Answers.Body: <p>A contact map predictor will usually output the probability of a contact for every residue pair in a protein, often ommitting very close pairs (e.g. less than 6 residue separation).</p>
  <p>To calculate the L/n score, rank the predicted contacts descending by probability and look at the first L/n contacts. The fraction of these that are actually contacts in the native structure is the L/n contact precision score.</p>
  <p>Often, you would filter the list to look at only contacts of a certain sequence separation, e.g. long range contacts between residues of &gt;23 separation (definitions vary between papers). If you have a good predictor this score is high for L/10 and falls as you go to L/1, which is expected as proteins don't usually have that many long range contacts to find.</p>
  
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Answers.CreationDate: 2020-11-23T11:33:33.167Z
Answers.LastActivityDate: 2020-11-23T11:33:33.167Z
Answers.UserDisplayName: jgreener
Body: <p>I am currently investigating how to predict protein structure and contact map predictions. There, I see things like top L/5 and top L/2 scores as a way to evaluate the contact map. What formulas do you use to evaluate these? Also, what is a meaningful evaluation method?</p>
  
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Comments.CreationDate: 2020-11-18T12:25:45.827Z
Comments.Text: L is protein length so you divide that by two or five! 
  Sorry, I could not resist that. 
  
  Anyway, there are a few metrics to rank the contact, so depends on the paper. The original EVFold paper is a good place to start https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0028766 even if you are interested in the AlphaFold stuff.
Comments.UserDisplayName: Matteo Ferla
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Comments.CreationDate: 2020-11-21T10:22:44.703Z
Comments.Text: @MatteoFerla Thanks for answering my question, I understand that L/5 is the length of the protein sequence divided by 5. Does that mean that Top L/5 represents the best prediction for all patches of L/5?
Comments.UserDisplayName: musako
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Comments.CreationDate: 2020-11-21T10:23:04.027Z
Comments.Text: @MatteoFerla Also, what does Short, Medium and Long mean in the accuracy column of the forecast? This is the paper: https://academic.oup.com/bioinformatics/article/35/22/4647/5487385
Comments.UserDisplayName: musako
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Comments.CreationDate: 2020-11-21T12:10:27.080Z
Comments.Text: That sounds like the range cutoffs —A range contact is not the distance of atoms, but the distance in residues in the linear sequence —in that paper <12 is short, >23 long. Honestly, I've not read that paper —the Zhang group have made I-Tasser so are a good group. But this is paper dependent, in the [AlphaFold one](https://www.nature.com/articles/s41586-019-1923-7) they divide the range in 64 bins, but still refer to short-range/medium-range/long-range.
Comments.UserDisplayName: Matteo Ferla
Tags: <proteins><protein-structure>
Title: How do you calculate the top L/5 score?
ThreadText: # How do you calculate the top L/5 score?
  
  (Asked by: username_0 on 2020-11-18)
  
  I am currently investigating how to predict protein structure and contact map predictions. There, I see things like top L/5 and top L/2 scores as a way to evaluate the contact map. What formulas do you use to evaluate these? Also, what is a meaningful evaluation method?
  
  **Tags:** proteins, protein-structure
  
  > **Comments:**
  > **username_1**: L is protein length so you divide that by two or five!  Sorry, I could not resist that.   Anyway, there are a few metrics to rank the contact, so depends on the paper. The original EVFold paper is a good place to start https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0028766 even if you are interested in the AlphaFold stuff.  
  > **username_0**: @username_1 Thanks for answering my question, I understand that L/5 is the length of the protein sequence divided by 5. Does that mean that Top L/5 represents the best prediction for all patches of L/5?  
  > **username_0**: @username_1 Also, what does Short, Medium and Long mean in the accuracy column of the forecast? This is the paper: https://academic.oup.com/bioinformatics/article/35/22/4647/5487385  
  > **username_1**: That sounds like the range cutoffs —A range contact is not the distance of atoms, but the distance in residues in the linear sequence —in that paper <12 is short, >23 long. Honestly, I've not read that paper —the Zhang group have made I-Tasser so are a good group. But this is paper dependent, in the [AlphaFold one](https://www.nature.com/articles/s41586-019-1923-7) they divide the range in 64 bins, but still refer to short-range/medium-range/long-range.  
  
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  ## 1 answers
  
  ### Answer by username_2 on 2020-11-23. Score: 2
  
  A contact map predictor will usually output the probability of a contact for every residue pair in a protein, often ommitting very close pairs (e.g. less than 6 residue separation).
  
  To calculate the L/n score, rank the predicted contacts descending by probability and look at the first L/n contacts. The fraction of these that are actually contacts in the native structure is the L/n contact precision score.
  
  Often, you would filter the list to look at only contacts of a certain sequence separation, e.g. long range contacts between residues of >23 separation (definitions vary between papers). If you have a good predictor this score is high for L/10 and falls as you go to L/1, which is expected as proteins don't usually have that many long range contacts to find.
  
  
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