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Science 308 (5721): 523-529

Copyright © 2005 by the American Association for the Advancement of Science

Causal Protein-Signaling Networks Derived from Multiparameter Single-Cell Data

Karen Sachs,1* Omar Perez,2* Dana Pe'er,3* Douglas A. Lauffenburger,1{dagger} Garry P. Nolan2{dagger}

Abstract: Machine learning was applied for the automated derivation of causal influences in cellular signaling networks. This derivation relied on the simultaneous measurement of multiple phosphorylated protein and phospholipid components in thousands of individual primary human immune system cells. Perturbing these cells with molecular interventions drove the ordering of connections between pathway components, wherein Bayesian network computational methods automatically elucidated most of the traditionally reported signaling relationships and predicted novel interpathway network causalities, which we verified experimentally. Reconstruction of network models from physiologically relevant primary single cells might be applied to understanding native-state tissue signaling biology, complex drug actions, and dysfunctional signaling in diseased cells.

1 Biological Engineering Division, Massachusetts Institute of Technology (MIT), Cambridge, MA 02139, USA.
2 Stanford University School of Medicine, The Baxter Laboratory of Genetic Pharmacology, Department of Microbiology and Immunology, Stanford, CA 94305, USA.
3 Harvard Medical School, Department of Genetics, Boston, MA 02115, USA.

* These authors contributed equally to this work.

{dagger} To whom correspondence should be addressed. E-mail: lauffen{at} (D.A.L.); gnolan{at} (G.P.N.)

