Cell Fates as High-Dimensional Attractor States of a Complex Gene Regulatory Network
Abstract
Cells in multicellular organisms switch between distinct cell fates, such as proliferation or differentiation into specialized cell types. Genome-wide gene regulatory networks govern this behavior. Theoretical studies of complex networks suggest that they can exhibit ordered (stable) dynamics, raising the possibility that cell fates may represent high-dimensional attractor states. We used gene expression profiling to show that trajectories of neutrophil differentiation converge to a common state from different directions of a 2773-dimensional gene expression state space, providing the first experimental evidence for a high-dimensional stable attractor that represents a distinct cellular phenotype.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The model of less mature cells maintaining looser chromatin can be represented by 'attractor states' within a genome-wide gene regulatory network.
“Theoretically, this model can be represented by “attractor states” within a genome-wide gene regulatory network (47).”
From Single-cell transcriptional diversity is a hallmark of developmental potential (2020) · cites this paper as [47]
Differentiating cells descend toward stable regions of the network (attractor states), characterized by restricted gene expression, whereas metastable cells broadly sample the network, maintaining higher differentiation potential.
“In this context, differentiating cells descend toward stable regions of the network (attractor states), characterized by restricted gene expression, whereas metastable cells broadly sample the network, maintaining higher differentiation potential (47).”
From Single-cell transcriptional diversity is a hallmark of developmental potential (2020) · cites this paper as [47]
Cites
Emergence of Scaling in Random Networks
Barabási, A.-L., & Albert, R. (1999) · Science · doi:10.1126/science.286.5439.509 · Cited by 36,135 · see citing works
Strogatz, S. H. (2001) · Nature · doi:10.1038/35065725 · Cited by 8,236 · see citing works
The Origins of Order: Self-Organization and Selection in Evolution
Kauffman, S. A. (1993) · doi:10.1093/oso/9780195079517.001.0001 · Cited by 7,855 · see citing works
Lethality and centrality in protein networks
Jeong, H., Mason, S., Barabási, A., & Oltvai, Z. (2001) · Nature · doi:10.1038/35075138 · Cited by 5,327 · see citing works
Metabolic stability and epigenesis in randomly constructed genetic nets
Kauffman, S. A. (1969) · Journal of Theoretical Biology · doi:10.1016/0022-5193(69)90015-0 · Cited by 4,871 · see citing works
Classes of small-world networks
Amaral, L. A. N., Scala, A., Barthélémy, M., & Stanley, H. E. (2000) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.200327197 · Cited by 3,051 · see citing works
Specificity and Stability in Topology of Protein Networks
Maslov, S., & Sneppen, K. (2002) · Science · doi:10.1126/science.1065103 · Cited by 3,051 · see citing works
Will a Large Complex System be Stable?
MAY, R. M. (1972) · Nature · doi:10.1038/238413a0 · Cited by 2,869 · see citing works
A Protein Interaction Map of Drosophila melanogaster
Giot, L., Bader, J. S., Brouwer, C., Chaudhuri, A., Kuang, B., Li, Y., Hao, Y. L., Ooi, C., Godwin, B., Vitols, E., et al. (2003) · Science · doi:10.1126/science.1090289 · Cited by 2,266 · see citing works
Induction of differentiation of the human promyelocytic leukemia cell line (HL-60) by retinoic acid
Breitman, T. R., Selonick, S. E., & Collins, S. J. (1980) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.77.5.2936 · Cited by 1,966 · see citing works
A Map of the Interactome Network of the Metazoan C. elegans
Li, S., Armstrong, C. M., Bertin, N., Ge, H., Milstein, S., Boxem, M., Vidalain, P., Han, J.-D. J., Chesneau, A., Hao, T., et al. (2004) · Science · doi:10.1126/science.1091403 · Cited by 1,628 · see citing works
Collins, S. J., Ruscetti, F. W., Gallagher, R. E., & Gallo, R. C. (1978) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.75.5.2458 · Cited by 1,594 · see citing works
MIPS: a database for genomes and protein sequences
Mewes, H. (2000) · Nucleic Acids Research · doi:10.1093/nar/28.1.37 · Cited by 1,276 · see citing works
Collins, S. (1987) · Blood · doi:10.1182/blood.v70.5.1233.1233 · Cited by 1,191 · see citing works
General Conclusions: Teleonomic Mechanisms in Cellular Metabolism, Growth, and DifferentiationPreprint
Monod, J., & Jacob, F. (1961) · Cold Spring Harbor Symposia on Quantitative Biology · doi:10.1101/sqb.1961.026.01.048 · Cited by 1,072 · see citing works
Multistability in the lactose utilization network of Escherichia coli
Ozbudak, E. M., Thattai, M., Lim, H. N., Shraiman, B. I., & van Oudenaarden, A. (2004) · Nature · doi:10.1038/nature02298 · Cited by 1,030 · see citing works
ENZYME INDUCTION AS AN ALL-OR-NONE PHENOMENON
Novick, A., & Weiner, M. (1957) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.43.7.553 · Cited by 891 · see citing works
MIPS: a database for genomes and protein sequences
Mewes, H. (2002) · Nucleic Acids Research · doi:10.1093/nar/30.1.31 · Cited by 784 · see citing works
A positive-feedback-based bistable ‘memory module’ that governs a cell fate decision.
