Mathematical Biology Models of Parkinson's Disease
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Vijayalakshmi Chelliah | Piet H. van der Graaf | V. Chelliah | P. H. van der Graaf | Suruchi Bakshi | Chao Chen | Suruchi Bakshi | Chao Chen | Vijayalakshmi Chelliah
[1] Eberhard O Voit,et al. Computational analysis of determinants of dopamine (DA) dysfunction in DA nerve terminals , 2009, Synapse.
[2] Michael Weiner,et al. Network Diffusion Model of Progression Predicts Longitudinal Patterns of Atrophy and Metabolism in Alzheimer's Disease. , 2015, Cell reports.
[3] Suneil K. Kalia,et al. Emerging disease‐modifying strategies targeting α‐synuclein for the treatment of Parkinson's disease , 2018, British journal of pharmacology.
[4] J. Agar,et al. Fitting neurological protein aggregation kinetic data via a 2-step, minimal/"Ockham's razor" model: the Finke-Watzky mechanism of nucleation followed by autocatalytic surface growth. , 2008, Biochemistry.
[5] V. Sossi,et al. Longitudinal progression of sporadic Parkinson's disease: a multi-tracer positron emission tomography study. , 2009, Brain : a journal of neurology.
[6] John P. Lowry,et al. An integrative dynamic model of brain energy metabolism using in vivo neurochemical measurements , 2009, Journal of Computational Neuroscience.
[7] M. Weiner,et al. A Network Diffusion Model of Disease Progression in Dementia , 2012, Neuron.
[8] Rafal Bogacz,et al. Computational Models Describing Possible Mechanisms for Generation of Excessive Beta Oscillations in Parkinson’s Disease , 2015, PLoS Comput. Biol..
[9] Alexander K. Buell,et al. Mutations associated with familial Parkinson’s disease alter the initiation and amplification steps of α-synuclein aggregation , 2016, Proceedings of the National Academy of Sciences.
[10] V. Sossi,et al. The Nature of Progression in Parkinson’s Disease: An Application of Non-Linear, Multivariate, Longitudinal Random Effects Modelling , 2013, PloS one.
[11] Kim Sneppen,et al. Modeling proteasome dynamics in Parkinson's disease , 2009, Physical biology.
[12] Richard H. Middleton,et al. A single compartment model of pacemaking in dissasociated Substantia nigra neurons , 2013, Journal of Computational Neuroscience.
[13] Samik Ghosh,et al. Integrating Pathways of Parkinson's Disease in a Molecular Interaction Map , 2013, Molecular Neurobiology.
[14] Efstathios D. Gennatas,et al. Predicting Regional Neurodegeneration from the Healthy Brain Functional Connectome , 2012, Neuron.
[15] D. Calvetti,et al. Uncertainty quantification in flux balance analysis of spatially lumped and distributed models of neuron–astrocyte metabolism , 2016, Journal of mathematical biology.
[16] D. Krainc,et al. α-synuclein toxicity in neurodegeneration: mechanism and therapeutic strategies , 2017, Nature Medicine.
[17] D. Mann,et al. Detection of elevated levels of soluble alpha-synuclein oligomers in post-mortem brain extracts from patients with dementia with Lewy bodies. , 2008, Brain : a journal of neurology.
[18] D. Calvetti,et al. A spatially distributed computational model of brain cellular metabolism. , 2015, Journal of theoretical biology.
[19] M. Duchen,et al. Crosstalk between Lysosomes and Mitochondria in Parkinson's Disease , 2017, Front. Cell Dev. Biol..
[20] P. Brundin,et al. Prying into the Prion Hypothesis for Parkinson's Disease , 2017, The Journal of Neuroscience.
[21] C. Dobson,et al. Nucleation-conversion-polymerization reactions of biological macromolecules with prenucleation clusters. , 2014, Physical review. E, Statistical, nonlinear, and soft matter physics.
