What we can learn from bioinformatics
July 10th, 2005 by Tom Johnson

A recent profile of mathematician-turned-geneticist Philip Green is a good-read introduction to bio-informatics, and bio-informatics just might produce some methodologies journalists can use to validate public records databases.

The article, “Bioinformatics,” is in the quarterly published by the Howard Hughes Medical Institute.  Some highlights:

* Using a detailed computational model, [researchers] found
that some kinds of [genetic] mutations occur at constant rates, like the
ticking of a clock, which makes them useful for dating evolutionary events.
Other kinds of mutations occur at varying rates de-pending on the generation
times of the organism. This information in turn makes it much easier to identify
parts of the genome that exhibit different patterns of change over time,
indicating that the DNA in those regions is subject to selection and therefore
playing a functional role. The idea, says Green, is to separate the noise of
meaningless changes in DNA so that the signals of consequential changes emerge
clearly from the background
Journalists could look at which elements are changed in a data base and
how often as a clue for the importance of the data base and the
relative importance of various elements.

* “The main issue [in biology and genomics] is how
quantitative we’re going to be able to get,” [Green] says. “Most people will
accept the idea that we will know qualitatively how things are interacting with
each other. But what you really want is a quantitative result, so that you can
change the levels of one component and predict how it will affect the system.”

*  “Back then, [says a colleague of Green’s] we wondered if
there was a need for mathematics in biology. In the mid-1980s, there weren’t a
lot of data. Biology was about analyzing the notes in your lab book.

the last 20 years, biology has become dominated by huge data sets. Now it’s an
exception rather than the rule to publish a paper that does not draw on large
databases of biological information. Mathematical analysis has become a
funda-mental part of biological research. It has turned out to be of equal
importance to experimentation.”

Take a look at the article.  It suggests some parallels of investigation for analytic journalism.

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