Xiong, W., & Ferrell, J. E. (2003) · Nature · doi:10.1038/nature02089 · Cited by 741 · see citing works
Huang, S., & Ingber, D. E. (2000) · Experimental Cell Research · doi:10.1006/excr.2000.5044 · Cited by 606 · see citing works
Self-citationWaddington, C. H. (1956) · Routledge eBooks · doi:10.4324/9781315665405 · Cited by 468 · see citing works
Are randomly grown graphs really random?
Callaway, D. S., Hopcroft, J. E., Kleinberg, J. M., Newman, M. E. J., & Strogatz, S. H. (2001) · Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics · doi:10.1103/physreve.64.041902 · Cited by 451 · see citing works
A model of transcriptional regulatory networks based on biases in the observed regulation rules
Harris, S. E., Sawhill, B. K., Wuensche, A., & Kauffman, S. A. (2002) · Complexity · doi:10.1002/cplx.10022 · Cited by 277 · see citing works
Options available—from start to finish—for obtaining data from DNA microarrays II
Holloway, A. J., van Laar, R. K., Tothill, R. W., & Bowtell, D. D. L. (2002) · Nature Genetics · doi:10.1038/ng1030 · Cited by 250 · see citing works
A natural class of robust networks
Aldana, M., & Cluzel, P. (2003) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1536783100 · Cited by 250 · see citing works
Gene Expression Dynamics Inspector (GEDI): for integrative analysis of expression profiles
Eichler, G. S., Huang, S., & Ingber, D. E. (2003) · Bioinformatics · doi:10.1093/bioinformatics/btg307 · Cited by 176 · see citing works
Self-citationThe role of certain Post classes in Boolean network models of genetic networks
Ilya Shmulevich, C., Lähdesmäki, H. J., Dougherty, E. R., Astola, J. T., & Zhang, W. (2003) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1534782100 · Cited by 141 · see citing works
From topology to dynamics in biochemical networks
Fox, J. J., & Hill, C. C. (2001) · Chaos An Interdisciplinary Journal of Nonlinear Science · doi:10.1063/1.1414882 · Cited by 102 · see citing works
Response of complex networks to stimuli
Yaneer Bar-yam, A., & Epstein, I. R. (2004) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0400673101 · Cited by 100 · see citing works
Marcotte, E. M. (2001) · Nature Biotechnology · doi:10.1038/90222 · Cited by 66 · see citing works
Statistical Mechanics of Voting
MEYER, D. A., & Brown, T. A. (1998) · Physical Review Letters · doi:10.1103/physrevlett.81.1718 · Cited by 48 · see citing works
Mesostructure of polymer collapse and fractal smoothing
Crooks, G. E., Ostrovsky, B., & Bar‐Yam, Y. (1999) · Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics · doi:10.1103/physreve.60.4559 · Cited by 24 · see citing works
Self-citationStructural information content and Lyapunov exponent calculation in protein unfolding
Gerstman, B. S., & Garbourg, Y. (1998) · Journal of Polymer Science Part B Polymer Physics · doi:10.1002/(sici)1099-0488(19981115)36:15 · Cited by 20 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Single-cell transcriptional diversity is a hallmark of developmental potential
Gulati, G. S., Sikandar, S. S., Wesche, D. J., Manjunath, A., Bharadwaj, A., Berger, M. J., Ilagan, F., Kuo, A. H., Hsieh, R. W., Cai, S., et al. (2020) · Science · doi:10.1126/science.aax0249 · Cited by 1,571 · see citing works
Transcriptome-wide noise controls lineage choice in mammalian progenitor cells
Chang, H. H., Hemberg, M., Barahona, M., Ingber, D. E., & Huang, S. (2008) · Nature · doi:10.1038/nature06965 · Cited by 1,067 · see citing works
