Sergio E. Baranzini

29.8k total citations · 5 hit papers
166 papers, 13.0k citations indexed

About

Sergio E. Baranzini is a scholar working on Molecular Biology, Pathology and Forensic Medicine and Immunology. According to data from OpenAlex, Sergio E. Baranzini has authored 166 papers receiving a total of 13.0k indexed citations (citations by other indexed papers that have themselves been cited), including 89 papers in Molecular Biology, 50 papers in Pathology and Forensic Medicine and 36 papers in Immunology. Recurrent topics in Sergio E. Baranzini's work include Multiple Sclerosis Research Studies (49 papers), Bioinformatics and Genomic Networks (20 papers) and Cytokine Signaling Pathways and Interactions (19 papers). Sergio E. Baranzini is often cited by papers focused on Multiple Sclerosis Research Studies (49 papers), Bioinformatics and Genomic Networks (20 papers) and Cytokine Signaling Pathways and Interactions (19 papers). Sergio E. Baranzini collaborates with scholars based in United States, Canada and United Kingdom. Sergio E. Baranzini's co-authors include Jorge R. Oksenberg, Stephen L. Hauser, Bernhard Hemmer, Alan J. Thompson, Jeroen J.G. Geurts, Olga Ciccarelli, Lawrence Steinman, David H. Rowitch, Raymond A. Sobel and Stephen P.J. Fancy and has published in prestigious journals such as Nature, Science and Proceedings of the National Academy of Sciences.

In The Last Decade

Sergio E. Baranzini

160 papers receiving 12.8k citations

Hit Papers

Multiple sclerosis 2001 2026 2009 2017 2018 2017 2001 2002 2017 400 800 1.2k
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Multiple sclerosis
    2018 1.2k citations Sergio E. Baranzini et al. profile →
  2. Gut bacteria from multiple sclerosis patients modulate human T cells and exacerbate symptoms in mouse models
    2017 730 citations Egle Cekanaviciute, Bryan B. Yoo et al. Proceedings of the National Academy of Sciences profile →
  3. The Influence of the Proinflammatory Cytokine, Osteopontin, on Autoimmune Demyelinating Disease
    2001 704 citations Sergio E. Baranzini, Jorge R. Oksenberg et al. profile →
  4. THE INFLUENCE OF THE PROINFLAMMATORY CYTOKINE, OSTEOPONTIN, ON AUTOIMMUNE DEMYELINATING DISEASE
    2002 662 citations Sergio E. Baranzini, Jorge R. Oksenberg et al. profile →
  5. Gut microbiota from multiple sclerosis patients enables spontaneous autoimmune encephalomyelitis in mice
    2017 650 citations Kerstin Berer, Lisa Ann Gerdes et al. Proceedings of the National Academy of Sciences profile →

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Sergio E. Baranzini 5.5k 4.5k 3.1k 1.7k 1.6k 166 13.0k
Scott S. Zamvil 3.4k 0.6× 5.1k 1.1× 8.0k 2.5× 1.7k 1.0× 2.1k 1.3× 191 15.4k
Frauke Zipp 3.2k 0.6× 4.7k 1.0× 3.6k 1.2× 1.1k 0.7× 3.3k 2.1× 308 13.6k
Michael K. Racke 3.2k 0.6× 5.2k 1.1× 6.7k 2.1× 1.4k 0.8× 1.5k 1.0× 180 13.2k
Jorge R. Oksenberg 4.3k 0.8× 6.3k 1.4× 8.0k 2.5× 2.9k 1.7× 1.2k 0.7× 244 17.6k
Sven G. Meuth 4.1k 0.7× 3.1k 0.7× 2.7k 0.8× 774 0.4× 2.6k 1.7× 561 14.0k
Krzysztof Selmaj 4.5k 0.8× 9.5k 2.1× 5.4k 1.7× 2.6k 1.5× 2.3k 1.5× 338 17.7k
Alexandre Prat 4.6k 0.8× 3.7k 0.8× 5.1k 1.6× 760 0.4× 5.9k 3.7× 209 16.2k
Francisco J. Quintana 6.1k 1.1× 1.9k 0.4× 9.3k 2.9× 732 0.4× 2.9k 1.9× 199 20.2k
Bruce Cree 3.2k 0.6× 8.3k 1.8× 2.7k 0.9× 2.1k 1.2× 1.2k 0.8× 279 13.0k
Peter Rieckmann 2.2k 0.4× 6.8k 1.5× 3.1k 1.0× 1.8k 1.0× 1.3k 0.8× 266 13.1k

Countries citing papers authored by Sergio E. Baranzini

Since Specialization
Citations

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

Fields of papers citing papers by Sergio E. Baranzini

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Sergio E. Baranzini. 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 Sergio E. Baranzini. The network helps show where Sergio E. Baranzini may publish in the future.

