncertainties and hence are not amenable to modeling. Nothing could be further from the truth.

Determinism and normality statistics have played havoc with many fields, including life sciences, for decades. Specialists in this industry followed standardized processes of discovery with rigid and prescriptive expectations of outcomes. The constant and nearly predictable failures have not forced significant changes, yet. The long cycles of research and development have allowed the perpetuation of the status-quo. The USC approach of taking well known mathematical principles and applying them differently with an eye toward practical applications is refreshing. More research of this ilk is needed if the industry is to pull out of the rut it is currently in.

Predictive and decision analytics – supported by established mathematics can wake up the slumbering life sciences industry. Tools have been available for over a decade – but not many have been willing to take the plunge.

(1) Taking the gamble out of DNA sequencing, Published: Sunday, February 24, 2013 - 15:32 in Biology & Nature, e!Science News.

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