ReviewFrontiers in pharmacology2018
Network-Based Methods for Prediction of Drug-Target Interactions.
Review in Frontiers in pharmacology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 101 papers.
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Who cites it
101 citing papers in PubMed.
- A Node-Adaptive Feature Fusion Network for Drug-Target Interaction Prediction Based on Multi-View Graphs.Biomolecules · 2026Article
- Bioactive Constituents, Mechanisms, and Complementary Therapeutic Applications of Food-Medicine Continuum Materia Medica for Atherosclerosis Prevention and Treatment.Pharmaceuticals (Basel, Switzerland) · 2026Review
- Machine Learning Approaches for Compound-Target Interaction Prediction: A Review.Foods (Basel, Switzerland) · 2026Review
- Integration of multi-omics and network toxicology reveals TLR4-mediated nephrotoxicity induced by arecoline.BMC pharmacology & toxicology · 2026Article
- Peiminine attenuates inflammatory bowel disease by suppressing TLR4 mediated NFƙB pathway: an integrated network pharmacology and experimental validation.Scientific reports · 2026Article
- Bioinformatics approach to identifying molecular targets of Danlou tablet against atherosclerosis: a machine learning pharmacology study.Naunyn-Schmiedeberg's archives of pharmacology · 2026Article
- Jichuan decoction alleviates constipation by inhibiting the PI3K/Akt/mTOR signaling pathway: an integrated network pharmacology and experimental study.Scientific reports · 2026Article
- Curated and Structure-Based Drug-Target Interactions Improve Underprediction of Drug Side Effects in Network Models.Journal of chemical information and modeling · 2026Article
- ViralBindPredict: empowering viral protein-ligand binding sites through deep learning and protein sequence-derived insights.GigaScience · 2026Article
- A Systematic Review of Drug-Related InteractionsUtilizing Deep Learning and LLMs for Prediction and Mitigation.ACS omega · 2025Review
- Article
- The Constrained Disorder Principle: A Paradigm Shift for Accurate Interactome Mapping and Information Analysis in Complex Biological Systems.Bioengineering (Basel, Switzerland) · 2025Review
- AΙ-Driven Drug Repurposing: Applications and Challenges.Medicines (Basel, Switzerland) · 2025Review
- Drug-disease networks and drug repurposing.PLoS computational biology · 2025Article
- Erchen Decoction Offers Health Benefits in Regulating Obesity: Component Analysis, Network Pharmacology, and Experiment Verification.Food science & nutrition · 2025Article
- Drug-target interaction prediction based on graph convolutional autoencoder with dynamic weighting residual GCN.BMC bioinformatics · 2025Article
- Cancer network pharmacology: multi-network regulatory mechanisms and future directions.Medical oncology (Northwood, London, England) · 2025Review
- Astaxanthin ameliorates benzalkonium chloride-induced dry eye disease through suppressing inflammation and oxidative stress via Keap1-Nrf2/HO-1 signaling pathways.Animal models and experimental medicine · 2025Article
- Labels as a feature: Network homophily for systematically annotating human GPCR drug-target interactions.Nature communications · 2025Article
- Integrating network pharmacology and in vivo study to explore the anti-Alzheimer's potential of3 Biotech · 2025Article
41 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Drug-target interaction (DTI) is the basis of drug discovery. However, it is time-consuming and costly to determine DTIs experimentally. Over the past decade, various computational methods were proposed to predict potential DTIs with high efficiency and low costs. These methods can be roughly divided into several categories, such as molecular docking-based, pharmacophore-based, similarity-based, machine learning-based, and network-based methods. Among them, network-based methods, which do not rely on three-dimensional structures of targets and negative samples, have shown great advantages over the others. In this article, we focused on network-based methods for DTI prediction, in particular our network-based inference (NBI) methods that were derived from recommendation algorithms. We first introduced the methodologies and evaluation of network-based methods, and then the emphasis was put on their applications in a wide range of fields, including target prediction and elucidation of molecular mechanisms of therapeutic effects or safety problems. Finally, limitations and perspectives of network-based methods were discussed. In a word, network-based methods provide alternative tools for studies in drug repurposing, new drug discovery, systems pharmacology and systems toxicology.
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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.