Ulrike D. Epple

701 citations
9 papers · 519 · h-index 7

Impact in

    • Cellular transport and secretion
    • Endoplasmic Reticulum Stress and Disease
    • Autophagy in Disease and Therapy

Papers in

    • Autophagy in Disease and Therapy 5
    • Endoplasmic Reticulum Stress and Disease 5
    • Cellular transport and secretion 2

Ulrike D. Epple

8 papers receiving 518 citations

Peers

Ulrike D. Epple
Comparison fields: 5 of 49
  • Cell Biology 299
  • Epidemiology 391
  • Physiology 56
  • Aging 10
  • Parasitology 36
Replace Machiko Sakoh‐Nakatogawa with:
Machiko Sakoh‐Nakatogawa Japan
Eri Hirata Japan
Jemma L. Webber United States
Chika Kondo Japan
Ingrid Bhatia Kiššová Slovakia
Wakana Adachi Japan
Evelyn Welter Germany
Norito Tamura Japan
Javier H. Hervás Spain
Daniel Bernklau Austria
Ulrike D. Epple relative to Machiko Sakoh‐Nakatogawa Japan Machiko Sakoh‐Nakatogawa's profile →
Citations per field
00.5×1.7×
Machiko Sakoh‐Nakatogawa · 1×
Citations per year

Countries citing papers authored by Ulrike D. Epple

Since Specialization
Citations

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

Fields of papers citing papers by Ulrike D. Epple

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ulrike D. Epple. 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 Ulrike D. Epple. The network helps show where Ulrike D. Epple may publish in the future.

Co-authors

The 7 scholars most cited alongside Ulrike D. Epple, 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 Ulrike D. Epple Line = papers co-authored together Ulrike D. Epple links everyone, so they are left out of the graph.

All Works

9 of 9 papers shown
#Work
1 2001152
2 200192
3 200581
4 200356
5 200051
6 200450
7 200232
8 19865
9
Model reduction of the fixed-bed reactor
19820

About Ulrike D. Epple

Ulrike D. Epple is a scholar working on Epidemiology, Cell Biology, Molecular Biology, Control and Systems Engineering and Oncology, having authored 9 papers that have together received 519 indexed citations. Recurring topics across this work include Endoplasmic Reticulum Stress and Disease (5 papers), Autophagy in Disease and Therapy (5 papers), Peptidase Inhibition and Analysis (2 papers), Cellular transport and secretion (2 papers), Advanced Control Systems Optimization (2 papers), Ubiquitin and proteasome pathways (1 paper), Nonlinear Dynamics and Pattern Formation (1 paper) and Galectins and Cancer Biology (1 paper). The work is most often cited by research in Cell Biology (299 citations), Epidemiology (391 citations), Physiology (56 citations), Aging (10 citations) and Parasitology (36 citations). Ulrike D. Epple has collaborated with scholars based in Germany and United Kingdom. Frequent co-authors include Michael Thumm, Eeva‐Liisa Eskelinen, Henning Barth, Khuyen Meiling-Wesse, Christiane Voss, Roswitha Krick and Ernst Dieter Gilles. Their work appears in journals such as Journal of Biological Chemistry, FEBS Letters, Journal of Bacteriology, Journal of Cell Science and IFAC Proceedings Volumes.

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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