Eric Neumann

2.1k citations
21 papers · 695 · h-index 12

Impact in

Papers in

    • Bioinformatics and Genomic Networks 8
    • Biomedical Text Mining and Ontologies 7
    • Gene expression and cancer classification 4
    • Metabolomics and Mass Spectrometry Studies 3
    • Microbial Metabolic Engineering and Bioproduction 2
    • Semantic Web and Ontologies 4

Eric Neumann

20 papers receiving 646 citations

Peers

Eric Neumann
Comparison fields: 5 of 110
  • Information Systems and Management 64
  • Cellular and Molecular Neuroscience 132
  • Molecular Biology 465
  • Computational Theory and Mathematics 76
  • Artificial Intelligence 138
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Citations per field
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Citations per year

Countries citing papers authored by Eric Neumann

Since Specialization
Citations

This map shows the geographic impact of Eric Neumann'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 Eric Neumann with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Eric Neumann more than expected).

Fields of papers citing papers by Eric Neumann

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Eric Neumann. 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 Eric Neumann. The network helps show where Eric Neumann may publish in the future.

Co-authors

The 25 scholars most cited alongside Eric Neumann, 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 Eric Neumann Line = papers co-authored together Eric Neumann links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 21 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1996141
2 200494
3 200793
4 200455
5 200550
6 200948
7 200539
8 199237
9 200430
10 200825
11 200424
12
An evaluation of ontology exchange languages for bioinformatics.
200022
13 199210
14 202110
15 20065
16 20023
17 20213
18 20073
19 20212
20 20151

About Eric Neumann

Eric Neumann is a scholar working on Molecular Biology, Artificial Intelligence, Cellular and Molecular Neuroscience, Ecology, Evolution, Behavior and Systematics and Information Systems and Management, having authored 21 papers that have together received 695 indexed citations. Recurring topics across this work include Bioinformatics and Genomic Networks (8 papers), Biomedical Text Mining and Ontologies (7 papers), Semantic Web and Ontologies (4 papers), Gene expression and cancer classification (4 papers), Metabolomics and Mass Spectrometry Studies (3 papers), Neurobiology and Insect Physiology Research (3 papers), Computational Drug Discovery Methods (2 papers) and Microbial Metabolic Engineering and Bioproduction (2 papers). The work is most often cited by research in Information Systems and Management (64 citations), Cellular and Molecular Neuroscience (132 citations), Molecular Biology (465 citations), Computational Theory and Mathematics (76 citations) and Artificial Intelligence (138 citations). Eric Neumann has collaborated with scholars based in United States, Netherlands and Germany. Frequent co-authors include Jeffrey C. Hall, Dennis Quan, Linda M. Hall, Lee Ann Smith, Alexandre A. Peixoto, Iván Herman, Tonya Hongsermeier, Susie Stephens, Bruce J. Aronow and Ranga Chandra Gudivada. Their work appears in journals such as OMICS A Journal of Integrative Biology, Biological Cybernetics, Journal of Web Semantics, Journal of Insect Behavior and BMC Bioinformatics.

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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