ArticleBioinformatics (Oxford, England)2018
DDR: efficient computational method to predict drug-target interactions using graph mining and machine learning approaches.
Article in Bioinformatics (Oxford, England), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
12 citing papers in PubMed.
- Improving drug repositioning with negative data labeling using large language models.Journal of cheminformatics · 2025Article
- KGRDR: a deep learning model based on knowledge graph and graph regularized integration for drug repositioning.Frontiers in pharmacology · 2025Article
- GSRF-DTI: a framework for drug-target interaction prediction based on a drug-target pair network and representation learning on a large graph.BMC biology · 2024Article
- Article
- Label Transfer for Drug Disease Association in Three Meta-Paths.Evolutionary bioinformatics online · 2024Article
- Prediction of Drug-Target Interaction Using Dual-Network Integrated Logistic Matrix Factorization and Knowledge Graph Embedding.Molecules (Basel, Switzerland) · 2022Article
- A brief review of protein-ligand interaction prediction.Computational and structural biotechnology journal · 2022Review
- Development of simultaneous interaction prediction approach (SiPA) for the expansion of interaction network of traditional Chinese medicine.Chinese medicine · 2020Article
- Predicting Polypharmacy Side-effects Using Knowledge Graph Embeddings.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2020Article
- Predicting The Effects of Chemical-Protein Interactions On Proteins Using Tensor Factorisation.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2020Article
- Dipeptide Frequency of Word Frequency and Graph Convolutional Networks for DTA Prediction.Frontiers in bioengineering and biotechnology · 2020Article
- Comparison Study of Computational Prediction Tools for Drug-Target Binding Affinities.Frontiers in chemistry · 2019Review
Corrections and comments
- Erratum for
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
PubMed holds no abstract for this paper.
Identifiers
What OpenQuestion holds
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.