Self-citationPisarchik, A. N., & Feudel, U. (2014) · Physics Reports · doi:10.1016/j.physrep.2014.02.007 · Cited by 795 · see citing works
Bifurcation dynamics in lineage-commitment in bipotent progenitor cells
Huang, S., Guo, Y.-P., May, G., & Enver, T. (2007) · Developmental Biology · doi:10.1016/j.ydbio.2007.02.036 · Cited by 560 · see citing works
Self-citationHuang, S., Ernberg, I. T., & Kauffman, S. A. (2009) · Seminars in Cell and Developmental Biology · doi:10.1016/j.semcdb.2009.07.003 · Cited by 556 · see citing works
Self-citationColloquium : Criticality and dynamical scaling in living systems
Muñoz, M. A. (2018) · Reviews of Modern Physics · doi:10.1103/revmodphys.90.031001 · Cited by 527 · see citing works
Non-genetic heterogeneity of cells in development: more than just noise
Huang, S. (2009) · Development · doi:10.1242/dev.035139 · Cited by 482 · see citing works
Self-citationBrock, A., Chang, H. H., & Huang, S. (2009) · Nature Reviews Genetics · doi:10.1038/nrg2556 · Cited by 481 · see citing works
Self-citationTransition states and cell fate decisions in epigenetic landscapes
Moris, N., Pina, C., & Arias, A. M. (2016) · Nature Reviews Genetics · doi:10.1038/nrg.2016.98 · Cited by 438 · see citing works
Mapping transcriptomic vector fields of single cells
Qiu, X., Zhang, Y., Martin-Rufino, J. D., Weng, C., Hosseinzadeh, S., Yang, D., Pogson, A. N., Hein, M. Y., Min, K. H., Wang, L., et al. (2022) · Cell · doi:10.1016/j.cell.2021.12.045 · Cited by 436 · see citing works
Cell tension, matrix mechanics, and cancer development
Huang, S., & Ingber, D. E. (2005) · Cancer Cell · doi:10.1016/j.ccr.2005.08.009 · Cited by 426 · see citing works
Self-citationLevin, M. G. (2014) · Molecular Biology of the Cell · doi:10.1091/mbc.e13-12-0708 · Cited by 397 · see citing works
On Having No Head: Cognition throughout Biological Systems
Baluška, F., & Levin, M. G. (2016) · Frontiers in Psychology · doi:10.3389/fpsyg.2016.00902 · Cited by 383 · see citing works
Systems biology of stem cell fate and cellular reprogramming
MacArthur, B. D., Ma’ayan, A., & Lemischka, I. R. (2009) · Nature Reviews Molecular Cell Biology · doi:10.1038/nrm2766 · Cited by 359 · see citing works
Mechanical control of tissue morphogenesis during embryological development
Ingber, D. E. (2006) · The International Journal of Developmental Biology · doi:10.1387/ijdb.052044di · Cited by 352 · see citing works
Self-citationHuang, S. (2011) · BioEssays · doi:10.1002/bies.201100031 · Cited by 351 · see citing works
Self-citationCell Fate Decision as High-Dimensional Critical State Transition
Mojtahedi, M., Skupin, A., Zhou, J., Castaño, I. G., Leong-Quong, R. Y. Y., Chang, H. H., Trachana, K., Giuliani, A., & Huang, S. (2016) · PLoS Biology · doi:10.1371/journal.pbio.2000640 · Cited by 346 · see citing works
Self-citationStem Cell States, Fates, and the Rules of Attraction
Enver, T., Pera, M. F., Peterson, C., & Andrews, P. W. (2009) · Cell stem cell · doi:10.1016/j.stem.2009.04.011 · Cited by 319 · see citing works
Data based identification and prediction of nonlinear and complex dynamical systems
Wang, W.-X., Lai, Y.-C., & Grebogi, C. (2016) · Physics Reports · doi:10.1016/j.physrep.2016.06.004 · Cited by 317 · see citing works
Reprogramming cell fates: reconciling rarity with robustness
Huang, S. (2009) · BioEssays · doi:10.1002/bies.200800189 · Cited by 316 · see citing works
Self-citationCan cancer be reversed by engineering the tumor microenvironment?
