Margit Pacher

814 citations
7 papers · 695 · h-index 7

Impact in

    • Protein Kinase Regulation and GTPase Signaling
    • Melanoma and MAPK Pathways
    • Protein Tyrosine Phosphatases
    • Ubiquitin and proteasome pathways
    • 14-3-3 protein interactions

Papers in

    • 14-3-3 protein interactions 2
    • Protein Kinase Regulation and GTPase Signaling 2
    • Protein Tyrosine Phosphatases 2
    • Photosynthetic Processes and Mechanisms 1
    • Gene expression and cancer classification 1
    • Growth Hormone and Insulin-like Growth Factors 2

Margit Pacher

7 papers receiving 690 citations

Peers

Margit Pacher
Comparison fields: 5 of 78
  • Cancer Research 108
  • Molecular Biology 473
  • Oncology 147
  • Aging 9
  • Cell Biology 68
Replace Iris Eisenmann-Tappe with:
Iris Eisenmann-Tappe Germany
Lora W. Forman United States
Zeng Quan Yang United States
Nilotpal Roy United States
Crystal M. Weyman United States
Francisco E. Gago Argentina
Miia M. Rytinki Finland
M E Cornet Spain
Eeva Sommer United Kingdom
Binoj C. Nair United States
Margit Pacher relative to Iris Eisenmann-Tappe Germany Iris Eisenmann-Tappe's profile →
Citations per field
00.5×12×
Iris Eisenmann-Tappe · 1×
Citations per year

Countries citing papers authored by Margit Pacher

Since Specialization
Citations

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

Fields of papers citing papers by Margit Pacher

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

7 of 7 papers shown
#Work
1 2004203
2 2000191
3 200299
4 200584
5 200660
6 200433
7 200125

About Margit Pacher

Margit Pacher is a scholar working on Molecular Biology, Endocrinology, Diabetes and Metabolism, Ecology, Evolution, Behavior and Systematics, Oncology and Genetics, having authored 7 papers that have together received 695 indexed citations. Recurring topics across this work include 14-3-3 protein interactions (2 papers), Protein Kinase Regulation and GTPase Signaling (2 papers), Protein Tyrosine Phosphatases (2 papers), Growth Hormone and Insulin-like Growth Factors (2 papers), Photosynthetic Processes and Mechanisms (1 paper), Biocrusts and Microbial Ecology (1 paper), Digestive system and related health (1 paper) and Gene expression and cancer classification (1 paper). The work is most often cited by research in Cancer Research (108 citations), Molecular Biology (473 citations), Oncology (147 citations), Aging (9 citations) and Cell Biology (68 citations). Margit Pacher has collaborated with scholars based in Austria, Germany and China. Frequent co-authors include Klaus Podar, Manuela Baccarini, Martin Schreiber, Dietmar Abraham, Markus Kubicek, Christian Stratowa, Wolfgang Sommergruber, E. Kubista, Stephen M. Dilworth and Walter Kölch. Their work appears in journals such as Clinical Cancer Research, Journal of Biological Chemistry, Carcinogenesis, Journal of Bacteriology and Cancer Research.

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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