mikelkou/fava
Functional Associations using Variational Autoencoders
FAVA helps biologists and bioinformaticians understand how proteins work together by building comprehensive protein interaction networks from 'omics' data like single-cell RNA sequencing or proteomics. You input your experimental data, and it outputs a network showing which proteins are functionally associated. This tool is ideal for researchers studying protein function, especially for less-understood proteins, without being biased by existing literature.
Use this if you need to discover new protein-protein functional associations from your omics data and want to avoid biases present in existing, literature-driven networks.
Not ideal if you are looking for a tool to analyze genetic mutations or perform sequence alignment rather than functional protein associations.
Stars
43
Forks
3
Language
Jupyter Notebook
License
MIT
Last pushed
Mar 09, 2026
Commits (30d)
0
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