A blueprint for human whole-cell modeling
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Abstract
Whole-cell dynamical models of human cells are a central goal of systems biology. Such models could help researchers understand cell biology and help physicians treat disease. Despite significant challenges, we believe that human whole-cell models are rapidly becoming feasible. To develop a plan for achieving human whole-cell models, we analyzed the existing models of individual cellular pathways, surveyed the biomodeling community, and reflected on our experience developing whole-cell models of bacteria. Based on these analyses, we propose a plan for a project, termed the Human Whole-Cell Modeling Project, to achieve human whole-cell models. The foundations of the plan include technology development, standards development, and interdisciplinary collaboration.
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BioModels is the world's largest repository of curated models and the third most used data resource after PubMed and Google Scholar among scientists who use modelling in their research.
“BioModels is the world’s largest repository of curated models and is the third most used data resource after PubMed and Google Scholar among the scientists who use modelling in their research (Stanford et al., 2015; Szigeti et al., 2018).”
From BioModels Parameters: a treasure trove of parameter values from published systems biology models (2020) · cites this paper as Szigeti et al., 2018
The “Incompatible models” section identifies BioModels as a model repository. It does not say that BioModels is the world’s largest repository of curated models or rank its use against PubMed and Google Scholar; searches for those terms found no supporting passage in our copy. No page number was available. (LLM, conf=0.78)
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Cites
What is flux balance analysis?
Orth, J. D., Thiele, I., & Palsson, B. Ø. (2010) · Nature Biotechnology · doi:10.1038/nbt.1614 · Cited by 3,903 · see citing works
A pathology atlas of the human cancer transcriptome
Uhlen, M., Zhang, C., Lee, S., Sjöstedt, E., Fagerberg, L., Bidkhori, G., Benfeitas, R., Arif, M., Liu, Z., Edfors, F., et al. (2017) · Science · doi:10.1126/science.aan2507 · Cited by 3,371 · see citing works
Hucka, M., Finney, A., Sauro, H. M., Bolouri, H., Doyle, J. C., Kitano, H., Arkin, A. P., Bornstein, B. J., Bray, D., Cornish-Bowden, A., et al. (2003) · Bioinformatics · doi:10.1093/bioinformatics/btg015 · Cited by 3,060 · see citing works
Architecture of the human regulatory network derived from ENCODE data
Gerstein, M., Kundaje, A. B., Hariharan, M., Landt, S. G., Yan, K., Cheng, C., Mu, X. J., Khurana, E., Rozowsky, J. S., Alexander, R. P., et al. (2012) · Nature · doi:10.1038/nature11245 · Cited by 1,418 · see citing works
A Whole-Cell Computational Model Predicts Phenotype from Genotype
Karr, J. R., Sanghvi, J. C., Macklin, D. N., Gutschow, M. V., Jacobs, J. M., Bolival, B., Assad-Garcia, N., Glass, J. I., & Covert, M. W. (2012) · Cell · doi:10.1016/j.cell.2012.05.044 · Cited by 1,300 · see citing works
Modelling and analysis of gene regulatory networks
Karlebach, G., & Shamir, R. (2008) · Nature Reviews Molecular Cell Biology · doi:10.1038/nrm2503 · Cited by 1,296 · see citing works
