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# 1. Who needs random numbers?

### To shuffle sequences

To test the significance of a putative sequence homology. Keep the
amino acid (or nucleotide) content constant, but swap around the
residues randomly, and compute similarity again.

### To select test data from a large DB

SWISS-PROT currently contains about 80.000 protein sequences. Select
1000 of these as a simple quick test set, before doing complete
analysis. It is not good enough to use the first 1000 in the Swissprot
file, since the entries have probably not been added in random order
to the file.

### To do a simulation starting from a random configuration

Molecular dynamics: random initial velocities (Maxwell distribution
for a given temperature), and maybe somewhat randomized initial positions.

### Simulated annealing

An optimization algorithm to find the minimum (or maximum) of a
complicated function. Use random numbers to explore many combinations
of variable (parameter) values, and to decide which "bad" moves to
accept during the search.

### Genetic algorithms

An optimization algorithm: Encode a proposed solution to a problem
as a gene, allow mutations and recombinations randomly, perform
evolution over a set of different solutions to find the minimum (or
maximum) of the function.

Copyright © 2000
Per Kraulis
$Date: 2000/12/12 15:49:04 $