[22] Carole J. Proctor,et al. An in silico model of the ubiquitin-proteasome system that incorporates normal homeostasis and age-related decline , 2007, BMC Systems Biology.
[23] P. Wellstead,et al. Continuous real-time in vivo measurement of cerebral nitric oxide supports theoretical predictions of an irreversible switching in cerebral ROS after sufficient exposure to external toxins. , 2013, Journal of Parkinson's disease.
[24] P. Nagabhushan,et al. Mathematical approach to understand the kinetics of α-synuclein aggregation: Relevance to Parkinson's disease , 2008, Comput. Biol. Medicine.
[25] Sébastien Ourselin,et al. Computational modelling of pathogenic protein spread in neurodegenerative diseases , 2018, PloS one.
[26] K. Kieburtz,et al. A review of disease progression models of Parkinson's disease and applications in clinical trials , 2016, Movement disorders : official journal of the Movement Disorder Society.
[27] E. Bézard,et al. Alpha‐synuclein propagation: New insights from animal models , 2016, Movement disorders : official journal of the Movement Disorder Society.
[28] Sylvie Retout,et al. Item Response Theory as an Efficient Tool to Describe a Heterogeneous Clinical Rating Scale in De Novo Idiopathic Parkinson’s Disease Patients , 2017, Pharmaceutical Research.
[29] Lama M Chahine,et al. Blood-based biomarkers for Parkinson's disease. , 2014, Parkinsonism & related disorders.
[30] R. Finke,et al. Protein aggregation kinetics, mechanism, and curve-fitting: a review of the literature. , 2009, Biochimica et biophysica acta.
[31] L. Clare,et al. Cognitive reserve in Parkinson's disease: a systematic review and meta-analysis. , 2014, Parkinsonism & related disorders.
[32] Yashar Sarbaz,et al. A review of presented mathematical models in Parkinson’s disease: black- and gray-box models , 2015, Medical & Biological Engineering & Computing.
[33] J. Jankovic,et al. Functional decline in Parkinson disease. , 2001, Archives of neurology.
[34] Carole J. Proctor,et al. Modelling the Role of UCH-L1 on Protein Aggregation in Age-Related Neurodegeneration , 2010, PloS one.
[35] Tuomas P. J. Knowles,et al. Kinetic model of the aggregation of alpha-synuclein provides insights into prion-like spreading , 2016, Proceedings of the National Academy of Sciences.
[36] Andreas Zell,et al. Parkinson’s disease: dopaminergic nerve cell model is consistent with experimental finding of increased extracellular transport of α-synuclein , 2013, BMC Neuroscience.
[37] Christopher M. Dobson,et al. Direct Observation of the Interconversion of Normal and Toxic Forms of α-Synuclein , 2012, Cell.
[38] Alexander K. Buell,et al. The role of stable α-synuclein oligomers in the molecular events underlying amyloid formation. , 2014, Journal of the American Chemical Society.
[39] Eberhard O. Voit,et al. Biochemical Systems Theory: A Review , 2013 .
[40] H. Braak,et al. Stanley Fahn Lecture 2005: The staging procedure for the inclusion body pathology associated with sporadic Parkinson's disease reconsidered , 2006, Movement disorders : official journal of the Movement Disorder Society.
[41] N. Bresolin,et al. Brain Mitochondria, Aging, and Parkinson’s Disease , 2018, Genes.
[42] S. Wieser,et al. Social Costs of Iron Deficiency Anemia in 6–59-Month-Old Children in India , 2015, PloS one.
[43] H. Nijhout,et al. Theoretical Biology and Medical Modelling Open Access Homeostatic Mechanisms in Dopamine Synthesis and Release: a Mathematical Model , 2022 .
[44] Jianhua Zhang,et al. Mitochondrial function and autophagy: integrating proteotoxic, redox, and metabolic stress in Parkinson's disease , 2018, Journal of neurochemistry.
[45] G. Porenta. A computer model of neuronal pathways in the basal ganglia. , 1986, Computer methods and programs in biomedicine.