The Human Genome Project: Lessons from Large-Scale Biology
Collins, F. S., Morgan, M., & Patrinos, A. (2003) · Science · doi:10.1126/science.1084564 · Cited by 1,284 · see citing works
Systems Biology and New Technologies Enable Predictive and Preventative Medicine
Hood, L., Heath, J. R., Phelps, M. E., & Lin, B. (2004) · Science · doi:10.1126/science.1104635 · Cited by 1,108 · see citing works
Quantitative mass spectrometry in proteomics: critical review update from 2007 to the present
Bantscheff, M., Lemeer, S., Savitski, M. M., & Kuster, B. (2012) · Analytical and Bioanalytical Chemistry · doi:10.1007/s00216-012-6203-4 · Cited by 801 · see citing works
Integrating high-throughput and computational data elucidates bacterial networks
Covert, M. W., Knight, E. M., Reed, J. L., Herrgard, M. J., & Palsson, B. O. (2004) · Nature · doi:10.1038/nature02456 · Cited by 792 · see citing works
E-CELL: software environment for whole-cell simulation
Tomita, M., Hashimoto, K., Takahashi, K., Shimizu, T. S., Matsuzaki, Y., Miyoshi, F., Saito, K., Tanida, S., Yugi, K., Venter, J. C., et al. (1999) · Bioinformatics · doi:10.1093/bioinformatics/15.1.72 · Cited by 764 · see citing works
Howe, D. G., Costanzo, M. C., Fey, P., Gojobori, T., Hannick, L. I., Hide, W., Hill, D. P., Kania, R., Schaeffer, M. L., Pierre, S. S., et al. (2008) · Nature · doi:10.1038/455047a · Cited by 695 · see citing works
Single cell analysis: the new frontier in 'Omics'
Wang, D., & Bodovitz, S. (2010) · Trends in biotechnology · doi:10.1016/j.tibtech.2010.03.002 · Cited by 669 · see citing works
Toward a detailed computational model for the mammalian circadian clock
Leloup, J., & Goldbeter, A. (2003) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1132112100 · Cited by 535 · see citing works
Single-cell multiomics: multiple measurements from single cells
Macaulay, I. C., Ponting, C. P., & Voet, T. (2017) · Trends in Genetics · doi:10.1016/j.tig.2016.12.003 · Cited by 451 · see citing works
Modeling Single-Neuron Dynamics and Computations: A Balance of Detail and Abstraction
Herz, A. V. M., Gollisch, T., Machens, C. K., & Jaeger, D. (2006) · Science · doi:10.1126/science.1127240 · Cited by 450 · see citing works
Rule-Based Modeling of Biochemical Systems with BioNetGen
Faeder, J. R., Blinov, M. L., & Hlavacek, W. S. (2009) · Methods in molecular biology · doi:10.1007/978-1-59745-525-1_5 · Cited by 432 · see citing works
Ågren, R., Bordel, S., Mardinoğlu, A., Pornputtapong, N., Nookaew, I., & Nielsen, J. (2012) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1002518 · Cited by 430 · see citing works
Chandrasekaran, S., & Price, N. D. (2010) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1005139107 · Cited by 399 · see citing works
Whole-cell simulation: a grand challenge of the 21st century
Tomita, M. (2001) · Trends in biotechnology · doi:10.1016/s0167-7799(01)01636-5 · Cited by 319 · see citing works
Integrating metabolic, transcriptional regulatory and signal transduction models inEscherichia coli
Covert, M. W., Xiao, N., Chen, T. J., & Karr, J. R. (2008) · Bioinformatics · doi:10.1093/bioinformatics/btn352 · Cited by 316 · see citing works
The expanding scope of DNA sequencing