Ingber, D. E. (2008) · Seminars in Cancer Biology · doi:10.1016/j.semcancer.2008.03.016 · Cited by 294 · see citing works
Self-citationNon-Darwinian dynamics in therapy-induced cancer drug resistance
Pisco, A. O., Brock, A., Zhou, J., Moor, A. E., Mojtahedi, M., Jackson, D. A., & Huang, S. (2013) · Nature Communications · doi:10.1038/ncomms3467 · Cited by 289 · see citing works
Self-citationThe Roots of Bioinformatics in Theoretical Biology
Hogeweg, P. (2011) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1002021 · Cited by 288 · see citing works
Robustness and evolvability in genetic regulatory networks
Aldana, M., Balleza, E., Kauffman, S. A., & Resendiz, O. (2006) · Journal of Theoretical Biology · doi:10.1016/j.jtbi.2006.10.027 · Cited by 270 · see citing works
Bifurcation analysis of single-cell gene expression data reveals epigenetic landscape
Marco, E., Karp, R. L., Guo, G., Robson, P., Hart, A. H., Trippa, L., & Yuan, G.-C. (2014) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1408993111 · Cited by 268 · see citing works
Adaptive Response of a Gene Network to Environmental Changes by Fitness-Induced Attractor Selection
Kashiwagi, A., Urabe, I., Kaneko, K., & Yomo, T. (2006) · PLoS ONE · doi:10.1371/journal.pone.0000049 · Cited by 267 · see citing works
The Potential Landscape of Genetic Circuits Imposes the Arrow of Time in Stem Cell Differentiation
Wang, J., Xu, L., Wang, E., & Huang, S. (2010) · Biophysical Journal · doi:10.1016/j.bpj.2010.03.058 · Cited by 239 · see citing works
Self-citationLevin, M. G. (2014) · The Journal of Physiology · doi:10.1113/jphysiol.2014.271940 · Cited by 237 · see citing works
Eukaryotic cells are dynamically ordered or critical but not chaotic
Shmulevich, I., Kauffman, S. A., & Aldana, M. (2005) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0506771102 · Cited by 229 · see citing works
Park, J., Jang, S., Lee, D., Lee, J.-H., Kang, U., Chang, H., Kim, H. J., Han, S.-H., Seo, J., Choi, M., et al. (2021) · Nature Communications · doi:10.1038/s41467-020-20440-5 · Cited by 224 · see citing works
A complex systems approach to aging biology
Cohen, A. A., Ferrucci, L., Fülöp, T., Gravel, D., Hao, N., Kriete, A., Levine, M. E., Lipsitz, L. A., Olde Rikkert, M. G. M., Rutenberg, A., et al. (2022) · Nature Aging · doi:10.1038/s43587-022-00252-6 · Cited by 221 · see citing works
Manu, Surkova, S. Y., Spirov, A. V., Gursky, V. V., Janssens, H., Kim, A.-R., Radulescu, O., Vanario‐Alonso, C. E., Sharp, D. H., Samsonova, M. G., et al. (2009) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1000303 · Cited by 211 · see citing works
Rescuing drug discovery: in vivo systems pathology and systems pharmacology
van der Greef, J., & McBurney, R. N. (2005) · Nature Reviews Drug Discovery · doi:10.1038/nrd1904 · Cited by 209 · see citing works
Specialization Can Drive the Evolution of Modularity
Espinosa‐Soto, C., & Wagner, A. (2010) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1000719 · Cited by 206 · see citing works
Extracellular matrix, mechanotransduction and structural hierarchies in heart tissue engineering
Parker, K. K., & Ingber, D. E. (2007) · Philosophical Transactions of the Royal Society B Biological Sciences · doi:10.1098/rstb.2007.2114 · Cited by 199 · see citing works
Self-citationIndividual Retinal Progenitor Cells Display Extensive Heterogeneity of Gene Expression
Trimarchi, J. M., Stadler, M. B., & Cepko, C. L. (2008) · PLoS ONE · doi:10.1371/journal.pone.0001588 · Cited by 194 · see citing works
A Dynamical-Systems View of Stem Cell Biology
Furusawa, C., & Kaneko, K. (2012) · Science · doi:10.1126/science.1224311 · Cited by 191 · see citing works
