A simple tutorial SPatt (work in progress)

Toy example with a binary alphabet

Ribosome binding sites in upstream regions of co-regulated genes

Prosite signature in a set of proteins

Using Scilab to perform computations

Let us consider the toy-example pattern aba on the binary alphabet. We use a order model with parameter ab_m0.markov 

spatt -a "ab" -p "aba" -m 0 -M ab_m0.markov

Processing this command, SPatt produces the Scilab source file pmc.sci which contains the optimal Markov chain embedding of the problem. We can now load this file into Scilab using: 

scilab -nw -f pmc.sci

The following commands are then typed into the Scilab interface:

-->x=poly(0,'x'); M=full(P)+x*full(Q)
 M  =
 
    0.6     0.4     0       0      
                                   
    0       0.4     0.6     0      
                                   
    0.6     0       0       0.4x   
                                   
    0       0.4     0.6     0      
 
-->aux=M^20; res=aux(starts,final)
 res  =
 
                           2            3            4            5            6            7            
    0.0177338x + 0.0295794x + 0.0256004x + 0.0146999x + 0.0060711x + 0.0018461x + 0.0004048x             
                        8             9                                                                  
            + 0.0000601x + 0.0000044x

res now contains the probability generating function of the random count of aba in a binary random (generated according to ab_m0.markov) sequence of length 20. For example, this random count is 4 with probability coeff(res,4)=0.0146999, 7 with probability coeff(res,7)=0.0004048.

Using graphviz to visualize NFA and DFA

spatt -a "ab" -p "aba" -m 0 --nfa nfa.dot
dot nfa.dot -Gbgcolor="transparent" -Tpng > nfa.png

spatt -a "ab" -p "aba" -m 0 --dfa dfa.dot 
dot dfa.dot -Gbgcolor="transparent" -Tpng > dfa.png

spatt -a "ab" -p "aba" -m 0 -r --dfa dfa_renewal.dot 
dot dfa.dot -Gbgcolor="transparent" -Tpng > dfa_renewal.png

Last edited 01/13/2012