[46] R. Chung,et al. Potential Modes of Intercellular α-Synuclein Transmission , 2017, International journal of molecular sciences.
[47] R. Finke,et al. Sigmoidal Nucleation and Growth Curves Across Nature Fit by the Finke–Watzky Model of Slow Continuous Nucleation and Autocatalytic Growth: Explicit Formulas for the Lag and Growth Times Plus Other Key Insights , 2017 .
[48] L. Kuhn,et al. Age at antiretroviral therapy initiation and cell-associated HIV-1 DNA levels in HIV-1-infected children , 2018, PloS one.
[49] I. Kuznetsov,et al. Mathematical models of α-synuclein transport in axons , 2016, Computer methods in biomechanics and biomedical engineering.
[50] D. Mann,et al. Post mortem cerebrospinal fluid α-synuclein levels are raised in multiple system atrophy and distinguish this from the other α-synucleinopathies, Parkinson's disease and Dementia with Lewy bodies , 2012, Neurobiology of Disease.
[51] Raymond J. Dolan,et al. Alterations in Brain Connectivity Underlying Beta Oscillations in Parkinsonism , 2011, PLoS Comput. Biol..
[52] A. Duncan,et al. Noise-induced multistability in chemical systems: Discrete versus continuum modeling. , 2014, Physical review. E, Statistical, nonlinear, and soft matter physics.
[53] Michele Vendruscolo,et al. Molecular mechanisms of protein aggregation from global fitting of kinetic models , 2016, Nature Protocols.
[54] Elodie Marcon,et al. Orthosteric Binding of ρ-Da1a, a Natural Peptide of Snake Venom Interacting Selectively with the α1A-Adrenoceptor , 2013, PloS one.
[55] C. Dobson,et al. Lipid vesicles trigger α-synuclein aggregation by stimulating primary nucleation. , 2015, Nature chemical biology.
[56] Robert L. Green,et al. A pragmatic approach to biochemical systems theory applied to an α-synuclein-based model of Parkinson's disease , 2009, Journal of Neuroscience Methods.
[57] M. Karlsson,et al. Modeling a Composite Score in Parkinson’s Disease Using Item Response Theory , 2017, The AAPS Journal.
[58] Elias S. Manolakos,et al. In silico modeling of the effects of alpha-synuclein oligomerization on dopaminergic neuronal homeostasis , 2014, BMC Systems Biology.
[59] Michelle M. McCarthy,et al. Striatal origin of the pathologic beta oscillations in Parkinson's disease , 2011, Proceedings of the National Academy of Sciences.
[60] B. Hayete,et al. Large-scale identification of clinical and genetic predictors of Parkinson’s disease motor progression in newly-diagnosed patients: a longitudinal cohort study and validation , 2017, The Lancet Neurology.
[61] Vladimir S Fonov,et al. Network connectivity determines cortical thinning in early Parkinson’s disease progression , 2017, Nature Communications.
[62] A. Fallgatter,et al. Alpha-Synuclein Levels in Blood Plasma Decline with Healthy Aging , 2015, PloS one.
[63] G. Morfill,et al. Observation of particle pairing in a two-dimensional plasma crystal. , 2013, Physical review. E, Statistical, nonlinear, and soft matter physics.
[64] V. Baekelandt,et al. Linking Neuroinflammation and Neurodegeneration in Parkinson's Disease , 2018, Journal of immunology research.
[65] J. Padiadpu,et al. Integrating glutathione metabolism and mitochondrial dysfunction with implications for Parkinson’s disease: A dynamic model , 2007, Neuroscience.
[66] P. Wellstead,et al. Dynamic modelling of protein and oxidative metabolisms simulates the pathogenesis of Parkinson's disease. , 2012, IET systems biology.
[67] C Laibe,et al. The Impact of Mathematical Modeling in Understanding the Mechanisms Underlying Neurodegeneration: Evolving Dimensions and Future Directions , 2017, CPT: pharmacometrics & systems pharmacology.
