Ricarda Schwab

612 total citations
9 papers, 493 citations indexed

About

Ricarda Schwab is a scholar working on Molecular Biology, Oncology and Hematology. According to data from OpenAlex, Ricarda Schwab has authored 9 papers receiving a total of 493 indexed citations (citations by other indexed papers that have themselves been cited), including 3 papers in Molecular Biology, 3 papers in Oncology and 2 papers in Hematology. Recurrent topics in Ricarda Schwab's work include Peptidase Inhibition and Analysis (2 papers), Ubiquitin and proteasome pathways (2 papers) and Hormonal and reproductive studies (1 paper). Ricarda Schwab is often cited by papers focused on Peptidase Inhibition and Analysis (2 papers), Ubiquitin and proteasome pathways (2 papers) and Hormonal and reproductive studies (1 paper). Ricarda Schwab collaborates with scholars based in Germany, Switzerland and Australia. Ricarda Schwab's co-authors include Marcus Groettrup, E.M. Huber, Michael Basler, Wolfgang Heinemeyer, Christopher J. Kirk, M. Groll, Rolf Knoth, Christoph E. Hagemeyer, Ralf Peter Meyer and Silke Wiesner and has published in prestigious journals such as Cell, Nature Communications and Blood.

In The Last Decade

Ricarda Schwab

7 papers receiving 485 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Ricarda Schwab Germany	5	408	199	95	70	56	9	493
Chunwan Lu United States	11	391 1.0×	229 1.2×	114 1.2×	67 1.0×	79 1.4×	12	616
Leslie Douglas United States	11	476 1.2×	176 0.9×	114 1.2×	61 0.9×	31 0.6×	13	589
Kenna Shirasuna Japan	8	370 0.9×	206 1.0×	84 0.9×	41 0.6×	31 0.6×	12	515
Su‐Fern Tan United States	16	348 0.9×	101 0.5×	103 1.1×	51 0.7×	67 1.2×	29	477
Lilian Stärck Germany	8	337 0.8×	203 1.0×	177 1.9×	55 0.8×	33 0.6×	12	540
Sarah J. Turner United Kingdom	7	304 0.7×	144 0.7×	123 1.3×	19 0.3×	64 1.1×	12	529
Roger Mosselmans Belgium	11	161 0.4×	101 0.5×	82 0.9×	53 0.8×	48 0.9×	18	394
Guiqin Xu China	12	425 1.0×	188 0.9×	78 0.8×	59 0.8×	54 1.0×	21	559
Liqing Zhuang Australia	7	345 0.8×	200 1.0×	93 1.0×	49 0.7×	92 1.6×	7	535
Eun Ryoung Jang United States	16	506 1.2×	231 1.2×	68 0.7×	70 1.0×	47 0.8×	24	657

Countries citing papers authored by Ricarda Schwab

Since Specialization

Citations

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

Fields of papers citing papers by Ricarda Schwab

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ricarda Schwab

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

All Works

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9 of 9 papers shown

1.

Renders, Simon, Alexander Waclawiczek, Ricarda Schwab, et al.. (2025). Prospective clinical validation of MAC-scoring as an affordable, real-time biomarker for HMA/venetoclax response in AML. Blood. 146(Supplement 1). 3493–3493.

2.

Kriegsmann, Katharina, Calin Manta, Ricarda Schwab, et al.. (2022). Comparison of bone marrow and peripheral blood aberrant plasma cell assessment by NGF in patients with MM. Blood Advances. 7(3). 379–383.

3.

Aichem, Annette, Nicola Catone, Andrej Berg, et al.. (2018). The structure of the ubiquitin-like modifier FAT10 reveals an alternative targeting mechanism for proteasomal degradation. Nature Communications. 9(1). 3321–3321. 37 indexed citations

4.

Huber, E.M., Michael Basler, Ricarda Schwab, et al.. (2012). Immuno- and Constitutive Proteasome Crystal Structures Reveal Differences in Substrate and Inhibitor Specificity. Cell. 148(4). 727–738. 402 indexed citations

5.

Huber, E.M., Michael Basler, Ricarda Schwab, et al.. (2012). Constitutive and immunoproteasome crystal structures reveal differences in substrate and inhibitor specificity. Molecular Immunology. 51(1). 18–19. 1 indexed citations

6.

Meyer, Ralf Peter, et al.. (2010). Xenobiotics in the Limbic System—Affecting Brain's Network Function. Vitamins and hormones. 82. 87–106. 1 indexed citations

7.

Meyer, Ralf Peter, et al.. (2009). Concordant up‐regulation of cytochrome P450 Cyp3a11, testosterone oxidation and androgen receptor expression in mouse brain after xenobiotic treatment. Journal of Neurochemistry. 109(2). 670–681. 19 indexed citations

8.

Hagemeyer, Christoph E., et al.. (2009). 7-Benzyloxyresorufin-O-dealkylase activity as a marker for measuring cytochrome P450 CYP3A induction in mouse liver. Analytical Biochemistry. 398(1). 104–111. 24 indexed citations

9.

Schwab, Ricarda, M Sébald, & F. Kaudewitz. (1971). Influence of ethidium bromide on respiration in Schizosaccharomyces pombe. Molecular and General Genetics MGG. 110(4). 361–366. 9 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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