Manuela Neumann

2.0k total citations
22 papers, 1.4k citations indexed

About

Manuela Neumann is a scholar working on Molecular Biology, Plant Science and Neurology. According to data from OpenAlex, Manuela Neumann has authored 22 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Molecular Biology, 9 papers in Plant Science and 4 papers in Neurology. Recurrent topics in Manuela Neumann's work include Prion Diseases and Protein Misfolding (9 papers), Plant Molecular Biology Research (5 papers) and Neurological diseases and metabolism (4 papers). Manuela Neumann is often cited by papers focused on Prion Diseases and Protein Misfolding (9 papers), Plant Molecular Biology Research (5 papers) and Neurological diseases and metabolism (4 papers). Manuela Neumann collaborates with scholars based in Germany, Sweden and China. Manuela Neumann's co-authors include H. A. Kretzschmar, Markus Schmid, Walter Schulz‐Schaeffer, Lukas Cepek, Markus Otto, S. Poser, Petra Steinacker, Jens Wiltfang, Silvio Collani and Levi Yant and has published in prestigious journals such as Nature Communications, PLoS ONE and The Plant Cell.

In The Last Decade

Manuela Neumann

22 papers receiving 1.4k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Manuela Neumann Germany 17 1.0k 442 264 240 198 22 1.4k
Madalena Martins Portugal 15 587 0.6× 401 0.9× 41 0.2× 96 0.4× 74 0.4× 22 1.1k
Lisa Henderson United States 15 613 0.6× 241 0.5× 159 0.6× 119 0.5× 148 0.7× 25 1.3k
Sebastian Boland United States 17 458 0.5× 105 0.2× 88 0.3× 256 1.1× 91 0.5× 18 1.0k
Anna Drews United Kingdom 15 229 0.2× 68 0.2× 117 0.4× 206 0.9× 87 0.4× 27 795
Lewis Evans United Kingdom 14 587 0.6× 37 0.1× 141 0.5× 425 1.8× 77 0.4× 17 1.1k
Kenji Uéda Japan 13 469 0.5× 235 0.5× 131 0.5× 209 0.9× 380 1.9× 17 1.0k
Harry C. Meeker United States 22 1.2k 1.1× 26 0.1× 522 2.0× 345 1.4× 74 0.4× 51 1.6k
Ruqiang Xu United States 23 841 0.8× 517 1.2× 149 0.6× 62 0.3× 15 0.1× 41 1.4k
Sabine Martin Germany 17 824 0.8× 220 0.5× 51 0.2× 36 0.1× 53 0.3× 28 1.2k
Zeyni Mansuroglu France 12 427 0.4× 59 0.1× 109 0.4× 399 1.7× 74 0.4× 14 1.0k

