ArticleNucleic acids research2024
Drugst.One - a plug-and-play solution for online systems medicine and network-based drug repurposing.
Article in Nucleic acids research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 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
19 citing papers in PubMed.
- Inferring and evaluating network medicine-based disease modules with nextflow.Bioinformatics (Oxford, England) · 2026Article
- Leveraging Quantitative Proteomics and Extracellular Vesicle Data to Uncover Druggable Receptor Kinases Across Cancers.Journal of extracellular vesicles · 2026Article
- Computational frameworks for enhanced extracellular vesicle biomarker discovery.Experimental & molecular medicine · 2026Review
- Mapping drug mechanisms with ProteomicsDB: unified omics and cell sensitivity data at scale.Nucleic acids research · 2026Article
- Leveraging bioinformatics approaches for drug repositioning in space radiation protection.PloS one · 2026Article
- NetMedPy: a Python package for large-scale network medicine screening.Bioinformatics (Oxford, England) · 2025Article
- Article
- Drug Repurposing for Kala-Azar.Pharmaceutics · 2025Article
- Computational drug repurposing: approaches, evaluation of in silico resources and case studies.Nature reviews. Drug discovery · 2025Review
- Computational Drug Repositioning in Cardiorenal Disease: Opportunities, Challenges, and Approaches.Proteomics · 2025Article
- NApy: efficient statistics in Python for large-scale heterogeneous data with enhanced support for missing data.GigaScience · 2025Article
- Network medicine-based epistasis detection in complex diseases: ready for quantum computing.Nucleic acids research · 2024Article
- MetalinksDB: a flexible and contextualizable resource of metabolite-protein interactions.Briefings in bioinformatics · 2024Article
- PathDIP 5: improving coverage and making enrichment analysis more biologically meaningful.Nucleic acids research · 2024Article
- WikiPathways 2024: next generation pathway database.Nucleic acids research · 2024Article
- Molecular landscape of kidney allograft tissues data integration portal (NephroDIP): a curated database to improve integration of high-throughput kidney transplant datasets.Frontiers in immunology · 2024Article
- Inference of differential key regulatory networks and mechanistic drug repurposing candidates from scRNA-seq data with SCANet.Bioinformatics (Oxford, England) · 2023Article
- Proteomic meta-study harmonization, mechanotyping and drug repurposing candidate prediction with ProHarMeD.NPJ systems biology and applications · 2023Article
- Meta-analysis of proteomics data from osteoblasts, bone, and blood: Insights into druggable targets, active factors, and potential biomarkers for bone biomaterial design.Journal of tissue engineeringArticle
Corrections and comments
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Authors and funding
40 authors.
Funding
Abstract
In recent decades, the development of new drugs has become increasingly expensive and inefficient, and the molecular mechanisms of most pharmaceuticals remain poorly understood. In response, computational systems and network medicine tools have emerged to identify potential drug repurposing candidates. However, these tools often require complex installation and lack intuitive visual network mining capabilities. To tackle these challenges, we introduce Drugst.One, a platform that assists specialized computational medicine tools in becoming user-friendly, web-based utilities for drug repurposing. With just three lines of code, Drugst.One turns any systems biology software into an interactive web tool for modeling and analyzing complex protein-drug-disease networks. Demonstrating its broad adaptability, Drugst.One has been successfully integrated with 21 computational systems medicine tools. Available at https://drugst.one, Drugst.One has significant potential for streamlining the drug discovery process, allowing researchers to focus on essential aspects of pharmaceutical treatment research.
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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.