Co-authorship network of co-authors of Sergio E. Baranzini

This figure shows the co-authorship network connecting the top 25 collaborators of Sergio E. Baranzini. A scholar is included among the top collaborators of Sergio E. Baranzini 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 Sergio E. Baranzini. Sergio E. Baranzini 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.
Yoon, Hongsup, Lisa Ann Gerdes, Florian Beigel, et al.. (2025). Multiple sclerosis and gut microbiota: Lachnospiraceae from the ileum of MS twins trigger MS-like disease in germfree transgenic mice—An unbiased functional study. Proceedings of the National Academy of Sciences. 122(18). e2419689122–e2419689122. 2 indexed citations
2.
Patel, Lucas, Yoshihiko Tomofuji, Antonio González, et al.. (2025). Incomplete human reference genomes can drive false sex biases and expose patient-identifying information in metagenomic data. Nature Communications. 16(1). 825–825. 5 indexed citations
3.
Soman, Karthik, Peter W. Rose, John H. Morris, et al.. (2024). Biomedical knowledge graph-optimized prompt generation for large language models. Bioinformatics. 40(9). 30 indexed citations
4.
Shams, Hengameh, Alessandro Didonna, Sergio E. Baranzini, et al.. (2023). Integration of epigenetic and genetic profiles identifies multiple sclerosis disease-critical cell types and genes. Communications Biology. 6(1). 342–342. 16 indexed citations
5.
Harroud, Adil, Ruth E. Mitchell, Tom G. Richardson, et al.. (2021). Childhood obesity and multiple sclerosis: A Mendelian randomization study. Multiple Sclerosis Journal. 27(14). 2150–2158. 33 indexed citations
6.
Nelson, Charlotte, Amber M. Paul, Ryan T. Scott, et al.. (2021). Knowledge Network Embedding of Transcriptomic Data from Spaceflown Mice Uncovers Signs and Symptoms Associated with Terrestrial Diseases. Life. 11(1). 42–42. 7 indexed citations
7.
Cruz-Herranz, Andrés, Frederike Cosima Oertel, Kicheol Kim, et al.. (2021). Distinctive waves of innate immune response in the retina in experimental autoimmune encephalomyelitis. JCI Insight. 6(11). 16 indexed citations
8.
Mycko, Marcin P. & Sergio E. Baranzini. (2020). microRNA and exosome profiling in multiple sclerosis. Multiple Sclerosis Journal. 26(5). 599–604. 60 indexed citations
9.
Sádaba, María C., Veit Rothhammer, Úrsula Muñoz, et al.. (2020). Serum antibodies to phosphatidylcholine in MS. Neurology Neuroimmunology & Neuroinflammation. 7(4). 17 indexed citations
10.
Harroud, Adil, J. Brent Richards, & Sergio E. Baranzini. (2020). Mendelian randomization study shows no causal effects of serum urate levels on the risk of MS. Neurology Neuroimmunology & Neuroinflammation. 8(1). 7 indexed citations
11.
Nelson, Charlotte, Atul J. Butte, & Sergio E. Baranzini. (2019). Integrating biomedical research and electronic health records to create knowledge-based biologically meaningful machine-readable embeddings. Nature Communications. 10(1). 3045–3045. 41 indexed citations
12.
Niu, Jianqin, Hui‐Hsin Tsai, Kimberly K. Hoi, et al.. (2019). Aberrant oligodendroglial–vascular interactions disrupt the blood–brain barrier, triggering CNS inflammation. Nature Neuroscience. 22(5). 709–718. 171 indexed citations
13.
Cekanaviciute, Egle, Anne‐Katrin Pröbstel, Tessel F. Runia, et al.. (2018). Multiple Sclerosis-Associated Changes in the Composition and Immune Functions of Spore-Forming Bacteria. mSystems. 3(6). 61 indexed citations
14.
Berer, Kerstin, Lisa Ann Gerdes, Egle Cekanaviciute, et al.. (2017). Gut microbiota from multiple sclerosis patients enables spontaneous autoimmune encephalomyelitis in mice. Proceedings of the National Academy of Sciences. 114(40). 10719–10724. 650 indexed citations breakdown →
15.
Cekanaviciute, Egle, Bryan B. Yoo, Tessel F. Runia, et al.. (2017). Gut bacteria from multiple sclerosis patients modulate human T cells and exacerbate symptoms in mouse models. Proceedings of the National Academy of Sciences. 114(40). 10713–10718. 730 indexed citations breakdown →
16.
Baranzini, Sergio E. & Jorge R. Oksenberg. (2017). The Genetics of Multiple Sclerosis: From 0 to 200 in 50 Years. Trends in Genetics. 33(12). 960–970. 148 indexed citations
17.
Fewings, Nicole, Prudence N. Gatt, Fiona C. McKay, et al.. (2017). The autoimmune risk gene ZMIZ1 is a vitamin D responsive marker of a molecular phenotype of multiple sclerosis. Journal of Autoimmunity. 78. 57–69. 23 indexed citations
18.
Matsushita, Takuya, Lohith Madireddy, Till Sprenger, et al.. (2015). Genetic associations with brain cortical thickness in multiple sclerosis. Genes Brain & Behavior. 14(2). 217–227. 23 indexed citations
19.
Hallett, Michael, Jack P. Antel, Amit Bar‐Or, et al.. (2014). Naive CD4 T-cell activation identifies MS patients having rapid transition to progressive MS. Neurology. 82(8). 681–690. 22 indexed citations
20.
Okuda, Darin T., Ellen M. Mowry, A. Beheshtian, et al.. (2008). Incidental MRI anomalies suggestive of multiple sclerosis. Neurology. 72(9). 800–805. 392 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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