The theory of evolution is useless, without practical application.
- Evolutionary theory is the framework tying together all of biology. It
explains similarities and differences between organisms, fossils,
biogeography, drug resistance, extreme features such as the peacock's
tail, relative virulence of parasites, and much more besides.
Without the theory of evolution, it would
still be possible to
know much about biology, but not to understand it.
This explanatory framework is useful in a practical sense. First, a
unified theory is easier to learn, because the facts connect together
rather than being so many isolated bits of trivia. Second, having a
theory makes it possible to see gaps in the theory, suggesting
productive areas for new research.
- Evolutionary theory has been put to practical use in several areas
(Futuyma 1995; Bull and Wichman 2001). For example:
- Bioinformatics, a multi-billion-dollar industry, consists largely of
the comparison of genetic sequences. Descent with modification is
one of its most basic assumptions.
- Diseases and pests evolve resistance to the drugs and pesticides we
use against them. Evolutionary theory is used in the field of
resistance management in both medicine and agriculture (Bull and
- Evolutionary theory is used to manage fisheries for greater yields
(Conover and Munch 2002).
- Artificial selection has been used since prehistory, but it has
become much more efficient with the addition of quantitative trait
- Knowledge of the evolution of parasite virulence in human
populations can help guide public health policy (Galvani 2003).
- Sex allocation theory, based on evolution theory, was used to
predict conditions under which the highly endangered kakapo bird
would produce more female offspring, which retrieved it from the
brink of extinction (Sutherland 2002).
Evolutionary theory is being applied to and has potential applications
in may other areas, from evaluating the threats of genetically modified
crops to human psychology. Additional applications are sure to come.
- Phylogenetic analysis, which uses the evolutionary principle of common
descent, has proven its usefulness:
- Tracing genes of known function and comparing how they are related
to unknown genes helps one to predict unknown gene function, which
is foundational for drug discovery (Branca 2002; Eisen and Wu 2002;
- Phylogenetic analysis is a standard part of epidemiology, since it
allows the identification of disease reservoirs and sometimes the
tracking of step-by-step transmission of disease. For example,
phylogenetic analysis confirmed that a Florida dentist was infecting
his patients with HIV, that HIV-1 and HIV-2 were transmitted to
humans from chimpanzees and mangabey monkeys in the twentieth
century, and, when polio was being eradicated from the Americas,
that new cases were not coming from hidden reservoirs (Bull and
Wichman 2001). It was used in 2002 to help convict a man of
intentionally infecting someone with HIV (Vogel 1998). The same
principle can be used to trace the source of bioweapons (Cummings
and Relman 2002).
- Phylogenetic analysis to track the diversity of a pathogen can be
used to select an appropriate vaccine for a particular region
(Gaschen et al. 2002).
- Ribotyping is a technique for identifying an organism or at least
finding its closest known relative by mapping its ribosomal RNA onto
the tree of life. It can be used even when the organisms cannot be
cultured or recognized by other methods. Ribotyping and other
genotyping methods have been used to find previously unknown
infectious agents of human disease (Bull and Wichman 2001; Relman
- Phylogenetic analysis helps in determining protein folds, since
proteins diverging from a common ancestor tend to conserve their
folds (Benner 2001).
- Directed evolution allows the "breeding" of molecules or molecular
pathways to create or enhance products, including:
Directed evolution can also be used to study the folding and function
of natural enzymes (Taylor et al. 2001).
- enzymes (Arnold 2001)
- pigments (Arnold 2001)
- bacterial strains to decompose hazardous materials.
- The evolutionary principles of natural selection, variation, and
recombination are the basis for genetic algorithms, an engineering
technique that has many practical applications, including aerospace
engineering, architecture, astrophysics, data mining, drug discovery
and design, electrical engineering, finance, geophysics, materials
engineering, military strategy, pattern recognition, robotics,
scheduling, and systems engineering (Marczyk 2004).
