Answers.Body: <p>SEM specialises in identifying 'latent variables'.</p>
  
  <p>SEM are extensively used for questionnaire data. In questionnaire data, latent variables are the 'psychological' factors behind given (human) behaviours. </p>
  
  <p>Applying SEM to explicit molecular mechanisms doesn't make much sense unless there is a hidden component in a mechanism that has not been identified. However, even here the SEM will not tell you what the 'latent variable' represents.</p>
  
  <p>Thus I don't believe there is a good application to bioinformatics, outside human phenotypes derived from questionnaire data, which might be mapped on biological variables, but I could be wrong. </p>
  
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Answers.CreationDate: 2019-01-08T17:56:50.360Z
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Answers.Body: <p>I have came across them in gene regulatory network analysis before. see <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2278111/" rel="nofollow noreferrer">here</a> and <a href="http://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1003068" rel="nofollow noreferrer">here</a>. However I haven't seen them in other contexts, but that's not to say they don't exist.</p>
  
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Answers.CreationDate: 2017-11-08T11:01:28.997Z
Answers.LastActivityDate: 2017-11-08T11:10:56.987Z
Answers.LastEditDate: 2017-11-08T11:10:56.987Z
Answers.UserDisplayName: TW93
Body: <p>I am a bioinformatics student and I was learning the basics of <a href="https://en.wikipedia.org/wiki/Structural_equation_modeling" rel="nofollow noreferrer">structural equation modeling (SEM)</a>.</p>
  
  <p>I was wondering, are there any applications of SEM on  bioinformatics? Are there any strong sides for use of structural equation models using data on bioinformatics?</p>
  
  <p>I did a quick search and found almost nothing. While it seemed like a learning algorithm, I can't say I figured it out completely.</p>
  
Comments.ContentLicense: CC BY-SA 3.0
Comments.CreationDate: 2017-11-08T09:22:11.517Z
Comments.Text: I am not sure I understand your question, could you [edit] to clarify it? What do you mean by "strong sides for bioinformatics"? What do you want to know about bioinformatics? Or are you "just" asking about the algorithm of SEM? BTW [here](https://academic.oup.com/bib/article/3/2/119/181732) is a paper using SEM.
Comments.UserDisplayName: llrs
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Comments.CreationDate: 2017-11-08T11:12:55.983Z
Comments.Text: I mean, I haven't come across the usage of SEM in bioinformatics related articles. Bu it is widely used in education, questionaries and behavioral studies. In summary, I was wondering whether this method suitable for genomics studies or not.
Comments.UserDisplayName: Ugur Toprak
Tags: <r><algorithms><structural-variation>
Title: Can structural - equation modeling be used in Bioinformatics?
ThreadText: # Can structural - equation modeling be used in Bioinformatics?
  
  (Asked by: username_0 on 2017-11-08)
  
  I am a bioinformatics student and I was learning the basics of [structural equation modeling (SEM)](https://en.wikipedia.org/wiki/Structural_equation_modeling).
  
  I was wondering, are there any applications of SEM on bioinformatics? Are there any strong sides for use of structural equation models using data on bioinformatics?
  
  I did a quick search and found almost nothing. While it seemed like a learning algorithm, I can't say I figured it out completely.
  
  **Tags:** r, algorithms, structural-variation
  
  > **Comments:**
  > **username_1**: I am not sure I understand your question, could you [edit] to clarify it? What do you mean by "strong sides for bioinformatics"? What do you want to know about bioinformatics? Or are you "just" asking about the algorithm of SEM? BTW [here](https://academic.oup.com/bib/article/3/2/119/181732) is a paper using SEM.  
  > **username_0**: I mean, I haven't come across the usage of SEM in bioinformatics related articles. Bu it is widely used in education, questionaries and behavioral studies. In summary, I was wondering whether this method suitable for genomics studies or not.  
  
  ---
  
  ## 2 answers
  
  ### Answer by username_2 on 2019-01-08. Score: 1
  
  SEM specialises in identifying 'latent variables'.
  
  SEM are extensively used for questionnaire data. In questionnaire data, latent variables are the 'psychological' factors behind given (human) behaviours.
  
  Applying SEM to explicit molecular mechanisms doesn't make much sense unless there is a hidden component in a mechanism that has not been identified. However, even here the SEM will not tell you what the 'latent variable' represents.
  
  Thus I don't believe there is a good application to bioinformatics, outside human phenotypes derived from questionnaire data, which might be mapped on biological variables, but I could be wrong.
  
  
  ---
  
  ### Answer by username_3 on 2017-11-08. Score: 1
  
  I have came across them in gene regulatory network analysis before. see [here](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2278111/) and [here](http://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1003068). However I haven't seen them in other contexts, but that's not to say they don't exist.
  
  
  ---
  
  