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.
Papers
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Journal ArticleDOI
Synergy of interleukin 10 and toll-like receptor 9 signalling in B cell proliferation: Implications for lymphoma pathogenesis.
Maren Feist,Judith Kemper,Franziska Taruttis,Thorsten Rehberg,Julia C. Engelmann,Wolfram Gronwald,Michael Hummel,Rainer Spang,Dieter Kube +8 more
TL;DR: The observed synergism of IL10R and TLR9 signalling was able to induce proliferation in a comparable way as aberrant MYC and might play a role in B cell homeostasis or transformation.
Journal ArticleDOI
Refining pathways: A model comparison approach
Giusi Moffa,Gerrit Erdmann,Oksana Voloshanenko,Christian Hundsrucker,Mohammad Javad Sadeh,Michael Boutros,Rainer Spang +6 more
TL;DR: This paper adapts the framework of nested effect models to focus on a specific aspect of activated Wnt signalling in HCT116 colon cancer cells: Does the activation of Wnt target genes depend on the secretion of WNT ligands or do mutations in the signalling molecule β-catenin make this activation independent from them?
Journal ArticleDOI
Loss-Function Learning for Digital Tissue Deconvolution.
Franziska Görtler,Marian Schön,Jakob Simeth,Stefan Solbrig,Tilo Wettig,Peter J. Oefner,Rainer Spang,Michael Altenbuchinger +7 more
TL;DR: This study uses training data to learn the loss function ℒ along with the composition c and quantifies large cell fractions as accurately as existing methods and significantly improves the detection of small cell populations and the distinction of similar cell types.
Book ChapterDOI
Loss-function learning for digital tissue deconvolution
Franziska Görtler,Stefan Solbrig,Tilo Wettig,Peter J. Oefner,Rainer Spang,Michael Altenbuchinger +5 more
TL;DR: Digital tissue deconvolution (DTD) addresses the following inverse problem: Given the expression profile y of a tissue, what is the cellular composition c of that tissue?
Journal ArticleDOI
Round-robin test for the cell-of-origin classification of diffuse large B-cell lymphoma-a feasibility study using full slide staining.
Sarah Reinke,Julia Richter,Falko Fend,Alfred C. Feller,Martin-Leo Hansmann,Katrin Hüttl,Ilske Oschlies,German Ott,Peter Möller,Andreas Rosenwald,Harald Stein,Michael Altenbuchinger,Rainer Spang,Wolfram Klapper +13 more
TL;DR: This study describes the first round-robin test for COO subtyping in DLBCL using IHC and demonstrates that COO classification using the Hans classifier yields consistent results among experienced hematopathologists, even when variable staining protocols are used.