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Mathematical and computational models of immune-receptor signaling
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Goldstein B, Faeder JR, Hlavacek WS: Mathematical and computational models of immune-receptor signaling. Nat Rev Immunol 2004, 4:445-456. An excellent review of mathematical modeling applied to immune receptor signaling that highlights the need for modeling in this system.
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Nat Rev Immunol
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Goldstein, B.1
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An integrated model of epidermal growth factor receptor trafficking and signal transduction
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Biophys J
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Regulation of the mammalian cell cycle: A model of the G1-to-S transition
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Qu Z, Weiss JN, MacLellan WR: Regulation of the mammalian cell cycle: a model of the G1-to-S transition. Am J Physiol Cell Physiol 2003, 284:C349-C364.
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Am J Physiol Cell Physiol
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Qu, Z.1
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J Theor Biol
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Maeda, M.1
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Quantitative analysis of HER2-mediated effects on HER2 and epidermal growth factor receptor endocytosis
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Hendriks BS, Opresko LK, Wiley HS, et al.: Quantitative analysis of HER2-mediated effects on HER2 and epidermal growth factor receptor endocytosis. J Biol Chem 2003, 278:23343-23354. A great example of how models can be used to gain insight into complicated dynamics receptor trafficking in cancer cells with relevance to therapeutics.
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J Biol Chem
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Hendriks, B.S.1
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Data-driven computer simulation of human cancer cell
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Christopher R, Dhiman A, Fox J, et al.: Data-driven computer simulation of human cancer cell. Ann N Y Acad Sci 2004, 1020:1-22. Current computational methods and technologies actually make it feasible to integration vast amounts of data into whole-cell models containing many interacting genes, proteins, and protein modifications. These simulations are beginning to be used by pharmaceutical and biotechnology companies to test and devise effective therapeutics.
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Ann N Y Acad Sci
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Christopher, R.1
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Statistical mechanical approaches to models with many poorly known parameters
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Brown KS, Sethna JP: Statistical mechanical approaches to models with many poorly known parameters. Phys Rev 2003, 68:021904-021909. This article contains statistical approaches to analyzing the predictive accuracy of dynamical models.
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Phys Rev
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Brown, K.S.1
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Cancer as a robust system: Implications for anticancer therapy
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Kitano H: Cancer as a robust system: implications for anticancer therapy. Nat Rev Cancer 2004, 4:227-235. A nice discussion on the role of robustness in cancer and how this can be exploited for designing novel therapies.
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Nat Rev Cancer
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Kitano, H.1
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Network biology: Understanding the cell's functional organization
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Barabasi AL, Oltvai ZN: Network biology: understanding the cell's functional organization. Nat Rev Genet 2004, 5:101-113. An examination of the universal laws governing cellular networks.
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Nat Rev Genet
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Barabasi, A.L.1
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Biological networks: The tinkerer as an engineer
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Alon U: Biological networks: the tinkerer as an engineer. Science 2003, 301:1866-1867. A useful commentary on advances relating to the design principles of biological networks.
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Science
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Alon, U.1
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Summing up the noise in gene networks
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Paulsson J: Summing up the noise in gene networks. Nature 2004, 427:415-418. An analysis of the role of noise fluctuations in driving the dynamics of biological systems.
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Nature
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Paulsson, J.1
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Network motifs in integrated cellular networks of transcription- regulation and protein-protein interaction
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Shannon P, Markiel A, Ozier O, et al.: Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res 2003, 13:2498-2504.
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Inferring cellular networks using probabilistic graphical models
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Friedman N: Inferring cellular networks using probabilistic graphical models. Science 2004, 303:799-805. An excellent review on the use of probabilistic graphical models for inferring cellular networks. The article provides insights into how microarray data and other data types can be used to infer regulatory networks.
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Science
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Friedman, N.1
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A protein interaction map of Drosophila melanogaster
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Giot L, Bader JS, Brouwer C, et al.: A protein interaction map of Drosophila melanogaster. Science 2003, 302:1727-1736. An example of how high-throughput methods can reveal entire proteome networks for multicellular organisms. These approaches will be valuable in deciphering the human proteome.
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Science
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Giot, L.1
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A map of the interactome network of the Metazoan C. elegans
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Li S, Armstrong CM, Berlin N, et al.: A map of the interactome network of the Metazoan C. elegans. Science 2004, 303:540-543. Similar to [19••].
