Emma Persson

666 citations
13 papers · 292 · h-index 9

Impact in

    • Immune Cell Function and Interaction
    • Immunotherapy and Immune Responses
    • T-cell and B-cell Immunology
    • Viral-associated cancers and disorders

Papers in

    • Bioinformatics and Genomic Networks 3
    • Machine Learning in Bioinformatics 2
    • Genomics and Phylogenetic Studies 2
    • Glycosylation and Glycoproteins Research 1
    • Gene expression and cancer classification 1
    • Stroke Rehabilitation and Recovery 2

Emma Persson

13 papers receiving 286 citations

Peers

Emma Persson
Comparison fields: 5 of 78
  • Immunology 93
  • Oncology 61
  • Industrial and Manufacturing Engineering 18
  • Pathology and Forensic Medicine 33
  • Molecular Biology 101
Replace Jialin Yao with:
Jialin Yao China
Boni Ding China
Zide Zhang China
Jingyi Tan China
Chi‐Ling Lin Taiwan
Sunil Kumar India
Valesca Anschau Brazil
Mamoru Nishimura Japan
Pranay Ramteke India
Kuai Liu China
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Citations per field
00.5×3.8×
Jialin Yao · 1×
Citations per year

Countries citing papers authored by Emma Persson

Since Specialization
Citations

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

Fields of papers citing papers by Emma Persson

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

13 of 13 papers shown
#Work
1 201183
2 200961
3 202134
4 201225
5 202220
6 202319
7 201918
8 202114
9 20248
10 20216
11
Microarrays based on affinity-tagged SCFV antibodies: Sensitive detection of analyte in complex proteomes
20052
12 20241
13
Investigating the Use of Machine Learning to Detect Unilateral Arm Weakness
20201

About Emma Persson

Emma Persson is a scholar working on Molecular Biology, Rehabilitation, Immunology, Pathology and Forensic Medicine and Neurology, having authored 13 papers that have together received 292 indexed citations. Recurring topics across this work include Bioinformatics and Genomic Networks (3 papers), Machine Learning in Bioinformatics (2 papers), Genomics and Phylogenetic Studies (2 papers), Stroke Rehabilitation and Recovery (2 papers), Immune Cell Function and Interaction (2 papers), Advanced Proteomics Techniques and Applications (1 paper), Glycosylation and Glycoproteins Research (1 paper) and Gene expression and cancer classification (1 paper). The work is most often cited by research in Immunology (93 citations), Oncology (61 citations), Industrial and Manufacturing Engineering (18 citations), Pathology and Forensic Medicine (33 citations) and Molecular Biology (101 citations). Emma Persson has collaborated with scholars based in Sweden, United States and Germany. Frequent co-authors include William W. Agace, Erik L. L. Sonnhammer, Hergen Spits, Noémi Nagy, Ferenc A. Scheeren, Dániel Salamon, George Klein, Lóránd Kis, Eva Klein and Dimitri Guala. Their work appears in journals such as Journal of Molecular Biology, Trends in Immunology, Waste Management, Nucleic Acids Research and Sensors.

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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