Diseases as network perturbations
del Sol, A., Balling, R., Hood, L., & Galas, D. J. (2010) · Current Opinion in Biotechnology · doi:10.1016/j.copbio.2010.07.010 · Cited by 184 · see citing works
Biophysical models of tumour growth
Tracqui, P. (2009) · Reports on Progress in Physics · doi:10.1088/0034-4885/72/5/056701 · Cited by 182 · see citing works
Understanding gene circuits at cell-fate branch points for rational cell reprogramming
Zhou, J., & Huang, S. (2010) · Trends in Genetics · doi:10.1016/j.tig.2010.11.002 · Cited by 174 · see citing works
Self-citationRare variants in neuronal excitability genes influence risk for bipolar disorder
Ament, S. A., Szelinger, S., Glusman, G., Ashworth, J. R., Hou, L., Akula, N., Shekhtman, T., Badner, J. A., Brunkow, M. E., Mauldin, D. E., et al. (2015) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1424958112 · Cited by 175 · see citing works
Cyclic strain induces dual-mode endothelial-mesenchymal transformation of the cardiac valve
Balachandran, K., Alford, P. W., Wylie‐Sears, J., Goss, J. A., Grosberg, A., Bischoff, J. E., Aikawa, E. R., Levine, R. A., & Parker, K. K. (2011) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1106954108 · Cited by 175 · see citing works
Understanding biological functions through molecular networks
Han, J. J. (2008) · Cell Research · doi:10.1038/cr.2008.16 · Cited by 171 · see citing works
Choi, M., Shi, J., Jung, S. H., Chen, X. X., & Cho, K. (2012) · Science Signaling · doi:10.1126/scisignal.2003363 · Cited by 170 · see citing works
Moes, M., Béchec, A. L., Crespo, I., Laurini, C., Halavatyi, A. A., Vetter, G., del Sol, A., & Friederich, E. (2012) · PLoS ONE · doi:10.1371/journal.pone.0035440 · Cited by 168 · see citing works
Inferring rules of lineage commitment in haematopoiesis
Pina, C., Fugazza, C., Tipping, A. J., Brown, J., Soneji, S., Teles, J., Peterson, C., & Enver, T. (2012) · Nature Cell Biology · doi:10.1038/ncb2442 · Cited by 162 · see citing works
Huang, S., & Ingber, D. E. (2007) · Breast Disease · doi:10.3233/bd-2007-26104 · Cited by 161 · see citing works
Self-citationMultistable and multistep dynamics in neutrophil differentiation
Chang, H. H., Oh, P., Ingber, D. E., & Huang, S. (2006) · BMC Cell Biology · doi:10.1186/1471-2121-7-11 · Cited by 161 · see citing works
Self-citationA map of gene expression in neutrophil-like cell lines
Rincón, E., Rocha-Gregg, B. L., & Collins, S. R. (2018) · BMC Genomics · doi:10.1186/s12864-018-4957-6 · Cited by 156 · see citing works
Cellular network entropy as the energy potential in Waddington's differentiation landscape
Banerji, C. R. S., Miranda-Saavedra, D., Simone Severini, B., Widschwendter, M., Enver, T., Zhou, J. X., & Teschendorff, A. E. (2013) · Scientific Reports · doi:10.1038/srep03039 · Cited by 155 · see citing works
Memory in Microbes: Quantifying History-Dependent Behavior in a Bacterium
Wolf, D. M., Fontaine, L., Bischofs, I., Price, G., Keasling, J. D., & Arkin, A. P. (2008) · PLoS ONE · doi:10.1371/journal.pone.0001700 · Cited by 143 · see citing works
Is Target-Based Drug Discovery Efficient? Discovery and “Off-Target” Mechanisms of All Drugs
Sadri, A. (2023) · Journal of Medicinal Chemistry · doi:10.1021/acs.jmedchem.2c01737 · Cited by 141 · see citing works
THE EVOLUTION OF PHENOTYPIC CORRELATIONS AND “DEVELOPMENTAL MEMORY”
Watson, R. A. R., Wagner, G. P., Pavličev, M., Weinreich, D. M., & Mills, R. (2013) · Evolution · doi:10.1111/evo.12337 · Cited by 138 · see citing works
Albert, R., & Thakar, J. (2014) · WIREs Systems Biology and Medicine · doi:10.1002/wsbm.1273 · Cited by 135 · see citing works