Countries citing papers authored by Manuela Neumann

Since Specialization
Citations

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

Fields of papers citing papers by Manuela Neumann

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Manuela Neumann

This figure shows the co-authorship network connecting the top 25 collaborators of Manuela Neumann. A scholar is included among the top collaborators of Manuela Neumann 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 Manuela Neumann. Manuela Neumann is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Karasov, Talia L., et al.. (2024). Continental-scale associations of Arabidopsis thaliana phyllosphere members with host genotype and drought. Nature Microbiology. 9(10). 2748–2758. 4 indexed citations
2.
Ashkenazy, Haim, et al.. (2021). Commensal Pseudomonas protect Arabidopsis thaliana from a coexisting pathogen via multiple lineage-dependent mechanisms. The ISME Journal. 16(5). 1235–1244. 19 indexed citations
3.
Goretti, Daniela, et al.. (2020). A gibberellin methyltransferase modulates the timing of floral transition at the Arabidopsis shoot meristem. Physiologia Plantarum. 170(4). 474–487. 4 indexed citations
4.
Neumann, Manuela, et al.. (2019). CRISPR-based tools for targeted transcriptional and epigenetic regulation in plants. PLoS ONE. 14(9). e0222778–e0222778. 74 indexed citations
5.
You, Yuan, et al.. (2019). Phloem Companion Cell-Specific Transcriptomic and Epigenomic Analyses Identify MRF1, a Regulator of Flowering. The Plant Cell. 31(2). 325–345. 29 indexed citations
6.
Collani, Silvio, Manuela Neumann, Levi Yant, & Markus Schmid. (2019). FT Modulates Genome-Wide DNA-Binding of the bZIP Transcription Factor FD. PLANT PHYSIOLOGY. 180(1). 367–380. 127 indexed citations
7.
Karasov, Talia L., Juliana Almario, Wei Ding, et al.. (2018). Arabidopsis thaliana and Pseudomonas Pathogens Exhibit Stable Associations over Evolutionary Timescales. Cell Host & Microbe. 24(1). 168–179.e4. 105 indexed citations
8.
Weng, Mao‐Lun, Claude Becker, Julia Hildebrandt, et al.. (2018). Fine-Grained Analysis of Spontaneous Mutation Spectrum and Frequency in Arabidopsis thaliana. Genetics. 211(2). 703–714. 81 indexed citations
9.
You, Yuan, Aneta Sawikowska, Manuela Neumann, et al.. (2017). Temporal dynamics of gene expression and histone marks at the Arabidopsis shoot meristem during flowering. Nature Communications. 8(1). 15120–15120. 74 indexed citations
10.
Lövblad, Karl‐Olof, et al.. (2012). Creutzfeldt-Jakob Disease Revealed by a Logopenic Variant of Primary Progressive Aphasia. European Neurology. 67(6). 360–362. 9 indexed citations
11.
Bender, Andreas, Kim J. Krishnan, Gabriele Rieder, et al.. (2008). Dopaminergic midbrain neurons are the prime target for mitochondrial DNA deletions. Journal of Neurology. 255(8). 1231–1235. 70 indexed citations
12.
Gillardon, Frank, Alexander Kloß, Matthias Berg, et al.. (2007). The 20S proteasome isolated from Alzheimer’s disease brain shows post‐translational modifications but unchanged proteolytic activity. Journal of Neurochemistry. 101(6). 1483–1490. 36 indexed citations
13.
Roeber, Sigrun, Bjarne Krebs, Manuela Neumann, et al.. (2005). Creutzfeldt-Jakob disease in a patient with an R208H mutation of the prion protein gene (PRNP) and a 17-kDa prion protein fragment. Acta Neuropathologica. 109(4). 443–448. 21 indexed citations
14.
Windl, Otto, Malte Buchholz, Andrea Neubauer, et al.. (2005). Breaking an Absolute Species Barrier: Transgenic Mice Expressing the Mink PrP Gene Are Susceptible to Transmissible Mink Encephalopathy. Journal of Virology. 79(23). 14971–14975. 14 indexed citations
15.
Xiang, Wei, Otto Windl, Ingo M. Westner, et al.. (2005). Cerebral gene expression profiles in sporadic Creutzfeldt–Jakob disease. Annals of Neurology. 58(2). 242–257. 51 indexed citations
16.
Otto, Markus, Jens Wiltfang, Lukas Cepek, et al.. (2002). Tau protein and 14-3-3 protein in the differential diagnosis of Creutzfeldt–Jakob disease. Neurology. 58(2). 192–197. 214 indexed citations
17.
18.
Neumann, Manuela, et al.. (1997). Comparison of methods for isolation of mycobacteria from water. Applied and Environmental Microbiology. 63(2). 547–552. 53 indexed citations
19.
Proske, Daniela, Manuela Neumann, Martin H. Groschup, et al.. (1997). RNA aptamers specifically interact with the prion protein PrP. Journal of Virology. 71(11). 8790–8797. 174 indexed citations
20.
Kretzschmar, H. A., Manuela Neumann, G. Riethmüller, & Stanley B. Prusiner. (1992). Molecular cloning of a mink prion protein gene. Journal of General Virology. 73(10). 2757–2761. 13 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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