Shendure, J., & Aiden, E. L. (2012) · Nature Biotechnology · doi:10.1038/nbt.2421 · Cited by 300 · see citing works
Efficient modeling, simulation and coarse-graining of biological complexity with NFsim
Sneddon, M. W., Faeder, J. R., & Emonet, T. (2010) · Nature Methods · doi:10.1038/nmeth.1546 · Cited by 291 · see citing works
Recon 2.2: from reconstruction to model of human metabolism
Swainston, N., Smallbone, K., Hefzi, H., Dobson, P. D., Brewer, J., Hanscho, M., Zielinski, D. C., Ang, K. S., Gardiner, N. J., Gutierrez, J. M., et al. (2016) · Metabolomics · doi:10.1007/s11306-016-1051-4 · Cited by 285 · see citing works
BioModels: ten-year anniversary
Chelliah, V., Juty, N., Ajmera, I., Ali, R., Dumousseau, M., Glont, M., Hucka, M., Jalowicki, G., Keating, S., Knight-Schrijver, V., et al. (2015) · Nucleic Acids Research · doi:10.1093/nar/gku1181 · Cited by 281 · see citing works
Waltemath, D., Adams, R., Bergmann, F. T., Hucka, M., Kolpakov, F., Miller, A. K., Moraru, I., Nickerson, D., Sahle, S., Snoep, J., et al. (2011) · BMC Systems Biology · doi:10.1186/1752-0509-5-198 · Cited by 269 · see citing works
Ligand-Specific c-Fos Expression Emerges from the Spatiotemporal Control of ErbB Network Dynamics
Nakakuki, T., Birtwistle, M. R., Saeki, Y., Yumoto, N., Ide, K., Nagashima, T., Brusch, L., Ogunnaike, B. A., Okada, M., & Kholodenko, B. Ν. (2010) · Cell · doi:10.1016/j.cell.2010.03.054 · Cited by 241 · see citing works
Dynamic Analysis of Integrated Signaling, Metabolic, and Regulatory Networks
Lee, J. M., Gianchandani, E. P., Eddy, J. A., & Papin, J. A. (2008) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1000086 · Cited by 225 · see citing works
König, M., Bulik, S., & Holzhütter, H.-G. (2012) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1002577 · Cited by 202 · see citing works
Thiele, I., Jamshidi, N., Fleming, R. M. T., & Palsson, B. Ø. (2009) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1000312 · Cited by 182 · see citing works
Europe PMC: a full-text literature database for the life sciences and platform for innovation
The Europe PMC Consortium (2014) · Nucleic Acids Research · doi:10.1093/nar/gku1061 · Cited by 145 · see citing works
BioModels Database: A Repository of Mathematical Models of Biological Processes
Chelliah, V., Laibe, C., & Novère, N. G. L. (2013) · Methods in molecular biology · doi:10.1007/978-1-62703-450-0_10 · Cited by 133 · see citing works
Towards building the silicon cell: A modular approach
Snoep, J. L., Bruggeman, F. J., Olivier, B. G., & Westerhoff, H. V. (2005) · Biosystems · doi:10.1016/j.biosystems.2005.07.006 · Cited by 121 · see citing works
Annotation and merging of SBML models with semanticSBML
Krause, F., Uhlendorf, J., Lubitz, T., Schulz, M., Klipp, E., & Liebermeister, W. (2010) · Bioinform. · doi:10.1093/bioinformatics/btp642 · Cited by 108 · see citing works
Barnes, P. D., Carothers, C. D., Jefferson, D. R., & LaPre, J. M. (2013) · ACM/IEEE/SCS Workshop on Principles of Advanced and Distributed Simulation (PADS) · doi:10.1145/2486092.2486134 · Cited by 103 · see citing works
Metabolic fingerprinting reveals a novel candidate biomarker for prednisolone treatment in cattle
