ArticleScience signaling2010
Systems pharmacology of arrhythmias.
Article in Science signaling, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 64 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
64 citing papers in PubMed, 128 citations in OpenAlex.
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- BioMADE: Predicting Torsades de Pointes from molecular structures through biologically informed representations.bioRxiv : the preprint server for biology · 2026Article
- Integration of Gastric Cancer RNA-Seq Datasets Along With PPI Network Suggests That Nonhub Nodes Have the Potential to Become Biomarkers.Cancer reports (Hoboken, N.J.) · 2025Article
- PRDM16 determines specification of ventricular cardiomyocytes by suppressing alternative cell fates.Life science alliance · 2024Article
- No population left behind: Improving paediatric drug safety using informatics and systems biology.British journal of clinical pharmacology · 2022Review
- A Comparative Study of Systems Pharmacology and Gene Chip Technology for Predicting Targets of a Traditional Chinese Medicine Formula in Primary Liver Cancer Treatment.Frontiers in pharmacology · 2022Article
- Systems Biomedicine of Primary and Metastatic Colorectal Cancer Reveals Potential Therapeutic Targets.Frontiers in oncology · 2021Article
- Transcriptomic profiling of human cardiac cells predicts protein kinase inhibitor-associated cardiotoxicity.Nature communications · 2020Article
- Gradient Boosting Decision Tree-Based Method for Predicting Interactions Between Target Genes and Drugs.Frontiers in genetics · 2019Article
- A tutorial on model informed approaches to cardiovascular safety with focus on cardiac repolarisation.Journal of pharmacokinetics and pharmacodynamics · 2018Article
- Physiological genomics identifies genetic modifiers of long QT syndrome type 2 severity.The Journal of clinical investigation · 2018Article
- Network, Transcriptomic and Genomic Features Differentiate Genes Relevant for Drug Response.Frontiers in genetics · 2018Article
- Identification of the active compounds and significant pathways of yinchenhao decoction based on network pharmacology.Molecular medicine reports · 2017Article
- Systems biology of cellular membranes: a convergence with biophysics.Wiley interdisciplinary reviews. Systems biology and medicine · 2017Review
- Article
- Harnessing Big Data for Systems Pharmacology.Annual review of pharmacology and toxicology · 2017Review
- Network Pharmacology-Based Approach to Investigate the Analgesic Efficacy and Molecular Targets of Xuangui Dropping Pill for Treating Primary Dysmenorrhea.Evidence-based complementary and alternative medicine : eCAM · 2017Article
- Molecular Targets and Associated Potential Pathways of Danlu Capsules in Hyperplasia of Mammary Glands Based on Systems Pharmacology.Evidence-based complementary and alternative medicine : eCAM · 2017Article
- Mechanism-based Pharmacovigilance over the Life Sciences Linked Open Data Cloud.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2017Article
- An Integrative Data Science Pipeline to Identify Novel Drug Interactions that Prolong the QT Interval.Drug safety · 2016Article
4 more citing papers are in PubMed but not listed here.
Corrections and comments
- Erratum issued
Authors and funding
3 authors at 1 institution in 1 country.
Funding
Abstract
Long QT syndrome (LQTS) is a congenital or drug-induced change in electrical activity of the heart that can lead to fatal arrhythmias. Mutations in 12 genes encoding ion channels and associated proteins are linked with congenital LQTS. With a computational systems biology approach, we found that gene products involved in LQTS formed a distinct functional neighborhood within the human interactome. Other diseases form similarly selective neighborhoods, and comparison of the LQTS neighborhood with other disease-centered neighborhoods suggested a molecular basis for associations between seemingly unrelated diseases that have increased risk of cardiac complications. By combining the LQTS neighborhood with published genome-wide association study data, we identified previously unknown single-nucleotide polymorphisms likely to affect the QT interval. We found that targets of U.S. Food and Drug Administration (FDA)-approved drugs that cause LQTS as an adverse event were enriched in the LQTS neighborhood. With the LQTS neighborhood as a classifier, we predicted drugs likely to have risks for QT effects and we validated these predictions with the FDA's Adverse Events Reporting System, illustrating how network analysis can enhance the detection of adverse drug effects associated with drugs in clinical use. Thus, the identification of disease-selective neighborhoods within the human interactome can be useful for predicting new gene variants involved in disease, explaining the complexity underlying adverse drug side effects, and predicting adverse event susceptibility for new drugs.
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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.