A bipartite graph composed of approved drugs and proteins linked by drug–target binary associations.
A strategy for identifying new indications for approved or investigational (including clinically failed) drugs that have not been originally approved or dedicated (also termed drug repositioning, reprofiling or re-tasking).
Represents a group of nodes (ie, proteins or genes) whose perturbation can be linked to a particular disease (eg, COVID-19) phenotype.
An inter-discipline that applies systems biology principles and data science techniques in pharmacology.
The set of physical protein–protein interactions (the interactome) in human cells.
A discipline that seeks to redefine disease and therapeutics from an integrated perspective using systems biology and network science methodologies, offering important applications to drug design.
Node or vertex
The basic unit of graphs. Usually visualised as circles (or in other shapes), nodes represent basic entities, such as drugs and proteins.
Edge or link
A basic unit of graphs that connects two nodes. Usually visualised as lines (with arrows if directed), edges represent the relationships (eg, protein interaction) between the nodes.
- Cheng F
- Desai RJ
- Handy DE
- et al.
Artificial intelligence (AI)
The study of building machines or programmes that exhibit human intelligence in doing specific or general tasks.
Machine learning algorithms
A subset of AI algorithms that can learn from data, therefore removing the need for explicit instructions on how to do certain tasks.
Deep neural networks
A general term referring to multilayer neural networks.
Convolutional neural networks
Neural network architectures specifically designed for analysing image data, which generally include multiple layers of convolutional layers and pooling layers.
Graph representation learning
Specific deep learning techniques that are developed for learning feature representations of graph structure data.
Visible neural network
A new generation of visible approaches that aim to guide the structure of machine learning models with an increasingly extensive knowledge of a biological mechanism.