R
Rainer Spang
Researcher at University of Regensburg
Publications - 171
Citations - 11726
Rainer Spang is an academic researcher from University of Regensburg. The author has contributed to research in topics: Gene expression profiling & Diffuse large B-cell lymphoma. The author has an hindex of 48, co-authored 166 publications receiving 10400 citations. Previous affiliations of Rainer Spang include Max Planck Society & Duke University.
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Advanced patient age at diagnosis of diffuse large B-cell lymphoma is associated with molecular characteristics including ABC-subtype and high expression of MYC
Ulrike Paul,Julia Richter,Christiane Stuhlmann-Laiesz,Markus Kreuz,Inga Nagel,Heike Horn,Annette M. Staiger,Sietse M. Aukema,Michael Hummel,German Ott,Rainer Spang,Andreas Rosenwald,Alfred C. Feller,Sergio Cogliatti,Harald Stein,Martin-Leo Hansmann,Peter Møller,Monika Szczepanowski,Birgit Burkhardt,Michael Pfreundschuh,Norbert Schmitz,Markus Loeffler,Lorenz Trümper,Reiner Siebert,Wolfram Klapper +24 more
TL;DR: The data indicate that biological features of DLBCL and FL grade 3B are associated with increasing age among adult patients and the prevalence of the ABC/non-GCB-subtype in elderly patients suggests that therapies targeting this molecular subtype should be specifically explored in this subgroup.
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Response-Predictive Gene Expression Profiling of Glioma Progenitor Cells In Vitro
Sylvia Moeckel,Katharina Meyer,Petra Leukel,Fabian Heudorfer,Corinna Seliger,Christina Stangl,Ulrich Bogdahn,Martin Proescholdt,Alexander Brawanski,Arabel Vollmann-Zwerenz,Markus J. Riemenschneider,Anja-Katrin Bosserhoff,Rainer Spang,Peter Hau +13 more
TL;DR: Serious serum-free short-term treated in vitro cell cultures were used to predict treatment response in vitro with tyrosine kinase inhibitor Sunitinib and revealed additional predictive information in comparison to the evaluation of classical signaling analysis.
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Considering unknown unknowns: reconstruction of nonconfoundable causal relations in biological networks.
TL;DR: It is shown that in the presence of missing observations or hidden factors a reliable reconstruction of the full network is not feasible, but certain characteristics of signaling networks like the existence of cross-talk between certain branches of the network can be inferred in a nonconfoundable way.
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Detecting common gene expression patterns in multiple cancer outcome entities.
TL;DR: In an analysis of four prognostic cancer studies, involving breast cancer, leukemia, and mesothelioma, the method is able to identify 42 genes that show consistent up- or down-regulation in patients with a poor disease outcome.
Evaluating the effect of perturbations in reconstructing network topologies
Florian Markowetz,Rainer Spang +1 more
TL;DR: A systematic investigation of the effects of small sample size and the stability of the solution of the κ-network, a small Bayesian network model in which a parameter κ controls the conditional probability distributions of the nodes.