Nicholas Schwab

4.2k total citations
67 papers, 2.4k citations indexed

About

Nicholas Schwab is a scholar working on Immunology, Oncology and Pathology and Forensic Medicine. According to data from OpenAlex, Nicholas Schwab has authored 67 papers receiving a total of 2.4k indexed citations (citations by other indexed papers that have themselves been cited), including 35 papers in Immunology, 20 papers in Oncology and 19 papers in Pathology and Forensic Medicine. Recurrent topics in Nicholas Schwab's work include Multiple Sclerosis Research Studies (18 papers), Neuroinflammation and Neurodegeneration Mechanisms (18 papers) and T-cell and B-cell Immunology (17 papers). Nicholas Schwab is often cited by papers focused on Multiple Sclerosis Research Studies (18 papers), Neuroinflammation and Neurodegeneration Mechanisms (18 papers) and T-cell and B-cell Immunology (17 papers). Nicholas Schwab collaborates with scholars based in Germany, United States and Slovakia. Nicholas Schwab's co-authors include Heinz Wiendl, Tilman Schneider‐Hohendorf, Catharina C. Groß, Luisa Klotz, Sven G. Meuth, Johanna Breuer, Klaus Dornmair, Tanja Kuhlmann, Anne Waschbisch and Alla L. Zozulya and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Clinical Investigation and Nature Communications.

In The Last Decade

Nicholas Schwab

64 papers receiving 2.3k citations

Peers

Nicholas Schwab
Barbara Tucky United States
Tilman Schneider‐Hohendorf Germany
R. M. Ransohoff United States
Gregory F. Wu United States
Kerstin Göbel Germany
Masaaki Niino Japan
Klaus Lehmann‐Horn Germany
Luca Massacesi Italy
Elisabetta Capello Italy
William Sheremata United States
Barbara Tucky United States
Nicholas Schwab
Citations per year, relative to Nicholas Schwab Nicholas Schwab (= 1×) peers Barbara Tucky

Countries citing papers authored by Nicholas Schwab

Since Specialization
Citations

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

Fields of papers citing papers by Nicholas Schwab

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Nicholas Schwab

This figure shows the co-authorship network connecting the top 25 collaborators of Nicholas Schwab. A scholar is included among the top collaborators of Nicholas 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 Nicholas Schwab. Nicholas Schwab 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.
Cantoni, Claudia, Margarita Smirnov, Maria Firulyova, et al.. (2025). A single-cell compendium of human cerebrospinal fluid identifies disease-associated immune cell populations. Journal of Clinical Investigation. 135(1). 3 indexed citations
2.
Schneider‐Hohendorf, Tilman, Andreas Schulte‐Mecklenbeck, Catarina Rapôso, et al.. (2025). B- and T cell receptor sequencing elucidates characteristics of lymphocyte depletion by ocrelizumab. iScience. 28(8). 113068–113068.
3.
Schwab, Nicholas, Yvonne Pfeifer, Anika Wahl, et al.. (2025). Fatal Pneumocephalus Caused by Hypervirulent Klebsiella pneumoniae, Germany. Emerging infectious diseases. 31(10). 2008–2012.
4.
Corrie, Brian, Scott Christley, Christian E. Busse, et al.. (2022). Data Sharing and Reuse: A Method by the AIRR Community. Methods in molecular biology. 2453. 447–476. 3 indexed citations
5.
Arnaout, Ramy, et al.. (2021). The Future of Blood Testing Is the Immunome. Frontiers in Immunology. 12. 626793–626793. 33 indexed citations
6.
Zondler, Lisa, Sebastian Herich, Tilman Schneider‐Hohendorf, et al.. (2020). MCAM/CD146 Signaling via PLCγ1 Leads to Activation of β1-Integrins in Memory T-Cells Resulting in Increased Brain Infiltration. Frontiers in Immunology. 11. 599936–599936. 6 indexed citations
7.
Hörste, Gerd Meyer zu, Catharina C. Groß, Luisa Klotz, Nicholas Schwab, & Heinz Wiendl. (2020). Next-Generation Neuroimmunology: New Technologies to Understand Central Nervous System Autoimmunity. Trends in Immunology. 41(4). 341–354. 15 indexed citations
8.
Breuer, Judith, et al.. (2018). Does the environment influence multiple sclerosis pathogenesis via UVB light and/or induction of vitamin D?. Journal of Neuroimmunology. 329. 1–8. 17 indexed citations
9.
10.
Schwarte, Kathrin, Manuela Cerina, Alexander M. Herrmann, et al.. (2017). Chemokine CCL17 is expressed by dendritic cells in the CNS during experimental autoimmune encephalomyelitis and promotes pathogenesis of disease. Brain Behavior and Immunity. 66. 382–393. 38 indexed citations
11.
Tischner, Denise, Harmandeep Kaur, Jorge Carvalho, et al.. (2017). Single-cell profiling reveals GPCR heterogeneity and functional patterning during neuroinflammation. JCI Insight. 2(15). 22 indexed citations
12.
Herold, Martin, Johanna Breuer, Stephanie Hucke, et al.. (2017). Liver X receptor activation promotes differentiation of regulatory T cells. PLoS ONE. 12(9). e0184985–e0184985. 42 indexed citations
13.
Schulte‐Mecklenbeck, Andreas, Urvashi Bhatia, Tilman Schneider‐Hohendorf, et al.. (2017). Analysis of Lymphocyte Extravasation Using an <em>In Vitro</em> Model of the Human Blood-brain Barrier. Journal of Visualized Experiments. 4 indexed citations
14.
Klotz, Luisa, Maria Eveslage, Michael Deppe, et al.. (2015). Assessment of immune functions and MRI disease activity in relapsing-remitting multiple sclerosis patients switching from natalizumab to fingolimod (ToFingo-Successor). BMC Neurology. 15(1). 96–96. 6 indexed citations
15.
Kroner, Antje, Nicholas Schwab, Chi Wang Ip, et al.. (2009). Accelerated Course of Experimental Autoimmune Encephalomyelitis in PD-1-Deficient Central Nervous System Myelin Mutants. American Journal Of Pathology. 174(6). 2290–2299. 34 indexed citations
16.
Waschbisch, Anne, Sven G. Meuth, Alexander M. Herrmann, et al.. (2009). Intercellular exchanges of membrane fragments (trogocytosis) between human muscle cells and immune cells: A potential mechanism for the modulation of muscular immune responses. Journal of Neuroimmunology. 209(1-2). 131–138. 19 indexed citations
17.
Kroner, Antje, Nicholas Schwab, Chi Wang Ip, et al.. (2009). PD-1 Regulates Neural Damage in Oligodendroglia-Induced Inflammation. PLoS ONE. 4(2). e4405–e4405. 18 indexed citations
18.
Schwab, Nicholas, Christian G. Bien, Anne Waschbisch, et al.. (2009). CD8+ T-cell clones dominate brain infiltrates in Rasmussen encephalitis and persist in the periphery. Brain. 132(5). 1236–1246. 113 indexed citations
19.
Kroner, Antje, Nicholas Schwab, Chi Wang Ip, et al.. (2008). The co-inhibitory molecule PD-1 modulates disease severity in a model for an inherited, demyelinating neuropathy. Neurobiology of Disease. 33(1). 96–103. 11 indexed citations
20.
Schwab, Nicholas, et al.. (1993). Effects of somatostatin and captopril on glomerular prostaglandin E2 production in normal and diabetic rats. Prostaglandins. 46(1). 61–73. 5 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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