The purpose of our program is to provide the optimal set of mixing matrix and starting sequences in order to maximize
the yield of specific target motifs in *in vitro* selection. You may choose the target RNA structure for
*in vitro* selection. Our program will then give you the optimal set of mixing matrix and starting sequences.
See the tutorial section for background details.

As detailed above, the RNA pool designer computes the optimal designed pool parameters corresponding to the user input.
For example, if the user requests to use two mixing matrices with the conservation of C and G and all starting sequences to achieve 30% each
of 4_{1} and 4_{2} tree motifs as in target Pool T_{A},
the optimization specifies 78% of mixing matrix 13 with modified GTP aptamers (seq 5)
as starting sequence and 22% of mixing matrix 12 with the hammerhead ribozyme (seq 25).
This combination yields the desired structural distribution (subject to the correction of the 2D structure data).

Similarly, users can construct target Pool T_{B} to use three mixing matrices and all starting sequences to find 20% each of
5_{1}, 5_{2} and 5_{3} structures. The optimized output specifies 12% of mixing matrix 1 with
70S (seq 1) as starting sequence, 83% of MMT 12 with
tRNA (seq 2), and 5% of MMT 4 with
DsrA ncRNA (seq 21).

Users can further filter the output by selecting additional options to choose certain groups of starting sequences. In target Pool T_{C},
the user requests to use two mixing matrices to achieve 30% each of 5_{1} and 6_{1} similar to target Pool T_{A}.
However, the user is limiting the results by choosing starting sequences with 80-100 nucleotides. The optimized output shows
38.5% of mixing matrix 3 with tRNA (seq 2) and
61.5% of MMT 8 with let-7 ncRNA (seq 29).
Similarly, target Pool T_{D} further filters the optimized results by limiting the possible starting sequences to have
riboswitch function.

We apply our pool design approach for enhancing GTP-binding aptamers. Szostak’s group recently found that the GTP aptamer’s
binding affinity is correlated with structural complexity (e.g., number of stems) (Carothers et al., 2004;Carothers et al., 2006).
Specifically, a high affinity GTP aptamer (panel C in Ref. (Carothers et al., 2004)) is related to the
5_{2} tree structure. Interestingly, no GTP aptamer with a
4_{2} tree structure has been reported although it is structurally similar to the
5_{2} tree. Because the frequency of the 4_{2} motif is only 12% in random pool T_{F}, we propose designing a
GTP aptamer pool by enriching the pool with 5_{2} and 4_{2} motifs. Our target pool fractions (*T _{i}*) are
20% for 4