Answers.Body: <p>The answer to your main doubt about &quot;annotation vs. enrichment&quot; is that you need both, but you already have one annotation.</p>
  <p>You can only perform a functional enrichment analysis after you have a functional annotation. In your question, you state that you have KEGG annotation for your targets. That is it, knowing which target &quot;belongs&quot; to each KEGG module is an example of functional annotation of your targets. Several tools can annotate genes, proteins, etc. Knowing which protein is related to each drug or disease is also a functional annotation.</p>
  <p>Now, knowing which targets are significantly important can be achieved by functional enrichment analysis.</p>
  <p>For the network, both information can be used together. For example, you could link all elements to their functional annotation and use the available enrichment score as a quantitative parameter of importance for calculating correlations.</p>
  
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2020-12-23T05:35:40.000Z
Answers.LastActivityDate: 2020-12-23T05:35:40.000Z
Answers.UserDisplayName: Lucio Queiroz
Body: <p>I am currently working on a network pharmacology project where I am supposed to find out the possible diseases our drug might have an effect on. I am not a bioinformatics student, so my knowledge in the subject matter is very limited. I have all the targets and I am supposed to get the pathways associated with the targets. I used <code>STRING</code> for the purpose.</p>
  <ul>
  <li>I got both <code>KEGG</code> functional annotation and enrichment for my list of targets.</li>
  <li>I have to build a two-mode network</li>
  </ul>
  <p><strong>Question</strong> I am not very clear about</p>
  <ul>
  <li>the difference between enrichment and functional annotation and</li>
  <li>which data should be used for the next step.</li>
  </ul>
  
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2020-11-22T09:44:17.533Z
Comments.Text: If you can add more detail that might help, such as the pathway(s) your STRING analysis indicates. Your question appears vague for the decision you have and it is not clear why you don't use both for two different network analyses
Comments.UserDisplayName: M__
Tags: <proteins><networks><go-enrichment><functional-annotation><kegg>
Title: Functional Annotation vs Functional Enrichment--which one should I use for Network Analysis?
ThreadText: # Functional Annotation vs Functional Enrichment--which one should I use for Network Analysis?
  
  (Asked by: username_0 on 2020-11-22)
  
  I am currently working on a network pharmacology project where I am supposed to find out the possible diseases our drug might have an effect on. I am not a bioinformatics student, so my knowledge in the subject matter is very limited. I have all the targets and I am supposed to get the pathways associated with the targets. I used `STRING` for the purpose.
  
  * I got both `KEGG` functional annotation and enrichment for my list of targets.
  * I have to build a two-mode network
  
  **Question** I am not very clear about
  
  * the difference between enrichment and functional annotation and
  * which data should be used for the next step.
  
  **Tags:** proteins, networks, go-enrichment, functional-annotation, kegg
  
  > **Comments:**
  > **username_1**: If you can add more detail that might help, such as the pathway(s) your STRING analysis indicates. Your question appears vague for the decision you have and it is not clear why you don't use both for two different network analyses  
  
  ---
  
  ## 1 answers
  
  ### Answer by username_2 on 2020-12-23. Score: 1
  
  The answer to your main doubt about "annotation vs. enrichment" is that you need both, but you already have one annotation.
  
  You can only perform a functional enrichment analysis after you have a functional annotation. In your question, you state that you have KEGG annotation for your targets. That is it, knowing which target "belongs" to each KEGG module is an example of functional annotation of your targets. Several tools can annotate genes, proteins, etc. Knowing which protein is related to each drug or disease is also a functional annotation.
  
  Now, knowing which targets are significantly important can be achieved by functional enrichment analysis.
  
  For the network, both information can be used together. For example, you could link all elements to their functional annotation and use the available enrichment score as a quantitative parameter of importance for calculating correlations.
  
  
  ---
  
  