Alignment Implementation (AI)

I was working through an example at Stanford on the use of Python to implement genetic sequence alignment using "memoization" to speed up a recursive function and I remembered what I had invented. I won't spoil anybody's homework and publish my final code, as it defeats the purpose of learning. I could have taken the example, done the task with memoization and been done, but there in the corner is this idea from implementing the `einstein` puzzle that there is a way to do this better, faster and with more meaningful results that have a degree of certainty. This is where the synergy of continual analysis really shines as I extended a technique I had used before and the general case is what is important as it applies to many things including image compression, recognition and cognitive process.

I took bioinformatics a couple years ago and I was wildly disappointed for several reasons. One was the fact that the professor failed to show and left the course to a TA who had trouble speaking, writing code, understanding the concepts and it was obvious from their research interests and funding that they used the information gained to implement sequences for proprietary patenting of gene sequences. In the process of that course I realized how to do alignments better than the method which was taught as I am a programmer and inventor. I never shared that information as I know what would happen, it would be patented and used to further the hiding of methods so that everyone suffers so a few can be rich.

\sum_{\substack{
   0<i<m \\
   0<j<n
  }} 
 P(i,j)

I just can't get over this as I see no solution to the problem. Some people will grab an idea that flows naturally from the new information that exists and then poison the well that everybody drinks from. It is a behavior that is so foreign to me. They seek to be large by shrinking others. It reminds me of the "Time Lord Master's" molecular compressor and how he would leave these little shrunken people in his wake in the old Tom Baker Dr Who episodes.

 for i in range(0, len(strand2)):
  out.write(strand2[i]+" "+str(i))
 out.write("\n")