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I am exploring application of Graph convolution network on gene similarity network. I am trying to explore genemania.org and https://string-db.org/

Please let me know where can I find the data for my research in gene interaction network, which allows me to download the data in the form of an adjacency matrix.

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  • $\begingroup$ Welcome to Bioinformatics.StackExchange! To help us help you, it's always a good idea to let us know where you've looked and/or what you've tried so far. $\endgroup$ – Daniel Standage Mar 26 '19 at 18:55
  • $\begingroup$ Also, please edit your question and show us an example of your desired format. Do you only want the names of interacting proteins? Do you want some sort of value for the edges? Do you want all interactions (STRING has a lot of noise) or only high quality one? Maybe you only want binary, direct protein-protein interactions (so no immunoprecipitation results, or no complexes for example)? The more details you give us, the better your chances of getting a useful answer. $\endgroup$ – terdon Mar 26 '19 at 19:11
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The STRING download page is here. I am not sure that they provide any data in the form of an adjacency matrix, as the number of nodes (rows/columns) would be quite large, and for this reason they are likely to represent the data as lists of links, for compactness.

Their data will likely have to be cleaned for any purpose you are interested in. You will have to make some decisions on how to filter the data. For example, as suggested in the comments, you may want to filter on the quality of the evidence supporting interactions, or based on species of the protein, or other things.

It's possible that you may have better luck going with another database that has done some of these steps already. For example, there are relatively compact human interactome datasets here, or yeast interactome datasets here. In this case you will still need to convert from a list of links to an adjacency matrix, however this is not very difficult if you can use a scripting language.

Notably, you may have to figure out how to distinguish missing data from tested non-interactions in these cases (or decide that missing data is ok). In most cases people will not have exhaustively tested every cell of the all-by-all interactome adjacency matrix.

Hope that helps.

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