Floral Morphogenesis: Stochastic Explorations of a Gene Network Epigenetic Landscape
Alvarez-Buylla, E. R., Chaos, Á., Aldana, M., Benítez, M., Cortés-Poza, Y., Espinosa‐Soto, C., Hartasánchez, D. A., Lotto, R. B., Malkin, D., Santos, G. J. E., et al. (2008) · PLoS ONE · doi:10.1371/journal.pone.0003626 · Cited by 134 · see citing works
A geometrical approach to control and controllability of nonlinear dynamical networks
Wang, L.-Z., Su, R.-Q., Huang, Z., Wang, X., Wang, W.-X., Grebogi, C., & Lai, Y. (2016) · Nature Communications · doi:10.1038/ncomms11323 · Cited by 131 · see citing works
Network analyses in systems biology: new strategies for dealing with biological complexity
Green, S., Şerban, M., Scholl, R., Jones, N. J., Brigandt, I., & Bechtel, W. (2017) · Synthese · doi:10.1007/s11229-016-1307-6 · Cited by 131 · see citing works
Analysis of Time-Series Gene Expression Data: Methods, Challenges, and Opportunities
Androulakis, I. P., Yang, E., & Almon, R. R. (2007) · Annual Review of Biomedical Engineering · doi:10.1146/annurev.bioeng.9.060906.151904 · Cited by 130 · see citing works
Criticality Is an Emergent Property of Genetic Networks that Exhibit Evolvability
Torres-Sosa, C., Huang, S., & Aldana, M. (2012) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1002669 · Cited by 128 · see citing works
Self-citationAbsolute rate theories of epigenetic stability
Walczak, A. M., Onuchic, J. N., & Wolynes, P. G. (2005) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0509547102 · Cited by 127 · see citing works
Topography of epithelial–mesenchymal plasticity
Font-Clos, F., Zapperi, S., & Porta, C. A. M. L. (2018) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1722609115 · Cited by 125 · see citing works
Dynamics inside the cancer cell attractor reveal cell heterogeneity, limits of stability, and escape
Li, Q., Wennborg, A., Aurell, E. M., Dekel, E., Zou, J., Xu, Y., Huang, S., & Ernberg, I. T. (2016) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1519210113 · Cited by 121 · see citing works
Self-citationHuang, S. (2011) · Philosophical Transactions of the Royal Society B Biological Sciences · doi:10.1098/rstb.2011.0008 · Cited by 120 · see citing works
Self-citationII—James Woodward: Mechanistic Explanation: Its Scope and Limits
Woodward, J. (2013) · Aristotelian Society Supplementary Volume · doi:10.1111/j.1467-8349.2013.00219.x · Cited by 116 · see citing works
The molecular logic of Nanog-induced self-renewal in mouse embryonic stem cells
Heurtier, V., Owens, N. D. L., González, I., Mueller, F., Proux, C., Mornico, D., Clerc, P., Dubois, A., & Navarro, P. (2019) · Nature Communications · doi:10.1038/s41467-019-09041-z · Cited by 115 · see citing works
Lenas, P., Moos, M. C., & Luyten, F. P. (2009) · Tissue Engineering Part B Reviews · doi:10.1089/ten.teb.2009.0461 · Cited by 112 · see citing works
Discovery of a kernel for controlling biomolecular regulatory networks
Kim, J., Park, S., & Cho, K. (2013) · Scientific Reports · doi:10.1038/srep02223 · Cited by 111 · see citing works
Lenz, M., Müller, F.-J., Zenke, M., & Schuppert, A. (2016) · Scientific Reports · doi:10.1038/srep25696 · Cited by 111 · see citing works
A single-cell survey of cellular hierarchy in acute myeloid leukemia
Wu, J., Xiao, Y., Sun, J., Sun, H., Chen, H., Zhu, Y., Fu, H., Yu, C., Weigao, E., Lai, S., et al. (2020) · Journal of Hematology & Oncology · doi:10.1186/s13045-020-00941-y · Cited by 110 · see citing works
Epigenetic Landscapes Explain Partially Reprogrammed Cells and Identify Key Reprogramming Genes
Lang, A., Li, H., Collins, J. J., & Mehta, P. (2014) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1003734 · Cited by 109 · see citing works
