Moa Fransson

775 citations
12 papers · 627 · h-index 10

Impact in

  • Immunology top 10%
    • Immune Cell Function and Interaction
    • T-cell and B-cell Immunology
    • Immunotherapy and Immune Responses
  • Oncology top 10%
    • CAR-T cell therapy research

Papers in

Moa Fransson

12 papers receiving 622 citations

Peers

Moa Fransson
Comparison fields: 5 of 62
  • Immunology 327
  • Oncology 254
  • Developmental Neuroscience 25
  • Genetics 47
  • Neurology 34
Replace Maria Ravanini with:
Maria Ravanini Italy
Vadim Y. Taraban United Kingdom
Sarah Wilkinson United Kingdom
J. Shetye Sweden
Theresa Lopez United States
Navid Redjal United States
Yuedi Wang China
Gillian A. Kingsbury United States
Yasuyoshi Miyao Japan
Nicole A. Belmar United States
Moa Fransson relative to Maria Ravanini Italy Maria Ravanini's profile →
Citations per field
00.5×3.6×
Maria Ravanini · 1×
Citations per year

Countries citing papers authored by Moa Fransson

Since Specialization
Citations

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

Fields of papers citing papers by Moa Fransson

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

12 of 12 papers shown
#Work
1 2012298
2 201084
3 200543
4 200835
5 201434
6 201333
7 201431
8 201027
9 200918
10 201516
11
Finding Patterns in Vehicle Diagnostic Trouble Codes : A data mining study applying associative classification
20156
12 20202

About Moa Fransson

Moa Fransson is a scholar working on Immunology, Pathology and Forensic Medicine, Oncology, Surgery and Molecular Biology, having authored 12 papers that have together received 627 indexed citations. Recurring topics across this work include Immunotherapy and Immune Responses (6 papers), T-cell and B-cell Immunology (3 papers), Multiple Sclerosis Research Studies (3 papers), CAR-T cell therapy research (2 papers), Advanced Clustering Algorithms Research (1 paper), Data Mining Algorithms and Applications (1 paper), Rough Sets and Fuzzy Logic (1 paper) and RNA Interference and Gene Delivery (1 paper). The work is most often cited by research in Immunology (327 citations), Oncology (254 citations), Developmental Neuroscience (25 citations), Genetics (47 citations) and Neurology (34 citations). Moa Fransson has collaborated with scholars based in Sweden, Germany and United Kingdom. Frequent co-authors include Angelica Loskog, Joachim Burman, Peetra U. Magnusson, Elena Piras, Robert A. Harris, Eva B. Brittebo, Magnus Essand, Berith Nilsson, Binfeng Lu and Thomas H. Tötterman. Their work appears in journals such as Immunology, Clinical Cancer Research, Journal of Neuroimmunology, Journal of Immunotherapy and Journal of Neuroinflammation.

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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