ReviewNeuroinformatics2025
Twenty Years of Neuroinformatics: A Bibliometric Analysis.
Review in Neuroinformatics, 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.
- From association to intervention: Semantic trajectories and knowledge frontiers in epilepsy-gut microbiota research revealed by bibliometrics and NLP.IBRO neuroscience reports · 2026Review
- The Brain Imaging and Neurophysiology Dataset of large-scale multimodal neural data.Scientific data · 2026Article
- Digital Technologies Supporting Active Ageing: A Bibliometric Analysis of Emerging Trends and Thematic Structures.Inquiry : a journal of medical care organization, provision and financingArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This study presents a thorough bibliometric analysis of Neuroinformatics over the past 20 years, offering insights into the journal's evolution at the intersection of neuroscience and computational science. Using advanced tools such as VOS viewer and methodologies like co-citation analysis, bibliographic coupling, and keyword co-occurrence, we examine trends in publication, citation patterns, and the journal's influence. Our analysis reveals enduring research themes like neuroimaging, data sharing, machine learning, and functional connectivity, which form the core of Neuroinformatics. These themes highlight the journal's role in addressing key challenges in neuroscience through computational methods. Emerging topics like deep learning, neuron reconstruction, and reproducibility further showcase the journal's responsiveness to technological advances. We also track the journal's rising impact, marked by a substantial growth in publications and citations, especially over the last decade. This growth underscores the relevance of computational approaches in neuroscience and the high-quality research the journal attracts. Key bibliometric indicators, such as publication counts, citation analysis, and the h-index, spotlight contributions from leading authors, papers, and institutions worldwide, particularly from the USA, China, and Europe. These metrics provide a clear view of the scientific landscape and collaboration patterns driving progress. This analysis not only celebrates Neuroinformatics's rich history but also offers strategic insights for future research, ensuring the journal remains a leader in innovation and advances both neuroscience and computational science.
Indexed as
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.