Clercq, N. D., Bussche, J. V., Meulebroek, L. V., Croubels, S., Delahaut, P., Buyst, D., Martins, J. C., Stahl-Zeng, J., & Vanhaecke, L. (2015) · Metabolomics · doi:10.1007/s11306-015-0887-3 · Cited by 97 · see citing works
A Hybrid Model of Mammalian Cell Cycle Regulation
Singhania, R., Sramkoski, R. M., Jacobberger, J. W., & Tyson, J. J. (2011) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1001077 · Cited by 94 · see citing works
Gonçalves, E., Bucher, J., Ryll, A., Niklas, J., Mauch, K., Klamt, S., Rocha, M., & Sáez-Rodríguez, J. (2013) · Molecular BioSystems · doi:10.1039/c3mb25489e · Cited by 91 · see citing works
Correction: Dynamic Analysis of Integrated Signaling, Metabolic, and Regulatory Networks
Lee, J. M., Gianchandani, E. P., Eddy, J. A., & Papin, J. A. (2008) · PLoS Computational Biology · doi:10.1371/annotation/5594348b-de00-446a-bdd0-ec56e70b3553 · Cited by 89 · see citing works
Systems biology standards—the community speaks
Klipp, E., Liebermeister, W., Helbig, A., Kowald, A., & Schaber, J. (2007) · Nature Biotechnology · doi:10.1038/nbt0407-390 · Cited by 88 · see citing works
Carrera, J., & Covert, M. W. (2015) · Trends in Cell Biology · doi:10.1016/j.tcb.2015.09.004 · Cited by 88 · see citing works
The future of whole-cell modeling
Macklin, D. N., Ruggero, N. A., & Covert, M. W. (2014) · Current Opinion in Biotechnology · doi:10.1016/j.copbio.2014.01.012 · Cited by 83 · see citing works
The principles of whole-cell modeling
Karr, J. R., Takahashi, K., & Funahashi, A. (2015) · Current Opinion in Microbiology · doi:10.1016/j.mib.2015.06.004 · Cited by 82 · see citing works
Emerging whole-cell modeling principles and methods
Goldberg, A. P., Szigeti, B., Yin, H.-C., Sekar, J. A. P., Roth, Y. D., & Karr, J. R. (2017) · Current Opinion in Biotechnology · doi:10.1016/j.copbio.2017.12.013 · Cited by 82 · see citing works
An integrative, multi‐scale, genome‐wide model reveals the phenotypic landscape of Escherichia coli
Carrera, J., Estrela, R., Luo, J., Rai, N., Τσουκαλάς, Α., & Tagkopoulos, I. (2014) · Molecular Systems Biology · doi:10.15252/msb.20145108 · Cited by 76 · see citing works
Large-scale non-targeted metabolomic profiling in three human population-based studies
Ganna, A., Fall, T., Salihović, S., Lee, W., Broeckling, C. D., Kumar, J., Hägg, S., Stenemo, M., Magnusson, P. K. E., Prenni, J. E., et al. (2015) · Metabolomics · doi:10.1007/s11306-015-0893-5 · Cited by 65 · see citing works
Computational modeling of mammalian signaling networks
Hughey, J., Lee, T. K., & Covert, M. W. (2009) · WIREs Systems Biology and Medicine · doi:10.1002/wsbm.52 · Cited by 63 · see citing works
Toward Community Standards and Software for Whole-Cell Modeling
Waltemath, D., Karr, J. R., Bergmann, F., Chelliah, V., Hucka, M., Krantz, M., Liebermeister, W., Mendes, P., Myers, C. J., Pir, P., et al. (2016) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2016.2560762 · Cited by 57 · see citing works
Reverse engineering a hierarchical regulatory network downstream of oncogenic KRAS
Stelniec‐Klotz, I., Legewie, S., Tchernitsa, O. I., Witzel, F., Klinger, B., Sers, C., Herzel, H., Blüthgen, N., & Schäfer, R. (2012) · Molecular Systems Biology · doi:10.1038/msb.2012.32 · Cited by 55 · see citing works
A reappraisal of how to build modular, reusable models of biological systems.
