U E Schaible

861 citations
11 papers · 725 · h-index 9

Impact in

Papers in

    • Vector-borne infectious diseases 11
    • Leptospirosis research and findings 2
    • Viral Infections and Vectors 7
    • Dermatological diseases and infestations 3

U E Schaible

10 papers receiving 690 citations

Peers

U E Schaible
Comparison fields: 5 of 48
  • Parasitology 673
  • Infectious Diseases 530
  • Insect Science 147
  • Ecology, Evolution, Behavior and Systematics 163
  • Immunology 175
Replace Kathleen D. Moody with:
Kathleen D. Moody United States
S E Moter Germany
Nancy Marcantonio United States
Dieter Rössler Germany
Quan Lin United States
Mary M. Petzke United States
Toru Kariu United States
Anneke Oei Netherlands
B. Rutti Switzerland
Amy Bowman United States
U E Schaible relative to Kathleen D. Moody United States Kathleen D. Moody's profile →
Citations per field
00.5×1.5×
Kathleen D. Moody · 1×
Citations per year

Countries citing papers authored by U E Schaible

Since Specialization
Citations

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

Fields of papers citing papers by U E Schaible

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by U E Schaible. 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 U E Schaible. The network helps show where U E Schaible may publish in the future.

Co-authors

The 22 scholars most cited alongside U E Schaible, 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 U E Schaible Line = papers co-authored together U E Schaible links everyone, so they are left out of the graph.

All Works

11 of 11 papers shown
#Work
1 1990234
2 199393
3 199483
4 199061
5 199157
6 199453
7 199353
8 198953
9
A 14,000 MW lipoprotein and a glycolipid-like structure of Borrelia burgdorferi induce proliferation and immunoglobulin production in mouse B cells at high frequencies.
199437
10 20081
11 20080

About U E Schaible

U E Schaible is a scholar working on Parasitology, Infectious Diseases, Public Health, Environmental and Occupational Health, Immunology and Ecology, Evolution, Behavior and Systematics, having authored 11 papers that have together received 725 indexed citations. Recurring topics across this work include Vector-borne infectious diseases (11 papers), Viral Infections and Vectors (7 papers), Dermatological diseases and infestations (3 papers), Leptospirosis research and findings (2 papers), Toxin Mechanisms and Immunotoxins (2 papers), Zoonotic diseases and public health (2 papers), Mosquito-borne diseases and control (2 papers) and Insect and Pesticide Research (1 paper). The work is most often cited by research in Parasitology (673 citations), Infectious Diseases (530 citations), Insect Science (147 citations), Ecology, Evolution, Behavior and Systematics (163 citations) and Immunology (175 citations). U E Schaible has collaborated with scholars based in Germany, Switzerland and Czechia. Frequent co-authors include Markus M. Simon, Manuel Modolell, C Muşeţeanu, Michael D. Kramer, Lise Gern, Klaus Eichmann, Michael D. Kramer, R Wallich, Reinhard Wallich and S E Moter. Their work appears in journals such as Infection and Immunity, Immunology Letters, Immunobiology, The Journal of Infectious Diseases and Proceedings of the National Academy of Sciences.

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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