I see check summing works quite well. I had expected more false positives because different sequences can lead to the same checksum.

The algorithm is probably being flattered by my test data -- 16-bit random values. Although I am seeing a few false positives, it doesn't take long to verify them using a value-by-value comparison of a relatively small (currently 100, but that's flexible) number of actual values. With 100 x 16-bit numbers, there are huge number of possibilties (1e65536), so finding a repeat of those 100 is a pretty strong indicator of having found the start of the next repeat.

I realise with bio data, especially if its just ACGT, you'd need use a much longer tell-tale sequence to avoid many false positives.

With the rise and rise of 'Social' network sites: 'Computers are making people easier to use everyday'
Examine what is said, not who speaks -- Silence betokens consent -- Love the truth but pardon error.
"Science is about questioning the status quo. Questioning authority". The enemy of (IT) success is complexity.
In the absence of evidence, opinion is indistinguishable from prejudice. Suck that fhit

In reply to Re^4: Algorithm inspiration required. by BrowserUk
in thread Algorithm inspiration required. by BrowserUk

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