<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>

CC BY-SA 4.0
2021-08-22T06:56:31.640Z
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.
Matteo Ferla
CC BY-SA 4.0
2021-09-02T15:54:21.693Z
Here is the post mentioned by @ATPoint: https://www.biostars.org/p/9485815/
Ram RS
<machine-learning><protein-protein-interaction><deep-learning>
Build protein-protein interaction prediction deep learning model
# 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

