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Welcome to Adaptive Complexity, where I write about genomics, systems biology, evolution, and the connection between science and literature, government, and society.

I'm a biochemist

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In a column in Nature, Colin Macilwain suggests that bad science reporting is due in part to its relatively low cost:

Propped up by the specious authority of their jargon and, most of all, by their cheapness to report — which stands in stark contrast to proper investigations of issues such as public corruption, corporate maleficence or industrial health and safety — essentially silly stories about science continue to fill newspapers and news broadcasts.

Bad science stories basically write themselves, because the research has already been written up, published, and packaged into a university press release.

The result is
When asked to justify the research I do, I always struggle a little to explain my dissatisfaction with the traditional descriptive, non-quantitative explanations of molecular biological systems. As a glance at a classic molecular cell biology textbook will easily demonstrate, molecular biologists have been tremendously successful with verbal or semi-quantitative explanations of what goes on inside the cell. And in any case, the complexity of the cell is extremely daunting for the would-be theoretical biologist.

The question of whether record snows in the Northeast US says something about climate change is a scientific question. The NY Times shows us how not to report on a scientific issue:

Skeptics of global warming are using the record-setting snows to mock those who warn of dangerous human-driven climate change — this looks more like global cooling, they taunt.

Most climate scientists respond that the ferocious storms are consistent with forecasts that a heating planet will produce more frequent and more intense weather events.
Walter Fontana, a Professor of Systems Biology at Harvard, reflects on models in biology:

Models will play a central role in the representation, storage, manipulation, and transmission of knowledge in systems biology. Models that are capable of fulfilling all these purposes will likely differ from the familiar styles deployed with great success in the physical sciences. "Classical" flavors of models may be viewed on a continuum between two major types:

Models that are of heuristic nature.
I am convinced that we can discover, by means of purely mathematical constructions, those concepts and those lawful connections between them which furnish the key to the understanding of natural phenomena. Experience may suggest the appropriate mathematical concepts, but they most certainly cannot be deduced from it. Experience remains, of course, the sole criterion of physical utility of a mathematical construction. But the creative principle resides in mathematics. In a certain sense therefore, I hold it true that pure thought can grasp reality, as the ancients dreamed.

- Albert Einstein, quote in Einstein, Jeremy Bernstein, p. 127 (Penguin, 1978)

I saw that mathematics was split up into numerous specialties, each of which could easily absorb the short lifetime granted to us. Consequently, I saw myself in the position of Buridan's ass which was unable to decide upon any specific bundle of hay. This was obviously due to the fact that my intuition was not strong enough in the field of mathematics in order to differentiate clearly the fundamentally important from the rest of the more or less dispensable erudition... In [physics] however, I soon learned to scent out that which was able to lead to fundamentals and to turn aside from everything else, from the multitude of things which clutter up the mind and divert it from the essential.