**MixtureMoDe** is a tool for learning a mixture of several iPMMs of given maximal order from a set of pre-aligned DNA sequences of same length.
The learning procedure is similar to that of **DeNovoMoDe**, but the target function is now the sum of the BIC scores of the individual components.

If the content of the "Input data" file starts with '>', it is interpreted as FastA file. Otherwise it is interpreted as plain text, where every line contains a single sequence. 
The input expects upper- and lower case letters of the standard DNA alphabet {A,C,G,T}. If other symbols from the IUPAC code (such as N) are encountered, they are replaced by a random sample from the distribution of {A,C,G,T} in the data set. 
All input sequences are expected to have the same length.

If the "Number of mixture components" is set to 1, the tool does essentially the same as **SimpleMoDe**.

The specified "Component order" applies to every mixture component. If different components are supposed to have a different maximal order, use **FlexibleMoDe** instead.

The default values for "Initial iterations", "Additional iterations" and "Restarts" are relatively small values which are, however, in many cases sufficient for finding a motif (if present in the data).
Increasing the number of restarts is typically the most promising option to increase the probability of finding a hard-to-spot pattern.
 
If no "Name" is specified, it is set by default to "Mixture(*a* , *b*)", where *a* is "Number of mixture components", and *b* is "Component order".

The tool returns
(i) a logfile containing the scores of all iteration steps in the stochastic search for evaluating whether the parameter values for "Initial iterations", "Additional iterations" and "Restarts" have been sufficient or not.
(ii) all learned components models, with each component containing exactly the same output as returned by **SimpleMoDe**.  
