Lia Domide

729 citations
5 papers · 322 · h-index 4

Impact in

Papers in

    • Functional Brain Connectivity Studies 4
    • Neural dynamics and brain function 3
    • Memory and Neural Mechanisms 1
    • EEG and Brain-Computer Interfaces 1
    • Bioinformatics and Genomic Networks 1
    • Biomedical Text Mining and Ontologies 1

Lia Domide

4 papers receiving 320 citations

Peers

Lia Domide
Comparison fields: 5 of 45
  • Cognitive Neuroscience 276
  • Radiology, Nuclear Medicine and Imaging 93
  • Cellular and Molecular Neuroscience 48
  • Biophysics 14
  • Computational Mathematics 1
Replace Xiaolu Kong with:
Xiaolu Kong Singapore
Kevin A. Archie United States
Răzvan Gămănuț United States
Loïc Magrou United States
Hannelore Aerts Belgium
James C. Pang Australia
Ricardo Pio Monti United Kingdom
Eric Bridgeford United States
Teresa Murta United Kingdom
Marie-Alice Gariel France
Lia Domide relative to Xiaolu Kong Singapore Xiaolu Kong's profile →
Citations per field
00.5×1.5×2.3×
Xiaolu Kong · 1×
Citations per year

Countries citing papers authored by Lia Domide

Since Specialization
Citations

This map shows the geographic impact of Lia Domide's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Lia Domide with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Lia Domide more than expected).

Fields of papers citing papers by Lia Domide

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Lia Domide. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Lia Domide. The network helps show where Lia Domide may publish in the future.

Co-authors

The 21 scholars most cited alongside Lia Domide, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Lia Domide Line = papers co-authored together Lia Domide links everyone, so they are left out of the graph.

All Works

About Lia Domide

Lia Domide is a scholar working on Cognitive Neuroscience, Molecular Biology, Computational Theory and Mathematics, Radiology, Nuclear Medicine and Imaging and Infectious Diseases, having authored 5 papers that have together received 322 indexed citations. Recurring topics across this work include Functional Brain Connectivity Studies (4 papers), Neural dynamics and brain function (3 papers), Memory and Neural Mechanisms (1 paper), Advanced Neuroimaging Techniques and Applications (1 paper), Bioinformatics and Genomic Networks (1 paper), Computational Drug Discovery Methods (1 paper), EEG and Brain-Computer Interfaces (1 paper) and Biomedical Text Mining and Ontologies (1 paper). The work is most often cited by research in Cognitive Neuroscience (276 citations), Radiology, Nuclear Medicine and Imaging (93 citations), Cellular and Molecular Neuroscience (48 citations), Biophysics (14 citations) and Computational Mathematics (1 citation). Lia Domide has collaborated with scholars based in France, Germany and Canada. Frequent co-authors include Viktor Jirsa, Marmaduke Woodman, Paula Sanz‐Leon, Anthony R. McIntosh, S. A. Knock, Laurent Pézard, M. Shahid, Jiali Wang, Hui Li and B. G. Müller. Their work appears in journals such as Frontiers in Neuroinformatics, Journal of Alzheimer s Disease and eLife.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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