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Si us plau utilitzeu sempre aquest identificador per citar o enllaçar aquest document: https://hdl.handle.net/2445/230873
Twenty Years of Neuroinformatics: A Bibliometric Analysis
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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.
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GUILLEN PUJADAS, Miguel, et al. Twenty Years of Neuroinformatics: A Bibliometric Analysis. Neuroinformatics. 2025. Vol. 23, num. 1. ISSN 1539-2791. [consulted: 24 of July of 2026]. Available at: https://hdl.handle.net/2445/230873