Roland Martin
University of Zurich
377 Papers
4.4K Citations
Roland Martin is an academic researcher from University of Zurich. The author has contributed to research in topics: Multiple sclerosis & T cell. The author has an hindex of 86, co-authored 367 publications. Previous affiliations of Roland Martin include National Institutes of Health & Catalan Institution for Research and Advanced Studies.
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Papers
Mechanisms of immunomodulation by glatiramer acetate.
Bruno Gran,L. R. Tranquill,M. Chen,Bibiana Bielekova,W. Zhou,Suhayl Dhib-Jalbut,Roland Martin +6 more
TL;DR: This study confirms a preferential inhibitory effect of GA on autoreactive TCC and demonstrates further that GA induces T cells that crossreact with myelin proteins that play an important role in mediating the effect of the drug in vivo.
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Retinal damage in multiple sclerosis disease subtypes measured by high-resolution optical coherence tomography.
Timm Oberwahrenbrock,Sven Schippling,Marius Ringelstein,Falko Kaufhold,Hanna Zimmermann,Nazmiye Keser,Kim Lea Young,Jens Harmel,Hans-Peter Hartung,Roland Martin,Friedemann Paul,Orhan Aktas,Alexander U. Brandt +12 more
TL;DR: Analysis of this large-scale cross-sectional dataset of MS patients studied with spectral-domain OCT confirmed and allows to generalize previous findings, carving out distinct patterns in different MS subtypes.
Targeting Dipeptidyl Peptidase IV (CD26) Suppresses Autoimmune Encephalomyelitis and Up-Regulates TGF-β1 Secretion In Vivo
Andreas Steinbrecher,Dirk Reinhold,Laura Quigley,Ameer M Gado,Nancy Tresser,Leonid Izikson,Ilona Born,Jürgen Faust,Klaus Neubert,Roland Martin,Siegfried Ansorge,Stefan Brocke +11 more
TL;DR: The data suggest that DP IV inhibition represents a novel and specific therapeutic approach protecting from autoimmune disease by a mechanism that includes an active TGF-β1-mediated antiinflammatory effect at the site of pathology.
Application of support vector machines for T-cell epitopes prediction
TL;DR: For the first time, it is demonstrated that SVMs can be trained on relatively small data sets to provide prediction more accurate than those based on previously published methods or on MHC binding.