Cells in a tissue compound communicate through proteins, which are secreted by secretory cells and detected through receptors on the receipient cell. Immune cells communicate non-stop with nearly all cells of the human body. Cells within the tumor stroma communicate with the actual tumor cells and thereby influence their growth, their potential to devleop metastasis and also their therapy resistence. From the view point of a system biologist, these paracrine signals all resemble connections between intracellular networks. Within our BioSysNet project we are trying to computationally simulate the "language" of these cellular networks. In the long term, this knowledge should help to discover therapeutic alterations of the intercellular proteom in order to lower the therapy resistence of individual tumors. 

Benedict Anchang
Inka Appel
Peter Butzhammer
Julia C. Engelmann
Daniela Herold
Christian Hundsrucker
Philipp Knollmüller
Christian Kohler
Claudio Lottaz
Matthias Maneck
Katharina Meyer
Mohammad Javad Sadeh
Rainer Spang (head)
Tully Yates

Hannus M, Beitzinger M, Engelmann JC, Weickert MT, Spang R, Hannus S, Meister G (2014). siPools: highly complex but accurately defined siRNA pools eliminate off-target effects. Nucleic Acids Res 42(12):8049-61.

Holler E, Butzhammer P, Schmid K, Hundsrucker C, Koestler J, Peter K, Zhu W, Sporrer D, Hehlgans T, Kreutz M, Holler B, Wolff D, Edinger M, Andreesen R, Levine JE, Ferrara JL, Gessner A, Spang R, Oefner PJ (2014). Metagenomic analysis of the stool microbiome in patients receiving allogeneic stem cell transplantation: loss of diversity is associated with use of systemic antibiotics and more pronounced in gastrointestinal graft-versus-host disease. Biol Blood Marrow Transplant 20(5):640-5. 

Engelmann JC, Spang R A Least Angle Regression Model for the Prediction of Canonical and Non-Canonical miRNA-mRNA Interactions. PLoS One. 2012;7(7):e40634. 2012 Jul 17

Maneck M, Schrader A, Kube D, Spang R. Genomic data integration using guided clustering. Bioinformatics 2011 27(16):2231-8

Appel IJ, Gronwald W, Spang R. Estimating classification probabilities in high-dimensional diagnostic studies. Bioinformatics 2011 27(18):2563-70.

Odoardi F, Sie C, Streyl K, Ulaganathan V, Schläger C, Lodygin D,

Heckelsmiller K, Nietfeld W, Ellwart J, Klinkert W, Lottaz C, Spang R, Lehrach H, Vingron M. Wekerle H. Flügel-Koch C. Flügel A. T cells become licensed in the lung to enter the central nervous system. Nature, 2012 488(7413):675–679

VerMilyea MD, Maneck M, Yoshida N, Blochberger I, Suzuki E, Suzuki T, Spang R, Klein CA, Perry AC. Transcriptome asymmetry within mouse zygotes but not between early embryonic sister blastomeres. EMBO J. 2011 30(9):1841-51

Anchang B, Sadeh MJ, Jacob J, Vlad MO, Oefner PJ, Spang R, Modelling the temporal interplay of molecular signalling and gene expression using dynamical nested effects models  PNAS 2009 106(16):6447-52

Bentink S, Wessendorf S, Schwaenen C, Rosolowski M, Klapper W, Rosenwald A, Ott G, Banham AH, Berger H, Feller AC, Hansmann ML, Hasenclever D, Hummel M, Lenze D, Möller P, Stuerzenhofecker B, Loeffler M, Trümper L, Stein H,  Siebert R, Spang R, Pathway activation patterns in diffuse large B-cell lymphomas, Leukemia 2008 22(9):1746-54

Kostka D, Spang R., Microarray Based Diagnosis Profits from Better Documentation of Gene Expression Signatures. PLoS Computational Biology 2008 4(2):e22

Markowetz F, Kostka D, Troyanskaja O, Spang R, Nested Effects Models for High-Dimensional Phenotyping. Bioinformatics 2007 23(13):i305-12. (ISMB 2007)

Hummel, Bentink, Berger, Klapper, Wessendorf, Barth, Bernd, Cogliatti, Dierlamm, Feller, Hansmann, Haralambieva, Harder, Hasenclever, Kühn, Lenze, Lichter, Martin-Subero, Möller, Müller-Hermelink, Ott, Parwaresch, Pott, Rosenwald, Rosolowski, Schwaenen, Stürzenhofecker, Szcepanowski, Trautmann, Wacker, Spang, Löffler, Trümper, Stein, Siebert A Biological Definition of Burkitt Lymphoma Derived From Transcriptional and Genomic Profiling.  New England Journal of Medicine 354(23), 2419-30, 2006