Neal, M. L., Cooling, M. T., Smith, L. P., Thompson, C. T., Sauro, H. M., Carlson, B. E., Cook, D. L., & Gennari, J. H. (2014) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1003849 · Cited by 49 · see citing works
Systems biology of the metabolic network regulated by the Akt pathway
Mosca, E., Barcella, M., Alfieri, R. R., Bevilacqua, A., Canti, G. L., & Milanesi, L. (2011) · Biotechnology Advances · doi:10.1016/j.biotechadv.2011.08.004 · Cited by 40 · see citing works
The evolution of standards and data management practices in systems biology
Stanford, N. J., Wolstencroft, K., Golebiewski, M., Kania, R., Juty, N., Tomlinson, C., Owen, S., Butcher, S., Hermjakob, H., Le Novère, N., et al. (2015) · Molecular Systems Biology · doi:10.15252/msb.20156053 · Cited by 38 · see citing works
Hilgartner, S. (2013) · BioSocieties · doi:10.1057/biosoc.2013.31 · Cited by 36 · see citing works
Huard, J., Mueller, S., Gilles, E. D., Klingmüller, U., & Klamt, S. (2012) · The FEBS Journal · doi:10.1111/j.1742-4658.2012.08572.x · Cited by 29 · see citing works
Toward Scalable Whole-Cell Modeling of Human Cells
Goldberg, A. P., Chew, Y. H., & Karr, J. R. (2016) · ACM SIGSIM Conference on Principles of Advanced Discrete Simulation (SIGSIM-PADS) · doi:10.1145/2901378.2901402 · Cited by 18 · see citing works
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BioModels—15 years of sharing computational models in life science
Malik-Sheriff, R. S., Glont, M., Nguyen, T. V. N., Tiwari, K., Roberts, M. G., Xavier, A., Vu, M. T., Men, J., Maire, M., Kananathan, S., et al. (2019) · Nucleic Acids Research · doi:10.1093/nar/gkz1055 · Cited by 361 · see citing works
Emerging whole-cell modeling principles and methods
Goldberg, A. P., Szigeti, B., Yin, H.-C., Sekar, J. A. P., Roth, Y. D., & Karr, J. R. (2017) · Current Opinion in Biotechnology · doi:10.1016/j.copbio.2017.12.013 · Cited by 82 · see citing works
Azer, K., Kaddi, C. D., Barrett, J. S., Bai, J. P. F., McQuade, S. T., Merrill, N. J., Piccoli, B., Neves, S. R., Marchetti, L., Lombardo, R., et al. (2021) · Frontiers in Physiology · doi:10.3389/fphys.2021.637999 · Cited by 85 · see citing works
Whole-Cell Models and Simulations in Molecular Detail
Feig, M., & Sugita, Y. (2019) · Annual Review of Cell and Developmental Biology · doi:10.1146/annurev-cellbio-100617-062542 · Cited by 77 · see citing works
Building structural models of a whole mycoplasma cell
Maritan, M., Autin, L., Karr, J., Covert, M. W., Olson, A. J., & Goodsell, D. S. (2022) · Journal of Molecular Biology · doi:10.1016/j.jmb.2021.167351 · Cited by 75 · see citing works
Vakser, I. A. (2020) · Current Opinion in Structural Biology · doi:10.1016/j.sbi.2020.07.001 · Cited by 62 · see citing works
Best Practices for Making Reproducible Biochemical Models
Porubsky, V. L., Goldberg, A. P., Rampadarath, A. K., Nickerson, D. P., Karr, J. R., & Sauro, H. M. (2020) · Cell Systems · doi:10.1016/j.cels.2020.06.012 · Cited by 45 · see citing works
Montagud, A., Ponce-de-León, M., & Valencia, A. (2021) · Current Opinion in Systems Biology · doi:10.1016/j.coisb.2021.100385 · Cited by 46 · see citing works
The design and engineering of synthetic genomes
James, J. S., Dai, J., Chew, W. L., & Cai, Y. (2024) · Nature Reviews Genetics · doi:10.1038/s41576-024-00786-y · Cited by 48 · see citing works
Portela, R., Varsakelis, C., Richelle, A., Giannelos, N., Pence, J., Dessoy, S., & von Stosch, M. (2020) · Advances in Biochemical Engineering/Biotechnology · doi:10.1007/10_2020_138 · Cited by 34 · see citing works
Waltemath, D., Golebiewski, M., Blinov, M. L., Gleeson, P., Hermjakob, H., Hucka, M., Inau, E. T., Keating, S., König, M., Krebs, O., et al. (2020) · Berichte aus der medizinischen Informatik und Bioinformatik/Journal of integrative bioinformatics · doi:10.1515/jib-2020-0005 · Cited by 38 · see citing works
Bayesian metamodeling of complex biological systems across varying representations
Raveh, B., Sun, L., White, K. L., Sanyal, T., Tempkin, J. O. B., Zheng, D., Bharath, K., Singla, J., Wang, C., Zhao, J., et al. (2021) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2104559118 · Cited by 34 · see citing works