[68] María Suárez,et al. Computational design of proteins with new functions , 2007, BMC Systems Biology.
[69] R. Kream,et al. Gut, Microbiome, and Brain Regulatory Axis: Relevance to Neurodegenerative and Psychiatric Disorders , 2018, Cellular and Molecular Neurobiology.
[70] A. Hodgkin,et al. A quantitative description of membrane current and its application to conduction and excitation in nerve , 1952, The Journal of physiology.
[71] F. Gorin,et al. Dynamic modeling of alpha-synuclein aggregation for the sporadic and genetic forms of Parkinson’s disease , 2006, Neuroscience.
[72] A. Kuznetsov,et al. What can trigger the onset of Parkinson's disease - A modeling study based on a compartmental model of α-synuclein transport and aggregation in neurons. , 2016, Mathematical biosciences.
[73] D. Surmeier,et al. Parkinson's Disease Is Not Simply a Prion Disorder , 2017, The Journal of Neuroscience.
[74] Patrik Brundin,et al. Pathogenesis of parkinson's disease: dopamine, vesicles and α-synuclein , 2002, Nature Reviews Neuroscience.
[75] Martin A. Nowak,et al. Prion infection dynamics , 1998 .
[76] P. Wellstead,et al. Feedback motif for the pathogenesis of Parkinson's disease. , 2012, IET systems biology.
[77] Sarika Jalan,et al. The Human Body as a Super Network: Digital Methods to Analyze the Propagation of Aging , 2020, Frontiers in Aging Neuroscience.
[78] Neil Benson,et al. Systems Pharmacology: Bridging Systems Biology and Pharmacokinetics-Pharmacodynamics (PKPD) in Drug Discovery and Development , 2011, Pharmaceutical Research.
[79] Michele Vendruscolo,et al. Nucleated polymerization with secondary pathways. I. Time evolution of the principal moments. , 2011, The Journal of chemical physics.
[80] Elise M. Braatz,et al. A mathematical model of insulin resistance in Parkinson's disease , 2015, Comput. Biol. Chem..
[81] R. Finke,et al. Alpha-synuclein aggregation variable temperature and variable pH kinetic data: a re-analysis using the Finke-Watzky 2-step model of nucleation and autocatalytic growth. , 2009, Biophysical chemistry.
[82] M. Cloutier,et al. Metabolomics and In-Silico Analysis Reveal Critical Energy Deregulations in Animal Models of Parkinson’s Disease , 2013, PloS one.
[83] Alberto J Espay,et al. Disease Modification in Parkinson's Disease: Current Approaches, Challenges, and Future Considerations , 2018, Movement disorders : official journal of the Movement Disorder Society.
[84] Michael K. Bane,et al. High-resolution Fourier-transform infrared spectroscopy of the v6 and Coriolis perturbation allowed v10 modes of ketenimine. , 2011 .
[85] M. Jabbour,et al. Chromatid recommensuration after segmental duplication , 2009, Theoretical Biology and Medical Modelling.
[86] Eberhard O Voit,et al. Rotenone and paraquat perturb dopamine metabolism: A computational analysis of pesticide toxicity. , 2014, Toxicology.
[87] F. Oosawa,et al. A theory of linear and helical aggregations of macromolecules. , 1962, Journal of molecular biology.
[88] Mathieu Cloutier,et al. An energy systems approach to Parkinson's disease , 2011, Wiley interdisciplinary reviews. Systems biology and medicine.
[89] Raymond J. Dolan,et al. Anticipation and Choice Heuristics in the Dynamic Consumption of Pain Relief , 2015, PLoS Comput. Biol..
[90] Michele Vendruscolo,et al. Nucleated polymerization with secondary pathways. II. Determination of self-consistent solutions to growth processes described by non-linear master equations. , 2011, The Journal of chemical physics.
[91] Eberhard O. Voit,et al. Computational Systems Analysis of Dopamine Metabolism , 2008, PloS one.