ArticleNucleic acids research2016
The SIDER database of drugs and side effects.
Article in Nucleic acids research, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 567 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
567 citing papers in PubMed.
- Circular RNAs in Drug-Induced Cardiotoxicity: Roles, Mechanisms, and Therapeutic Potential.Journal of biochemical and molecular toxicology · 2026Review
- Measuring AI Progress in Drug Discovery: A Reproducible Leaderboard for the Tox21 Challenge.Journal of chemical information and modeling · 2026Article
- CAFNet-DG: Task-Specific Modeling and Prevalence-Aware Evaluation for Adverse Drug Reaction Prioritization with Ordinal-Frequency Estimation.International journal of molecular sciences · 2026Article
- Topology-Guided Multi-Level Graph Learning: A Unified Framework for Molecular Property Prediction.Molecules (Basel, Switzerland) · 2026Article
- Scalable molecular representations enabled by multimodal fusion and sequence distillation.Nature communications · 2026Article
- HD-SKRG: a hierarchical dual-view and structure-knowledge relation graph enhancement network for few-shot molecular property prediction.Molecular diversity · 2026Article
- Using Artificial Intelligence to Identify Patterns and Predictors of Adverse Drug Reactions in Cardiovascular Patients: A Comprehensive Narrative Review.American journal of cardiovascular drugs : drugs, devices, and other interventions · 2026Review
- In-silico personalized protein-protein interaction networks prioritize candidate compounds for glioblastoma.PLoS computational biology · 2026Article
- Contrastive learning of adverse events to provide effective and interpretable vector representations for machine-assisted pharmacovigilance.Briefings in bioinformatics · 2026Article
- ToxiGuard: an AOP-guided mechanistically interpretable framework for multi-organ toxicity prediction.Archives of toxicology · 2026Article
- MSF-HierGNN: a multi-source substructure-fusion hierarchical GNN method and web server to predict molecular property for drug design.Briefings in bioinformatics · 2026Article
- MSGRL: A Motif-Driven Self-Supervised Graph Representation Learning Framework for Interpretable Molecular Property Prediction.Molecules (Basel, Switzerland) · 2026Article
- Article
- Tail-aware heterogeneous graph neural networks for multi-class drug-drug interaction prediction.Bioinformatics (Oxford, England) · 2026Article
- Deciphering the Leading-Edge Spatiotemporal Microenvironment of Hepatocellular Carcinoma for Targeted Drug Discovery Using SpaPred.International journal of molecular sciences · 2026Article
- Drugs inducing interstitial lung disease: in silico analysis of their structures and targets.Molecular medicine (Cambridge, Mass.) · 2026Article
- VITAGRAPH: building a knowledge graph for biologically relevant learning tasks.Scientific data · 2026Article
- Informative relational learning for adverse reaction prediction with enhanced generalization to novel drugs.Bioinformatics (Oxford, England) · 2026Article
- Integrating multi-type features and knowledge graph for graded prediction of drug-induced liver injury in humans.PLoS computational biology · 2026Article
- Computer-Interpretable Domain Knowledge for Drug-Induced Acute Kidney Injury: a Knowledge Graph Approach.Scientific data · 2026Article
507 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Unwanted side effects of drugs are a burden on patients and a severe impediment in the development of new drugs. At the same time, adverse drug reactions (ADRs) recorded during clinical trials are an important source of human phenotypic data. It is therefore essential to combine data on drugs, targets and side effects into a more complete picture of the therapeutic mechanism of actions of drugs and the ways in which they cause adverse reactions. To this end, we have created the SIDER ('Side Effect Resource', http://sideeffects.embl.de) database of drugs and ADRs. The current release, SIDER 4, contains data on 1430 drugs, 5880 ADRs and 140 064 drug-ADR pairs, which is an increase of 40% compared to the previous version. For more fine-grained analyses, we extracted the frequency with which side effects occur from the package inserts. This information is available for 39% of drug-ADR pairs, 19% of which can be compared to the frequency under placebo treatment. SIDER furthermore contains a data set of drug indications, extracted from the package inserts using Natural Language Processing. These drug indications are used to reduce the rate of false positives by identifying medical terms that do not correspond to ADRs.
Indexed as
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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.