Modular assembly of dynamic models in systems biology
Pan, M., Gawthrop, P. J., Cursons, J., & Crampin, E. J. (2021) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1009513 · Cited by 32 · see citing works
Aghakhani, S., Zerrouk, N., & Niarakis, A. (2020) · Cancers · doi:10.3390/cancers13010035 · Cited by 29 · see citing works
Erdem, C., Mutsuddy, A., Bensman, E. M., Dodd, W. B., Saint-Antoine, M., Bouhaddou, M., Blake, R. C., Gross, S. M., Heiser, L. M., Feltus, F. A., et al. (2022) · Nature Communications · doi:10.1038/s41467-022-31138-1 · Cited by 26 · see citing works
Computational Structural Biology: Successes, Future Directions, and Challenges
Nussinov, R., Tsai, C., Shehu, A., & Jang, H. (2019) · Molecules · doi:10.3390/molecules24030637 · Cited by 25 · see citing works
Organizing genome engineering for the gigabase scale
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Predicting gastrointestinal drug effects using contextualized metabolic models
Guebila, M. B., & Thiele, I. (2019) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1007100 · Cited by 22 · see citing works
Shaikh, B., Marupilla, G., Wilson, M., Blinov, M. L., Moraru, I. I., & Karr, J. R. (2021) · Nucleic Acids Research · doi:10.1093/nar/gkab411 · Cited by 21 · see citing works
Soft X‐ray tomograms provide a structural basis for whole‐cell modeling
Loconte, V., Chen, J., Vanslembrouck, B., Ekman, A. A., McDermott, G., Gros, M. A. L., & Larabell, C. A. (2022) · The FASEB Journal · doi:10.1096/fj.202200253r · Cited by 21 · see citing works
Moškon, M., & Režen, T. (2023) · Metabolites · doi:10.3390/metabo13010126 · Cited by 19 · see citing works
Organizing genome engineering for the gigabase scale
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Developments in integrative modeling with dynamical interfaces
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Genome-driven cell engineering review: in vivo and in silico metabolic and genome engineering
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Analysing and simulating energy-based models in biology using BondGraphTools
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Zelenka, N., Cara, N. H. D., Sharma, K., Sarvaharman, S., Ghataora, J. S., Parmeggiani, F., Nivala, J., Abdallah, Z. S., Marucci, L., & Gorochowski, T. E. (2024) · Synthetic Biology · doi:10.1093/synbio/ysae010 · Cited by 16 · see citing works
Gawthrop, P. J., Pan, M., & Crampin, E. J. (2021) · Journal of The Royal Society Interface · doi:10.1098/rsif.2021.0478 · Cited by 15 · see citing works
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Roth, Y. D., Lian, Z., Pochiraju, S., Shaikh, B., & Karr, J. R. (2020) · Nucleic Acids Research · doi:10.1093/nar/gkaa1008 · Cited by 15 · see citing works
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BioModels Parameters: a treasure trove of parameter values from published systems biology models
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Rajagopal, V., Arumugam, S., Hunter, P. J., Khadangi, A., Chung, J., & Pan, M. (2022) · Annual Review of Biomedical Data Science · doi:10.1146/annurev-biodatasci-072018-021246 · Cited by 12 · see citing works
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Chude-Okonkwo, U. A. K. (2021) · International Conference on Signal Processing and Communication Systems · doi:10.1109/icspcs53099.2021.9660222 · Cited by 10 · see citing works
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Wytock, T. P., & Motter, A. E. (2024) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2312942121 · Cited by 9 · see citing works
Pleione: A tool for statistical and multi-objective calibration of Rule-based models
Santibáñez, R., Garrido, D. A., & Martín, A. J. M. (2019) · Scientific Reports · doi:10.1038/s41598-019-51546-6 · Cited by 8 · see citing works
Santibáñez, R., Garrido, D. A., & Martín, A. J. M. (2020) · Bioinformatics · doi:10.1093/bioinformatics/btaa1040 · Cited by 9 · see citing works
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Sarkar, D., & Maranas, C. D. (2019) · BMC Chemical Engineering · doi:10.1186/s42480-019-0021-9 · Cited by 6 · see citing works
