ArticleEntropy (Basel, Switzerland)2023
Link Prediction with Continuous-Time Classical and Quantum Walks.
Article in Entropy (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed, 14 citations in OpenAlex.
- Machine Learning and Deep Learning Frameworks for Human-Virus Protein-Protein Interaction Prediction: Emerging Architectures, Methods, Benchmarks, and Challenges.International journal of molecular sciences · 2026Review
- Advancing understanding of long COVID pathophysiology through quantum walk-based network analysis.Bioinformatics advances · 2026Article
- Article
- Coalition of explainable artificial intelligence and quantum computing in precision medicine.Computational and structural biotechnology journal · 2025Review
- Disease gene prioritization with quantum walks.Bioinformatics (Oxford, England) · 2024Article
- Efficient Implementation of Discrete-Time Quantum Walks on Quantum Computers.Entropy (Basel, Switzerland) · 2024Article
- On the complexity of quantum link prediction in complex networks.Scientific reports · 2024Article
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Authors and funding
6 authors at 2 institutions in 1 country.
Funding
Abstract
Protein-protein interaction (PPI) networks consist of the physical and/or functional interactions between the proteins of an organism, and they form the basis for the field of network medicine. Since the biophysical and high-throughput methods used to form PPI networks are expensive, time-consuming, and often contain inaccuracies, the resulting networks are usually incomplete. In order to infer missing interactions in these networks, we propose a novel class of link prediction methods based on continuous-time classical and quantum walks. In the case of quantum walks, we examine the usage of both the network adjacency and Laplacian matrices for specifying the walk dynamics. We define a score function based on the corresponding transition probabilities and perform tests on six real-world PPI datasets. Our results show that continuous-time classical random walks and quantum walks using the network adjacency matrix can successfully predict missing protein-protein interactions, with performance rivalling the state-of-the-art.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.