Abstract
Network-based learning enables the identification of possible undiscovered interactions in biological systems. In this issue of Patterns, Du et al. show that applying these methods to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) reveals potential infection targets of the virus and possible interactions between SARS-CoV-2 proteins and human proteins.
Highlights
Network-based learning enables the identification of possible undiscovered interactions in biological systems
In this issue of Patterns, Du et al show that applying these methods to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) reveals potential infection targets of the virus and possible interactions between SARS-CoV-2 proteins and human proteins
Network-based data structures and methods have been an effective way of incorporating relational information and describing complex biological systems
Summary
Network-based learning enables the identification of possible undiscovered interactions in biological systems. In this issue of Patterns, Du et al show that applying these methods to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) reveals potential infection targets of the virus and possible interactions between SARS-CoV-2 proteins and human proteins.
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