Answers.Body: <p><em>Answer from @llrs, converted from comment:</em></p>
  <p>You could try to download RNAseq data from this bacteria and see if some of the RNA align to your sequence. You could try to blast your gene and look for the sequences that have low identity similarity (or classify them by type and then look what is each hit).</p>
  
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Answers.Text: Good idea but from my experience, normal alignment is not optimized for sRNA. Tools like targetRNA2 are optimized for sRNA alignment such as imperfect pairing and energy ..etc.
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Answers.CreationDate: 2021-05-12T02:20:47.020Z
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Body: <p>I am working on Vibrio parahaemolyticus. I have a gene that it is possible might be regulated by small non-coding RNAs. How can I predict possible sRNAs that target the transcript of this gene. Most software offers the opposite of what I want, i.e., they predict targets for small RNAs!</p>
  <p>I'm trying to predict bacterial small non-coding RNA in general (Support Vector Machine) but I got more than 8 thousand sequences within intergenic regions alone. Is there a code for aligning these sequences to my transcript?</p>
  
Tags: <bacteria>
Title: how do I predict bacterial small non-coding RNA for a specific mRNA?
ThreadText: # how do I predict bacterial small non-coding RNA for a specific mRNA?
  
  (Asked by: username_0 on 2017-12-14)
  
  I am working on Vibrio parahaemolyticus. I have a gene that it is possible might be regulated by small non-coding RNAs. How can I predict possible sRNAs that target the transcript of this gene. Most software offers the opposite of what I want, i.e., they predict targets for small RNAs!
  
  I'm trying to predict bacterial small non-coding RNA in general (Support Vector Machine) but I got more than 8 thousand sequences within intergenic regions alone. Is there a code for aligning these sequences to my transcript?
  
  **Tags:** bacteria
  
  
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  ## 1 answers
  
  ### Answer by username_1 on 2021-05-12. Score: 2
  
  *Answer from @llrs, converted from comment:*
  
  You could try to download RNAseq data from this bacteria and see if some of the RNA align to your sequence. You could try to blast your gene and look for the sequences that have low identity similarity (or classify them by type and then look what is each hit).
  
  > **Comments:**
  > **username_0**: Good idea but from my experience, normal alignment is not optimized for sRNA. Tools like targetRNA2 are optimized for sRNA alignment such as imperfect pairing and energy ..etc.  
  
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