Models for the Study of Whole Systems
Bell, I. R., & Koithan, M. S. (2006) · Integrative Cancer Therapies · doi:10.1177/1534735406295293 · Cited by 108 · see citing works
Oscillatory Protein Expression Dynamics Endows Stem Cells with Robust Differentiation Potential
Suzuki, N., Furusawa, C., & Kaneko, K. (2011) · PLoS ONE · doi:10.1371/journal.pone.0027232 · Cited by 107 · see citing works
Fei, L., Chen, H., Ma, L., Weigao, E., Wang, R., Fang, X., Zhou, Z., Sun, H., Wang, J., Jiang, M., et al. (2022) · Nature Genetics · doi:10.1038/s41588-022-01118-8 · Cited by 107 · see citing works
Gene regulatory network models for plant development
Alvarez-Buylla, E. R., Benítez, M., DAVILA, E., Chaos, Á., Espinosa‐Soto, C., & Padilla-Longoria, P. (2006) · Current Opinion in Plant Biology · doi:10.1016/j.pbi.2006.11.008 · Cited by 107 · see citing works
Expression cartography of human tissues using self organizing maps
Loeffler‐Wirth, H., Löffler, M., von Bergen�, M., & Binder, H. (2011) · BMC Bioinformatics · doi:10.1186/1471-2105-12-306 · Cited by 106 · see citing works
Basin Entropy in Boolean Network Ensembles
Krawitz, P. M., & Shmulevich, I. (2007) · Physical Review Letters · doi:10.1103/physrevlett.98.158701 · Cited by 106 · see citing works
Criticality Distinguishes the Ensemble of Biological Regulatory Networks
Daniels, B. C., Kim, H., Moore, D. G., Zhou, S., Smith, H. B., Karas, B., Kauffman, S. A., & Walker, S. I. (2018) · Physical Review Letters · doi:10.1103/physrevlett.121.138102 · Cited by 104 · see citing works
SERGIO: A Single-Cell Expression Simulator Guided by Gene Regulatory Networks
Dibaeinia, P., & Sinha, S. (2020) · Cell Systems · doi:10.1016/j.cels.2020.08.003 · Cited by 104 · see citing works
Aqueous outflow regulation – 21st century concepts
Johnstone, M., Chen, X., Tan, J. C. H., Martin, E. A., Wen, J. C., & Wang, R. K. (2020) · Progress in Retinal and Eye Research · doi:10.1016/j.preteyeres.2020.100917 · Cited by 104 · see citing works
Zhou, P., Wang, S., Li, T., & Nie, Q. H. (2021) · Nature Communications · doi:10.1038/s41467-021-25548-w · Cited by 102 · see citing works
Feedback loops and reciprocal regulation: recurring motifs in the systems biology of the cell cycle
Ferrell, J. E. (2013) · Current Opinion in Cell Biology · doi:10.1016/j.ceb.2013.07.007 · Cited by 101 · see citing works
Chisholm, R. H., Lorenzi, T., & Clairambault, J. (2016) · Biochimica et Biophysica Acta (BBA) - General Subjects · doi:10.1016/j.bbagen.2016.06.009 · Cited by 96 · see citing works
Noise-induced switches in network systems of the genetic toggle switch
Wang, J., Zhang, J., Yuan, Z., & Zhou, T. (2007) · BMC Systems Biology · doi:10.1186/1752-0509-1-50 · Cited by 94 · see citing works
Phenotypic Plasticity and Cell Fate Decisions in Cancer: Insights from Dynamical Systems Theory
Jia, D., Jolly, M. K., Kulkarni, P., & Levine, H. (2017) · Cancers · doi:10.3390/cancers9070070 · Cited by 94 · see citing works
Zhang, Q., Li, J., Middleton, A., Bhattacharya, S., & Conolly, R. B. (2018) · Frontiers in Public Health · doi:10.3389/fpubh.2018.00261 · Cited by 92 · see citing works
Manicka, S., & Levin, M. G. (2019) · Philosophical Transactions of the Royal Society B Biological Sciences · doi:10.1098/rstb.2018.0369 · Cited by 91 · see citing works
The informational architecture of the cell
Walker, S. I., Kim, H., & Davies, P. C. W. (2016) · Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences · doi:10.1098/rsta.2015.0057 · Cited by 91 · see citing works
Biswas, S., Manicka, S., Hoel, E. P., & Levin, M. G. (2021) · iScience · doi:10.1016/j.isci.2021.102131 · Cited by 90 · see citing works
