license:mit size_categories:100B<n<1T region:us biology
---
license: mit
tags:
- biology
size_categories:
- 100B<n<1T
---
# Aggregated Weight Matrices Used in *Transformers Enhance the Predictive Power of Network Medicine*
*Jonah Spector, Andrés Aldana Gonzalez, Michael Sebek, Joseph Ehlert, Christian DeFrondeville, Susan Dina Ghiassian, and Albert-László Barabási*
## Data Structure
This directory contains all aggregated weight matrices used to make figures in the manuscript. The data structure is as follows
```
aggregated_matrices
    aggregated_attentions
        dcm_samples
            fine_tuned
                max
                    layer_0
                    layer_1
                    layer_2
                    layer_3
                    layer_4
                    layer_5
            pretrained
                max
        genecorpus
            fine_tuned
                max
            pretrained
                max
    aggregated_embeddings
        dcm_samples
            fine_tuned
                max
                    layer_input
                    layer_0
                    layer_1
                    layer_2
                    layer_3
                    layer_4
                    layer_5
            pretrained
                max
        genecorpus
            fine_tuned
                max
            pretrained
                max
```
In the folder at the end of each branch there are 3 files, called ```counts.pkl```, ```vals.pkl```, ```gene_dict.pkl```. The counts matrix is a square matrix of size NxN, where N is the number of unique genes in the sample set. It counts how many times each pair of genes co-occurs in a sample. The vals matrix is the same shape, and contains the aggregated weight between each pair of genes. ```gene_dict.pkl``` is a dictionary that specifies the index of each gene in the matrix.