- Tools developed for evolutionary science have been put to other uses.
- Many statistical techniques, including analysis of variance and
linear regression, were developed by evolutionary biologists,
especially Ronald Fisher and Karl Pearson. These statistical
techniques have much wider application today.
- The same techniques of phylogenetic analysis developed for biology
can also trace the history of multiple copies of a manuscript
(Barbrook et al. 1998; Howe et al. 2001) and the history of
languages (Dunn et al. 2005).
- Good science need not have any application beyond satisfying curiosity.
Much of astronomy, geology, paleontology, natural history, and other
sciences have no practical application. For many people, knowledge is
a worthy end in itself.
- Science with little or no application now may find application in the
future, especially as the field matures and our knowledge of it becomes
more complete. Practical applications are often built upon ideas that
did not look applicable originally. Furthermore, advances in one area
of science can help illuminate other areas. Evolution provides a
framework for biology, a framework which can support other useful
- Anti-evolutionary ideas have been around for millennia and have not yet
contributed anything with any practical application.
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for biocatalyst design. Nature 409: 253-257.
- Barbrook, Adrian C., Christopher J. Howe, Norman Blake, and Peter
Robinson, 1998. The phylogeny of The Canterbury Tales.
Nature 394: 839.
- Benner, Steven A. 2001. Natural progression. Nature 409: 459.
- Branca, Malorye. 2002. Sorting the microbes from the trees. Bio-IT
Bulletin, Apr. 07.
- Bull, J. J. and H. A. Wichman. 2001. Applied evolution. Annual
Review of Ecology and Systematics 32: 183-217.
- Cherry, J. R., and A. L. Fidantsef. 2003. Directed evolution of
industrial enzymes: an update. Current Opinion in Biotechnology 14:
- Conover, D. O. and S. B. Munch. 2002. Sustaining fisheries yields over
evolutionary time scales. Science 297: 94-96. See also pp. 31-32.
- Cummings, C. A. and D. A. Relman. 2002. Microbial forensics--
"cross-examining pathogens". Science 296: 1976-1979.
- Dunn, M., A. Terrill, G. Reesink, R. A. Foley and S. C. Levinson.
2005. Structural phylogenetics and the reconstruction of ancient
language history. Science 309: 2072-2075. See also: Gray, Russell.
2005. Pushing the time barrier in the quest for language roots.
Science 309: 2007-2008.
- Eisen, J. and M. Wu. 2002. Phylogenetic analysis and gene functional
predictions: Phylogenomics in action. Theoretical Population
- Futuyma, D. J. 1995. The uses of evolutionary biology. Science 267:
- Galvani, Alison P. 2003. Epidemiology meets evolutionary ecology.
Trends in Ecology and Evolution 18(3): 132-139.
- Gaschen, B. et al.. 2002. Diversity considerations in HIV-1 vaccine
selection. Science 296: 2354-2360.
- Howe, Christopher J. et al. 2001. Manuscript evolution. Trends in
Genetics 17: 147-152.
- Marczyk, Adam. 2004. Genetic algorithms and evolutionary computation.
- Nesse, Randolph M. and George C. Williams. 1994. Why We Get Sick.
New York: Times Books.
- Relman, David A. 1999. The search for unrecognized pathogens.
Science 284: 1308-1310.
- Searls, D., 2003. Pharmacophylogenomics: Genes, evolution and drug
targets. Nature Reviews Drug Discovery 2: 613-623.
- Sutherland, William J., 2002. Science, sex and the kakapo. Nature
- Taylor, Sean V., Peter Kast, and Donald Hilvert. 2001. Investigating
and engineering enzymes by genetic selection. Angewandte Chemie
International Edition 40: 3310-3335.
- Vogel, Gretchen. 1998. HIV strain analysis debuts in murder trial.
Science 282: 851-852.
created 2005-3-26, modified 2005-10-4