Noise-Driven Stem Cell and Progenitor Population Dynamics
Hoffmann, M., Chang, H. H., Huang, S., Ingber, D. E., Loeffler, M., & Galle, J. (2008) · PLoS ONE · doi:10.1371/journal.pone.0002922 · Cited by 90 · see citing works
Self-citationPfeuty, B., & Kaneko, K. (2009) · Physical Biology · doi:10.1088/1478-3975/6/4/046013 · Cited by 89 · see citing works
Chen, J., Cheong, C., Lan, L., Zhou, X., Liu, J., Lü, A., Cheung, W. K., & Zhang, L. (2021) · Briefings in Bioinformatics · doi:10.1093/bib/bbab325 · Cited by 88 · see citing works
The unforeseen challenge: from genotype-to-phenotype in cell populations
Braun, E. (2015) · Reports on Progress in Physics · doi:10.1088/0034-4885/78/3/036602 · Cited by 88 · see citing works
Modeling endotoxin-induced systemic inflammation using an indirect response approach
Foteinou, P. T., Calvano, S. E., Lowry, S. F., & Androulakis, I. P. (2008) · Mathematical Biosciences · doi:10.1016/j.mbs.2008.09.003 · Cited by 88 · see citing works
Boolean network modeling in systems pharmacology
Bloomingdale, P., Nguyen, V. A., Niu, J., & Mager, D. E. (2018) · Journal of Pharmacokinetics and Pharmacodynamics · doi:10.1007/s10928-017-9567-4 · Cited by 86 · see citing works
Mechanically based generative laws of morphogenesis
Beloussov, L. V. (2008) · Physical Biology · doi:10.1088/1478-3975/5/1/015009 · Cited by 84 · see citing works
A Generic Mechanism for Adaptive Growth Rate Regulation
Furusawa, C., & Kaneko, K. (2008) · PLoS Computational Biology · doi:10.1371/journal.pcbi.0040003 · Cited by 84 · see citing works
Stochasticity and the Molecular Mechanisms of Induced Pluripotency
MacArthur, B. D., Please, C. P., & Oreffo, R. O. C. (2008) · PLoS ONE · doi:10.1371/journal.pone.0003086 · Cited by 83 · see citing works
Mouse embryonic stem cells can differentiate via multiple paths to the same state
Briggs, J. A., Li, V. C., Lee, S., Woolf, C. J., Klein, A., & Kirschner, M. W. (2017) · eLife · doi:10.7554/elife.26945 · Cited by 82 · see citing works
Attractors and Democratic Dynamics
Yaneer Bar-yam, A., Harmon, D., & de Bivort, B. L. (2009) · Science · doi:10.1126/science.1163225 · Cited by 82 · see citing works
Control of Stochastic and Induced Switching in Biophysical Networks
Wells, D. K., Kath, W. L., & Motter, A. E. (2015) · Physical Review X · doi:10.1103/physrevx.5.031036 · Cited by 81 · see citing works
- Authors
- Huang, S., Eichler, G., Bar-Yam, Y., & Ingber, D. E.
- Affiliations
- Boston Children's Hospital (US)
- Venue
- Physical Review Letters
- Publisher
- American Physical Society (APS)
- Published
- 2005-04-01
- Volume
- 94
- Issue
- 12
- Pages
- 128701-128701
- ISSN
- 0031-9007 (ISSN-L)
- 1079-7114
- OpenAlex
- W2141545875
- Cited by
- 775
- References
- 33
- Citations by year
- 2026: 42 · 2025: 33 · 2024: 30 · 2023: 31 · 2022: 49 · 2021: 42 · 2020: 56 · 2019: 30 · 2018: 54 · 2017: 39 · 2016: 34 · 2015: 32 · 2014: 34 · 2013: 42 · 2012: 26
- FWCI
- 10.04
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Physical Review Letters (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene Regulatory Network Analysis
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Developmental Biology and Gene Regulation
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Chromatin Dynamics
- Keywords
- cell fate, gene regulatory networks, granulocytic differentiation, cell phenotype, gene expression profiling, network theory
- MeSH terms
- Cell Differentiation, Dimethyl Sulfoxide, Gene Expression Regulation, Humans, Neutrophils, RNA, Messenger, Tretinoin, HL-60 Cells, Oligonucleotide Array Sequence Analysis, Gene Expression Profiling
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review