R help - Feb 2013 - Putting priors on which factors to sample more from, in random forests

I was wondering if anyone knows of a random forest implementation (or way
of tweaking the standard randomForest library) that allows one to specify
 some sort of variable importance a* *priori.

For example, say that I know that some variables/factors could be more
informative than others for classification. I would like to help RF look at
these variables more than others during splitting.

As far as I know, the standard implementations choose factors fully
randomly (i.e. uniform distribution) at each node.

Is there a way to influence this selection?

Thanks!

James

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