ArticleCurrent protocols2025
Creating an Interactive Web Interface for Networks Stored in Knowledge Graph Databases.
Article in Current protocols, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 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
3 citing papers in PubMed.
- ChEA-KG and ChEA-KG-TS: a network-based transcription factor enrichment analysis tool with an accompanying time-series workflow.Nucleic acids research · 2026Article
- The Common Fund Data Ecosystem (CFDE).bioRxiv : the preprint server for biology · 2026Article
- Creating an Interactive Web Interface for Networks Stored in Knowledge Graph Databases.Current protocols · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
Abstract
Knowledge graphs (KG) are an emerging approach to organize biomedical research data by abstracting knowledge into networks that connect genes, diseases, pathogens, drugs, metabolites, cell types, pathways, patients, researchers, and other related concepts. While there are many KG databases, most do not offer a free and customizable web-based user interface (UI) to query and interact with KG. We developed an open-source UI to create interactive websites from data stored in KG databases. So far, the KG-UI has been applied to eight bioinformatics projects: ReproTox-KG, Enrichr-KG, Harmonizome-KG, Data Distillery KG-UI, Biomarker-KG, Common Fund Data Ecosystem Gene Set Enrichment (CFDE-GSE), ChEA-KG, and lncRNAlyzr. To demonstrate how to install and customize the KG-UI, we created a demo KG that displays a network of relationships between NIH-funded principal investigators (PIs) from a single institution in a specific year. This PI network was constructed by querying PubMed using grant information collected by the Blue Ridge Institute for Medical Research (BRIMR). After publications were collected from PubMed, PI name disambiguation and metadata formatting was performed to create the PI demo KG. Instructions for ingesting this network of PIs into a KG database, setting up the web app, and customizing the app are provided in a step-by-step user guide. The KG-UI source code is available from: https://github.com/MaayanLab/Knowledge-Graph-UI/ and the demo KG is available from: https://github.com/MaayanLab/PINetworkDemo. © 2025 The Author(s). Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: Creating the principal investigator network Basic Protocol 2: Validating the principal investigator network Basic Protocol 3: Ingesting the KG assertions into Neo4j Basic Protocol 4: Interacting with the KG via the Neo4j remote interface Basic Protocol 5: Building and customizing the KG-UI Basic Protocol 6: Interacting with the KG-UI website.
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What Socratic 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 Socratic graph.