Amelie Schäfer

603 total citations
10 papers, 349 citations indexed

About

Amelie Schäfer is a scholar working on Physiology, Molecular Biology and Cognitive Neuroscience. According to data from OpenAlex, Amelie Schäfer has authored 10 papers receiving a total of 349 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Physiology, 3 papers in Molecular Biology and 3 papers in Cognitive Neuroscience. Recurrent topics in Amelie Schäfer's work include Alzheimer's disease research and treatments (7 papers), Prion Diseases and Protein Misfolding (3 papers) and Functional Brain Connectivity Studies (3 papers). Amelie Schäfer is often cited by papers focused on Alzheimer's disease research and treatments (7 papers), Prion Diseases and Protein Misfolding (3 papers) and Functional Brain Connectivity Studies (3 papers). Amelie Schäfer collaborates with scholars based in United States, Germany and United Kingdom. Amelie Schäfer's co-authors include Ellen Kuhl, Alain Goriely, Kevin Linka, Mathias Jucker, George Em Karniadakis, Zongren Zou, Xuhui Meng, Johannes Weickenmeier, Elizabeth C. Mormino and Mathias Peirlinck and has published in prestigious journals such as SHILAP Revista de lepidopterología, Scientific Reports and Computer Methods in Applied Mechanics and Engineering.

In The Last Decade

Amelie Schäfer

10 papers receiving 344 citations

Peers

Amelie Schäfer

PHYSI

MB

CN

SNP

RNMI

Yaoyu Zhang China

Marianna La Rocca Italy

Gemma Lancaster United Kingdom

Gustavo Sato dos Santos United Kingdom

Ernesto Zacur United Kingdom

Ary L. Goldberger United States

Juan Ruiz de Miras Spain

Anna Ghazaryan United States

Matías Nicolás Bossa Spain

Carson Ingo United States

Yaoyu Zhang China

Amelie Schäfer

23 ×0.2

PHYSI

28 ×0.3

MB

103 ×1.3

CN

117 ×1.6

SNP

78 ×1.2

RNMI

Citations per year, relative to Amelie Schäfer Amelie Schäfer (= 1×) peers Yaoyu Zhang

Countries citing papers authored by Amelie Schäfer

Since Specialization

Citations

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

Fields of papers citing papers by Amelie Schäfer

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Amelie Schäfer

This figure shows the co-authorship network connecting the top 25 collaborators of Amelie Schäfer. A scholar is included among the top collaborators of Amelie Schäfer based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Amelie Schäfer. Amelie Schäfer is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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10 of 10 papers shown

1.

Linka, Kevin, Amelie Schäfer, Xuhui Meng, et al.. (2022). Bayesian Physics Informed Neural Networks for real-world nonlinear dynamical systems. Computer Methods in Applied Mechanics and Engineering. 402. 115346–115346. 104 indexed citations

2.

Schäfer, Amelie, et al.. (2022). Correlating tau pathology to brain atrophy using a physics-based Bayesian model. Engineering With Computers. 38(5). 3867–3877. 12 indexed citations

3.

Schäfer, Amelie, et al.. (2021). Predicting brain atrophy from tau pathology: a summary of clinical findings and their translation into personalized models. SHILAP Revista de lepidopterología. 2. 100039–100039. 16 indexed citations

4.

Linka, Kevin, et al.. (2021). Effects of B.1.1.7 and B.1.351 on COVID-19 Dynamics: A Campus Reopening Study. Archives of Computational Methods in Engineering. 28(6). 4225–4236. 2 indexed citations

5.

Schäfer, Amelie, et al.. (2021). Bayesian Physics-Based Modeling of Tau Propagation in Alzheimer's Disease. Frontiers in Physiology. 12. 702975–702975. 21 indexed citations

6.

Schäfer, Amelie, Elizabeth C. Mormino, & Ellen Kuhl. (2020). Network Diffusion Modeling Explains Longitudinal Tau PET Data. Frontiers in Neuroscience. 14. 566876–566876. 26 indexed citations

7.

Schäfer, Amelie, Johannes Weickenmeier, & Ellen Kuhl. (2019). The interplay of biochemical and biomechanical degeneration in Alzheimer’s disease. Computer Methods in Applied Mechanics and Engineering. 352. 369–388. 29 indexed citations

8.

Schäfer, Amelie, et al.. (2019). Prion-like spreading of Alzheimer’s disease within the brain’s connectome. Journal of The Royal Society Interface. 16(159). 20190356–20190356. 88 indexed citations

9.

Schäfer, Amelie, et al.. (2019). Spatially-extended nucleation-aggregation-fragmentation models for the dynamics of prion-like neurodegenerative protein-spreading in the brain and its connectome. Journal of Theoretical Biology. 486. 110102–110102. 41 indexed citations

10.

Linka, Kevin, Amelie Schäfer, Markus Hillgärtner, et al.. (2019). Towards Patient-Specific Computational Modelling of Articular Cartilage on the Basis of Advanced Multiparametric MRI Techniques. Scientific Reports. 9(1). 7172–7172. 10 indexed citations

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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