text: user6815: I am working with an in silico model to measure the distances between drugs targets and disease proteins of a disease. I would want to compare these distances with the distances of random networks but I don't know which is the best way to do the comparison. For instance, if I have 300 drug targets and 500 disease proteins mapped in the interactome and I want to measure the distance between them and then compare to random networks with the same features. 
  How do I generate these random networks? Choosing the same number of drug targets (300) and disease genes (500) randomly in my referral network? Choosing the same number of nodes (300 and 500) and the same number of links?
  I'd appreciate your help!
  
  user2108: If your goal is only to account for degree distribution (i.e. Matteo Ferla's comment), a simulation approach you could use is:
  
  measure the degree (number of links) of each protein in your PPI
  find a large set of proteins that are equal or similar in degree to each of your proteins of interest (you may have to use a range of degrees to get a large enough set for comparison, ideally >=1000). We'll call these "comparable proteins" for each of your proteins of interest.
  For each protein of interest, make all of your measurements also for its set of comparable proteins
  Compare your measurement (shortest distance?) for the protein of interest to that for its comparable proteins. You could compute Z-scores from the parameters of the comparable protein distribution, or just empirical Monte Carlo p-values from where it falls in the distribution.
  
  This will give you at least a heuristic null distribution for each protein. It should be relatively easy to code up in whatever your favorite language is.
  Hope that helps-
  
original_text: 6815: <p>I am working with an in silico model to measure the distances between drugs targets and disease proteins of a disease. I would want to compare these distances with the distances of random networks but I don't know which is the best way to do the comparison. For instance, if I have 300 drug targets and 500 disease proteins mapped in the interactome and I want to measure the distance between them and then compare to random networks with the same features. </p>
  
  <p>How do I generate these random networks? Choosing the same number of drug targets (300) and disease genes (500) randomly in my referral network? Choosing the same number of nodes (300 and 500) and the same number of links?</p>
  
  <p>I'd appreciate your help!</p>
   2108: <p>If your goal is only to account for degree distribution (i.e. Matteo Ferla's comment), a simulation approach you could use is:</p>
  
  <ol>
  <li>measure the degree (number of links) of each protein in your PPI</li>
  <li>find a large set of proteins that are equal or similar in degree to each of your proteins of interest (you may have to use a range of degrees to get a large enough set for comparison, ideally >=1000). We'll call these "comparable proteins" for each of your proteins of interest.</li>
  <li>For each protein of interest, make all of your measurements also for its set of comparable proteins</li>
  <li>Compare your measurement (shortest distance?) for the protein of interest to that for its comparable proteins. You could compute Z-scores from the parameters of the comparable protein distribution, or just empirical Monte Carlo p-values from where it falls in the distribution.</li>
  </ol>
  
  <p>This will give you at least a heuristic null distribution for each protein. It should be relatively easy to code up in whatever your favorite language is.</p>
  
  <p>Hope that helps-</p>
  