APEX2S: A two-layer machine learning model for discovery of host-pathogen protein-protein interactions on cloud-based multiomics data
- Publisher:
- WILEY
- Publication Type:
- Journal Article
- Citation:
- Concurrency Computation, 2020, 32, (23)
- Issue Date:
- 2020-12-10
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| Filename | Description | Size | |||
|---|---|---|---|---|---|
| cpe.5846.pdf | Published version | 1.33 MB |
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Presented by the avalanche of biological interactions data, computational biology is now facing greater challenges on big data analysis and solicits more studies to mine and integrate cloud-based multiomics data, especially when the data are related to infectious diseases. Meanwhile, machine learning techniques have recently succeeded in different computational biology tasks. In this article, we have calibrated the focus for host-pathogen protein-protein interactions study, aiming to apply the machine learning techniques for learning the interactions data and making predictions. A comprehensive and practical workflow to harness different cloud-based multiomics data is discussed. In particular, a novel two-layer machine learning model, namely APEX2S, is proposed for discovery of the protein-protein interactions data. The results show that our model can better learn and predict from the accumulated host-pathogen protein-protein interactions.
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