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I've might have created a new algorithm for finding patterns in DNA. The technique has not been used before, and it managed to find a 33-mer with corresponding complement that exists both in E. Coli and in Salmonella. I think it's pretty neat but I don't know how to evaluate the results. In addition, I've developed this algorithm after a bioinformatics course where only the DNA sequences of E. Coli and Salmonella were provided, so I would like to test it on other sequences and have it evaluated by people who know what they are doing.

How would one get in contact with the right people for evaluating amateur bioinformatics result?

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  • $\begingroup$ If you took a course, start by chatting with the Professor/Instructor who taught it. They will either be able to chat about things with you or put you in touch with someone locally. $\endgroup$
    – Devon Ryan
    May 10 '20 at 19:17
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    $\begingroup$ It was one of those online Coursera courses. There are no real options to get in contact with the professor who created it. $\endgroup$ May 10 '20 at 19:20
  • $\begingroup$ What is the benefit of your approach? Is it faster than the myriad existing algorithms for pattern finding? Does it have better pattern-definition syntax? What kind of "patterns" are we talking about? What is this 33,er supposed to be? What makes it special? $\endgroup$
    – terdon
    May 11 '20 at 11:52
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    $\begingroup$ Wait, so you mean you just found some random sequence of 33nts whose only distinguishing feature is that you find it in many organisms? That doesn't seem strange, 33 is tiny, so you'll find loads of sequences that can be found all over the place at that length. Especially if you're not limiting to exact hits. Try generating some random 33nt sequences and searching for those, I bet many or even most of them will be found in hundreds of species. $\endgroup$
    – terdon
    May 11 '20 at 13:42
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    $\begingroup$ @dariober ah, but this isn't random at all. It's a superpermutation which I suspect will mean the sequence is relatively repetitive, making it far more likely to appear randomly in blast results. I admit I'm just speaking off the top of my head though (hence the comment instead of an answer). But yes, my assumption would be that finding a 33nt sequence present (as an imperfect match, mind you, as the OP described) in multiple genomes is not surprising per se. Finding exact matches in hundreds of genomes would be more intriguing, yes. $\endgroup$
    – terdon
    May 12 '20 at 17:08
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You need to understand the biological significance of the 33-mer locus.

  1. I'd blast your 33-mer on NCBI and see what the biological significane is of the locus. If might be a transposon/ promoter region.
  2. Look at the translation of the protein and if its part of a protein the location within the protein structure.
  3. Blast the entire locus including 5' and 3' regions of the 33-mer target
  4. Carefully assess the results for chance, e.g. conserved protein and the synonymous mutations just happened to drop out (Poison distribution).

Once you gain a greater understanding, it is likely to have been identified before and what you might contribute is a different method to obtain a known result.

In summary, you need the next level part of the course about translating a genetic correlation into a biological result/ mechanism. This isn't research grade work at present in my opinion.

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    $\begingroup$ Thank you for your answer, that NCBI is a really nice resource. $\endgroup$ May 10 '20 at 19:50

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