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22-Oct-2019 06:29

(A protein is made up of a sequence of basic building blocks called amino acids, which are joined together like the links in a chain.

Once all the amino acids are linked, the protein folds up into a complex three-dimensional shape based on which amino acids attract each other and which ones repel each other.

These promising candidates are kept and allowed to reproduce.

Multiple copies are made of them, but the copies are not perfect; random changes are introduced during the copying process.

These candidates may be solutions already known to work, with the aim of the GA being to improve them, but more often they are generated at random.

The GA then evaluates each candidate according to the fitness function.

This approach allows for greater precision and complexity than the comparatively restricted method of using binary numbers only and often "is intuitively closer to the problem space" (Fleming and Purshouse 2002, p. This technique was used, for example, in the work of Steffen Schulze-Kremer, who wrote a genetic algorithm to predict the three-dimensional structure of a protein based on the sequence of amino acids that go into it (Mitchell 1996, p. Schulze-Kremer's GA used real-valued numbers to represent the so-called "torsion angles" between the peptide bonds that connect amino acids.

But in the last few decades, the continuing advance of modern technology has brought about something new.

Evolution is now producing practical benefits in a very different field, and this time, the creationists cannot claim that their explanation fits the facts just as well.

In a pool of randomly generated candidates, of course, most will not work at all, and these will be deleted.

However, purely by chance, a few may hold promise - they may show activity, even if only weak and imperfect activity, toward solving the problem.

This approach allows for greater precision and complexity than the comparatively restricted method of using binary numbers only and often "is intuitively closer to the problem space" (Fleming and Purshouse 2002, p. This technique was used, for example, in the work of Steffen Schulze-Kremer, who wrote a genetic algorithm to predict the three-dimensional structure of a protein based on the sequence of amino acids that go into it (Mitchell 1996, p. Schulze-Kremer's GA used real-valued numbers to represent the so-called "torsion angles" between the peptide bonds that connect amino acids.

But in the last few decades, the continuing advance of modern technology has brought about something new.

Evolution is now producing practical benefits in a very different field, and this time, the creationists cannot claim that their explanation fits the facts just as well.

In a pool of randomly generated candidates, of course, most will not work at all, and these will be deleted.

However, purely by chance, a few may hold promise - they may show activity, even if only weak and imperfect activity, toward solving the problem.

The evolutionary postulate of common descent has aided the development of new medical drugs and techniques by giving researchers a good idea of which organisms they should experiment on to obtain results that are most likely to be relevant to humans.