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Science
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Li, S.1
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A physical and functional map of the human TNF-a/NF-kB signal transduction pathway
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Bouwmeester T, Bauch A, Ruffner H, et al.: A physical and functional map of the human TNF-a/NF-kB signal transduction pathway. Nat Cell Biol 2004, 6:97-105. An effective method for uncovering signaling protein networks of therapeutic pathways.
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Nat Cell Biol
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Bouwmeester, T.1
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Proteomics: The first decade and beyond
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Patterson SD, Aebersold RH: Proteomics: the first decade and beyond. Nat Genet Suppl 2003, 33:311-323. An excellent review of proteomic technologies.
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Nat Genet Suppl
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Patterson, S.D.1
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Proteomic profiling of the NCl-60 cancer cell lines using new high-density reverse-phase lysate microarrays
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Nishizuka S, Charboneau L, Young L, et al.: Proteomic profiling of the NCl-60 cancer cell lines using new high-density reverse-phase lysate microarrays. Proc Natl Acad Sci USA 2003, 100:14229-14234. Proteomic methods of ever-increasing accuracy will greatly affect the ability to create accurate quantitative models.
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Proc Natl Acad Sci USA
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Nishizuka, S.1
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Diagnostic markers that distinguish colon and ovarian adenocarcinomas: Identification by genomic, proteomic, and tissue array profiling
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Cancer Res
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Monitoring p53's pulse
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Tyson J: Monitoring p53's pulse. Nat Genet 2004, 36:113-114. Tyson discusses the importance of using mathematical approaches to decipher the dynamics of intricate and nonintuitive behavior.
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Nat Genet
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Lahav G, Rosenfeld N, Sigal A, et al.: Dynamics of the p53-Mdm2 feedback loop in individual cells. Nat Genet 2004, 36:147-150. Biological systems are both dynamical and stochastic, and many current experiments overlook this. This not only is a good example of the kind of interesting behavior when one looks at quantitative signal cell behavior but also has already resulted in a greater understanding of the mechanisms underlying p53 dynamics.
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Nat Genet
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Lahav, G.1
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Protein profiles associated with survival in lung adenocarcinoma
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Chen G, Gharib TG, Wang H, et al.: Protein profiles associated with survival in lung adenocarcinoma. Proc Natl Acad Sci USA 2003, 100:13537-13542. An example of proteomic technologies applied to lung cancer.
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Proc Natl Acad Sci USA
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Chen, G.1
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Clinical applications of proteomics
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Petricoin EF, Liotta LA: Clinical applications of proteomics. J Nutr 2003, 133:2476S-2484S. A review highlighting the need to measure proteomic levels directly in humans for diagnostics and therapy. Microarray data, although informative on a global level, will not be useful in revealing the dysfunction that occurs in protein networks for cancer.
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J Nutr
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Petricoin, E.F.1
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Geho DH, Petricoin EF, Liotta LA: Blasting into the microworld of tissue proteomics: a new window on cancer. Clin Cancer Res 2004, 10:825-827.
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Clin Cancer Res
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Baggerly KA, Morris JS, Coombes KR: Reproducibility of SELDI-TOF protein patterns in serum: comparing datasets from different experiments. Bioinformatics 2004, 20:777-785. A cautionary note about the importance of good experimental design and statistics to insure good reproducible results from human tissue proteomic data.
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Bioinformatics
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Kim JB, Stein R, O'Hare MJ: Three-dimensional in vitro tissue culture models of breast cancer-a review. Breast Cancer Res Treat 2004, 85:281-291.
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Development of a microscale cell culture analog to probe naphthalene toxicity
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Viravaidya K, Sin A, Shuler ML: Development of a microscale cell culture analog to probe naphthalene toxicity. Biotechnol Prog 2004, 20:316-323. An important effort in devising biologically relevant in vitro systems that is more reflective of whole body physiology. These devices have the potential to revolutionize efficacy and toxicity of therapeutic compounds in an efficient and scaleable manner.
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Biotechnol Prog
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Sin A, Chin KC, Jamil MF, et al.: The design and fabrication of three-chamber microscale cell culture analog devices with integrated dissolved oxygen sensors. Biotechnol Prog 2004, 20:338-345. This paper contains an important effort in connecting PBPK models to microfabricated devices that reflect human physiology.
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Biotechnol Prog
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Kuperwasser C, Chavarria T, Wu M, et al.: Reconstruction of functionally normal and malignant human breast tissues in mice. Proc Natl Acad Sci USA 2004, 101:4966-4971. More researchers need to consider ways of improving human in vivo correlative capabilities of their animal models. This article highlights important work with regard to this endeavor.
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Proc Natl Acad Sci USA
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Kuperwasser, C.1
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