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Uschner, F., & Klipp, E. (2019) · Current Opinion in Biotechnology · doi:10.1016/j.copbio.2019.03.011 · Cited by 4 · see citing works
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Marucci, L., Barberis, M., Karr, J. R., Ray, O., Race, P., Andrade, M. D. S., Grierson, C., Hoffmann, S. A., Landon, S., Rech, E., et al. (2020) · Frontiers in Bioengineering and Biotechnology · doi:10.3389/fbioe.2020.00942 · Cited by 39 · see citing works
Gawthrop, P. J., Pan, M., & Crampin, E. J. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.03.24.436792 · Cited by 4 · see citing works
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Alfego, D., & Kriete, A. (2017) · Biology · doi:10.3390/biology6040044 · Cited by 3 · see citing works
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Fischer, S., Dinh, M., Henry, V., Robert, P., Goelzer, A., & Fromion, V. (2021) · Scientific Reports · doi:10.1038/s41598-021-92833-5 · Cited by 3 · see citing works
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Burke, P. E. P. (2021) · doi:10.11606/t.95.2021.tde-23032021-143111 · Cited by 3 · see citing works
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Shaikh, B., Smith, L. P., Vasilescu, D., Marupilla, G., Wilson, M., Agmon, E., Agnew, H., Andrews, S., Anwar, A., Beber, M., et al. (2022) · Nucleic Acids Res. · doi:10.1093/nar/gkac331 · Cited by 31 · see citing works
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Babtie, A. C. (2019) · Current Opinion in Systems Biology · doi:10.1016/j.coisb.2019.10.014
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Gawthrop, P. J. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2007.15917
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Corbat, A. A., Silberberg, M., & Grecco, H. E. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.05.21.444824
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Chew, Y. H., & Karr, J. R. (2021) · Current Opinion in Systems Biology · doi:10.1016/j.coisb.2021.06.004
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Shaikh, B., Freiburger, A., König, M., Bergmann, F., Nickerson, D. P., Sauro, H. M., Blinov, M. L., Smith, L. P., Moraru, I. I., & Karr, J. R. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2106.00844
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Ghaemi, Z., Nafiu, O., Tajkhorshid, E., Gruebele, M., & Hu, J. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.06.01.494377
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Chew, Y. H., & Marucci, L. (2024) · Methods in molecular biology · doi:10.1007/978-1-0716-3718-0_6
Portela, R. M. C., Varsakelis, C., Richelle, A., Giannelos, N., Pence, J., Dessoy, S., & von Stosch, M. (2025) · Springer eBooks · doi:10.1007/978-3-031-75698-6_2
FAIRsharing record for: BioModels
FAIRsharing Team (2015) · FAIRsharing.org · doi:10.25504/fairsharing.paz6mh
- Authors
- Szigeti, B., Roth, Y. D., Sekar, J. A. P., Goldberg, A. P., Pochiraju, S. C., & Karr, J. R.
- Affiliations
- Icahn School of Medicine at Mount Sinai (US)
- Corresponding author
- Karr, Jonathan R.
- Venue
- Current Opinion in Systems Biology
- Publisher
- Elsevier BV
- Published
- 2018-02
- Volume
- 7
- Pages
- 8-15
- ISSN
- 2452-3100 (ISSN-L)
- PMC
- PMC5966287
- OpenAlex
- W2952117952
- Cited by
- 72
- References
- 55
- Citations by year
- 2026: 1 · 2025: 3 · 2024: 6 · 2023: 6 · 2022: 7 · 2021: 19 · 2020: 14 · 2019: 13 · 2018: 1 · 2017: 2
- FWCI
- 0.77
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- Current Opinion in Systems Biology (acceptedVersion)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, public-domain)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Science Foundation
- National Institute of Mental Health (1 R35 GM 119771-01, 1649014)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene Regulatory Network Analysis
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Microbial Metabolic Engineering and Bioproduction
- Keywords
- whole-cell modeling, human cells, systems biology, interdisciplinary collaboration
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