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   Abstract »    Full Text »    PDF »
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   Abstract »    Full Text »    PDF »
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   Abstract »    Full Text »    PDF »
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   Abstract »    Full Text »    PDF »
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   Abstract »    Full Text »    PDF »
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   Abstract »    Full Text »    PDF »
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   Abstract »    Full Text »    PDF »
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   Abstract »    Full Text »    PDF »
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Biometrika 98, 807-820
   Abstract »    PDF »
Introduction to Network Analysis in Systems Biology.
A. Ma'ayan (2011)
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   Abstract »    Full Text »    PDF »
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   Abstract »    Full Text »    PDF »
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   Abstract »    Full Text »    PDF »
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   Abstract »    Full Text »    PDF »
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   Abstract »    Full Text »    PDF »
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   Abstract »    Full Text »    PDF »
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   Abstract »    Full Text »    PDF »
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   Abstract »    Full Text »    PDF »
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   Abstract »    Full Text »    PDF »
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   Abstract »    Full Text »    PDF »
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   Abstract »    Full Text »    PDF »
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   Abstract »    Full Text »    PDF »
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   Abstract »    Full Text »    PDF »
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   Abstract »    Full Text »    PDF »
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   Abstract »    Full Text »    PDF »
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   Abstract »    Full Text »    PDF »
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Science 325, 429-432
   Abstract »    Full Text »    PDF »
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R. Cheong, C. J. Wang, and A. Levchenko (2009)
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   Abstract »    Full Text »    PDF »
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C. Huttenhower, E. M. Haley, M. A. Hibbs, V. Dumeaux, D. R. Barrett, H. A. Coller, and O. G. Troyanskaya (2009)
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   Abstract »    Full Text »    PDF »
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B. Anchang, M. J. Sadeh, J. Jacob, A. Tresch, M. O. Vlad, P. J. Oefner, and R. Spang (2009)
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   Abstract »    Full Text »    PDF »
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D. R. Bickel, Z. Montazeri, P.-C. Hsieh, M. Beatty, S. J. Lawit, and N. J. Bate (2009)
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   Abstract »    Full Text »    PDF »
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   Abstract »    Full Text »    PDF »
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A. Ma'ayan (2009)
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   Abstract »    Full Text »    PDF »
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S. X. Lu, O. Alpdogan, J. Lin, R. Balderas, R. Campos-Gonzalez, X. Wang, G.-J. Gao, D. Suh, C. King, M. Chow, et al. (2008)
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   Abstract »    Full Text »    PDF »
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   Abstract »    Full Text »    PDF »
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   Abstract »    Full Text »    PDF »
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   Abstract »    Full Text »    PDF »
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   Abstract »    Full Text »    PDF »
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S. Mukherjee and T. P. Speed (2008)
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   Abstract »    Full Text »    PDF »
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   Abstract »    Full Text »    PDF »
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   Abstract »    Full Text »    PDF »
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   Full Text »    PDF »
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B. S. Braun and K. Shannon (2008)
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   Abstract »    Full Text »    PDF »
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P. M. O'Callaghan and D. C. James (2008)
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   Abstract »    Full Text »    PDF »
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R. Zeiser, D. B. Leveson-Gower, E. A. Zambricki, N. Kambham, A. Beilhack, J. Loh, J.-Z. Hou, and R. S. Negrin (2008)
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   Abstract »    Full Text »    PDF »
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R. Zeiser, S. Youssef, J. Baker, N. Kambham, L. Steinman, and R. S. Negrin (2007)
Blood 110, 4588-4598
   Abstract »    Full Text »    PDF »
Coevolutionary networks of splicing cis-regulatory elements.
X. Xiao, Z. Wang, M. Jang, and C. B. Burge (2007)
PNAS 104, 18583-18588
   Abstract »    Full Text »    PDF »
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M. R. Chandok, F. I. Okoye, M. P. Ndejembi, and D. L. Farber (2007)
J. Immunol. 179, 3689-3698
   Abstract »    Full Text »    PDF »
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B. S. Srinivasan, N. H. Shah, J. A. Flannick, E. Abeliuk, A. F. Novak, and S. Batzoglou (2007)
Brief Bioinform 8, 318-332
   Abstract »    Full Text »    PDF »
Neurotrophic factors switch between two signaling pathways that trigger axonal growth.
M. Paveliev, M. Lume, A. Velthut, M. Phillips, U. Arumae, and M. Saarma (2007)
J. Cell Sci. 120, 2507-2516
   Abstract »    Full Text »    PDF »
The flow of cytometry into systems biology.
J. P. Nolan and L. Yang (2007)
Briefings in Functional Genomics
   Abstract »    Full Text »    PDF »
Nested effects models for high-dimensional phenotyping screens.
F. Markowetz, D. Kostka, O. G. Troyanskaya, and R. Spang (2007)
Bioinformatics 23, i305-i312
   Abstract »    Full Text »    PDF »
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Y. Pan, T. Durfee, J. Bockhorst, and M. Craven (2007)
Bioinformatics 23, i367-i376
   Abstract »    Full Text »    PDF »
Computational modeling of Caenorhabditis elegans vulval induction.
X. Sun and P. Hong (2007)
Bioinformatics 23, i499-i507
   Abstract »    Full Text »    PDF »
K-RasG12D expression induces hyperproliferation and aberrant signaling in primary hematopoietic stem/progenitor cells.
M. E. M. Van Meter, E. Diaz-Flores, J. A. Archard, E. Passegue, J. M. Irish, N. Kotecha, G. P. Nolan, K. Shannon, and B. S. Braun (2007)
Blood 109, 3945-3952
   Abstract »    Full Text »    PDF »
Bayesian methods in bioinformatics and computational systems biology.
D. J. Wilkinson (2007)
Brief Bioinform
   Abstract »    Full Text »    PDF »
Phosphoprotein Pathway Mapping: Akt/Mammalian Target of Rapamycin Activation Is Negatively Associated with Childhood Rhabdomyosarcoma Survival.
E. F. Petricoin III, V. Espina, R. P. Araujo, B. Midura, C. Yeung, X. Wan, G. S. Eichler, D. J. Johann Jr., S. Qualman, M. Tsokos, et al. (2007)
Cancer Res. 67, 3431-3440
   Abstract »    Full Text »    PDF »
Predicting protein-protein interactions based only on sequences information.
J. Shen, J. Zhang, X. Luo, W. Zhu, K. Yu, K. Chen, Y. Li, and H. Jiang (2007)
PNAS 104, 4337-4341
   Abstract »    Full Text »    PDF »
Altered activation of AKT is required for the suppressive function of human CD4+CD25+ T regulatory cells.
N. K. Crellin, R. V. Garcia, and M. K. Levings (2007)
Blood 109, 2014-2022
   Abstract »    Full Text »    PDF »
Thematic review series: Systems Biology Approaches to Metabolic and Cardiovascular Disorders. Multi-organ whole-genome measurements and reverse engineering to uncover gene networks underlying complex traits.
J. Tegner, J. Skogsberg, and J. Bjorkegren (2007)
J. Lipid Res. 48, 267-277
   Abstract »    Full Text »    PDF »
Dynamic modelling and analysis of biochemical networks: mechanism-based models and model-based experiments.
N. A.W. van Riel (2006)
Brief Bioinform 7, 364-374
   Abstract »    Full Text »    PDF »
SEBINI: Software Environment for BIological Network Inference.
R. C. Taylor, A. Shah, C. Treatman, and M. Blevins (2006)
Bioinformatics 22, 2706-2708
   Abstract »    Full Text »    PDF »
Isoelectric focusing technology quantifies protein signaling in 25 cells.
R. A. O'Neill, A. Bhamidipati, X. Bi, D. Deb-Basu, L. Cahill, J. Ferrante, E. Gentalen, M. Glazer, J. Gossett, K. Hacker, et al. (2006)
PNAS 103, 16153-16158
   Abstract »    Full Text »    PDF »
Delayed development and lifespan extension as features of metabolic lifestyle alteration in C. elegans under dietary restriction.
N. J. Szewczyk, I. A. Udranszky, E. Kozak, J. Sunga, S. K. Kim, L. A. Jacobson, and C. A. Conley (2006)
J. Exp. Biol. 209, 4129-4139
   Abstract »    Full Text »    PDF »
Comparative evaluation of reverse engineering gene regulatory networks with relevance networks, graphical gaussian models and bayesian networks.
A. V. Werhli, M. Grzegorczyk, and D. Husmeier (2006)
Bioinformatics 22, 2523-2531
   Abstract »    Full Text »    PDF »
Electrophysiological and gene expression profiling of neuronal cell types in mammalian neocortex.
K. Yano, T. Subkhankulova, F. J. Livesey, and H. P. C. Robinson (2006)
J. Physiol. 575, 361-365
   Abstract »    Full Text »    PDF »
The fluorescent toolbox for assessing protein location and function..
B. N. G. Giepmans, S. R. Adams, M. H. Ellisman, and R. Y. Tsien (2006)
Science 312, 217-224
   Abstract »    Full Text »    PDF »
Gene network inference from incomplete expression data: transcriptional control of hematopoietic commitment.
K. Missal, M. A. Cross, and D. Drasdo (2006)
Bioinformatics 22, 731-738
   Abstract »    Full Text »    PDF »

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