<p>There is a <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5921990/bin/12885_2018_4388_MOESM2_ESM.csv" rel="nofollow noreferrer">CSV table</a> in <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5921990/" rel="nofollow noreferrer">this paper</a> with 33 sets of genes.</p>

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2021-05-28T19:56:13.810Z
2021-05-28T19:56:13.810Z
user66081
<p><em>Note: this question has also been asked on <a href="https://www.biostars.org/p/9471832/" rel="nofollow noreferrer">Biostars</a></em></p>
<p>I am currently trying to complete a Breast Cancer Classification task using Neural Networks. I have experimented with using my full dataset of gene expressions(1000+) and managed to improve my results by using only the PAM50 genes. I was wondering though what other genes I could add to the list to even better improve my results.</p>
<p>I have tried looking for papers about extending the PAM50, but could not find anything. I would greatly appreciate any advice.</p>

<gene><cancer><deep-learning>
Important genes beyond PAM50 for breast cancer classification
# Important genes beyond PAM50 for breast cancer classification

(Asked by: username_0 on 2021-05-24)

*Note: this question has also been asked on [Biostars](https://www.biostars.org/p/9471832/)*

I am currently trying to complete a Breast Cancer Classification task using Neural Networks. I have experimented with using my full dataset of gene expressions(1000+) and managed to improve my results by using only the PAM50 genes. I was wondering though what other genes I could add to the list to even better improve my results.

I have tried looking for papers about extending the PAM50, but could not find anything. I would greatly appreciate any advice.

**Tags:** gene, cancer, deep-learning

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## 1 answers

### Answer by username_1 on 2021-05-28. Score: 3

There is a [CSV table](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5921990/bin/12885_2018_4388_MOESM2_ESM.csv) in [this paper](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5921990/) with 33 sets of genes.


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