Body: <p>I'm an undergraduate biology student and my thesis is on designing a deep learning architecture to predict whether two proteins interact or not given their primary sequences. I have read some papers with different approaches to the problem including the paper [https://academic.oup.com/bioinformatics/article/35/14/i305/5529260] uses <strong>PIPR</strong> model which is the state of the art model for this problem in 2019 and recently in 2021 the paper [https://www.biorxiv.org/content/10.1101/2021.01.22.427866v1] uses <strong>D-SCRIPT</strong> which surpass <strong>PIPR</strong> with the aspect of the small dataset and has better generalization feature for many model organisms.</p>
  <p>For my problem, I have two questions</p>
  <ol>
  <li>can you suggest to me the approach to build a model for my thesis. Should I follow these papers to build a model, how my model will be different from the models in the papers?</li>
  <li>Which architecture or model recently that the literature considers the most proper for the protein-protein interaction prediction approach?</li>
  </ol>
  <p>I very much appreciate any help from everyone!</p>
  
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2021-08-22T06:56:31.640Z
Comments.Text: Albeit to make a full structure... Check out https://github.com/sokrypton/ColabFold it's a mod of the AlphaFold2 notebook. Albeit not mentioned by AlphaFold2, the Rosettafold paper talks about complexes. It's not benchmarked. If two proteins don't interact the replicates will differ.
Comments.UserDisplayName: Matteo Ferla
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2021-09-02T15:54:21.693Z
Comments.Text: Here is the post mentioned by @ATPoint: https://www.biostars.org/p/9485815/
Comments.UserDisplayName: Ram RS
Tags: <machine-learning><protein-protein-interaction><deep-learning>
Title: Build protein-protein interaction prediction deep learning model
ThreadText: # Build protein-protein interaction prediction deep learning model
  
  (Asked by: username_0 on 2021-08-20)
  
  I'm an undergraduate biology student and my thesis is on designing a deep learning architecture to predict whether two proteins interact or not given their primary sequences. I have read some papers with different approaches to the problem including the paper [https://academic.oup.com/bioinformatics/article/35/14/i305/5529260] uses **PIPR** model which is the state of the art model for this problem in 2019 and recently in 2021 the paper [https://www.biorxiv.org/content/10.1101/2021.01.22.427866v1] uses **D-SCRIPT** which surpass **PIPR** with the aspect of the small dataset and has better generalization feature for many model organisms.
  
  For my problem, I have two questions
  
  1. can you suggest to me the approach to build a model for my thesis. Should I follow these papers to build a model, how my model will be different from the models in the papers?
  2. Which architecture or model recently that the literature considers the most proper for the protein-protein interaction prediction approach?
  
  I very much appreciate any help from everyone!
  
  **Tags:** machine-learning, protein-protein-interaction, deep-learning
  
  > **Comments:**
  > **username_1**: Albeit to make a full structure... Check out https://github.com/sokrypton/ColabFold it's a mod of the AlphaFold2 notebook. Albeit not mentioned by AlphaFold2, the Rosettafold paper talks about complexes. It's not benchmarked. If two proteins don't interact the replicates will differ.  
  > **username_2**: Here is the post mentioned by @ATPoint: https://www.biostars.org/p/9485815/  
  
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  ## 0 answers
  
  