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| <strong>Let's work together to unravel the mystery of Alzheimer's Disease.</strong> | | <strong>Advances biomedical science through integrating knowledge with quantitative models.</strong> |
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| "A full comprehension of the causes of a deadly disease is the essential prerequisite to find a cure."
| | This project aims to formalize and connect existing knowledge into predictive, multiscale modelling frameworks that can be evaluated against measurable data. |
| <ref>
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| Behl, Christian. Alzheimer’s Disease Research: What Has Guided Research So Far and Why It Is High Time for a Paradigm Shift (p. 6). Springer International Publishing. Kindle Edition.
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| </ref>
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| To find a cure for the disease, to find a disease changing medication, we must first understand the causal mechanisms at the origins of the disease, the aetiology. We currently have an incredible wealth of detailed knowledge relevant to the disease. What's needed is a means to integrate this knowledge to develop a more quantitative and rigorous science.
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| == Alzheimer’s Disease Multiscale Modelling Project ==
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| This initiative develops '''mechanistic, quantitative models''' of Alzheimer’s disease that connect molecular processes to brain-level observables.
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| Biological hypotheses are formalized mathematically, parameterized using published experimental data, and propagated across biological scales. Model predictions are evaluated against imaging, biomarker, neuropathological, and clinical measurements.
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| The project operates as an open, technically rigorous modeling laboratory.
| | == Mission == |
| | Our goal is to integrate biological knowledge through computational modeling |
| | to understand disease mechanisms. |
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| | == Approach == |
| | * Integrate published knowledge |
| | * Develop quantitative mechanistic models |
| | * Compare predictions with observations |
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| === Research Program === | | {| class="wikitable" style="background:#f8f9fa; border:1px solid #a2a9b1; padding:8px; width:85%;" |
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| | | '''How to Contribute''' |
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| We convert mechanistic hypotheses into testable, quantitative predictions.
| | Contributions are welcome from scientists with different backgrounds. Biologists and clinicians can help ensure that models remain grounded in experimental observations, while biophysicists and computational scientists can assist in translating mechanistic ideas into formal models. |
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| * Define biological mechanisms precisely
| | Contributors are invited to contact the site's founder ([mailto:robert.scott@univ-brest.fr robert.scott@univ-brest.fr]) or edit the pages directly as on Wikipedia. |
| * Express them in mathematical form
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| * Constrain parameters using experimental literature
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| * Scale effects from molecular to brain-level dynamics
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| * Compare predictions with independent datasets
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| [[Methodological Framework|Explore the Methodological Framework →]]
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| ----
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| === Multiscale Structure of Alzheimer’s Disease ===
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| Alzheimer’s disease spans interacting biological levels. Our modeling framework is organized accordingly:
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| * '''Molecular Level''' – Aβ aggregation kinetics, mutation-specific effects
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| * '''Cellular Level''' – Synaptic dysfunction, proteostasis disruption
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| * '''Network Level''' – Connectivity degradation, propagation dynamics
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| * '''Brain Level''' – Imaging biomarkers, regional atrophy patterns
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| * '''Clinical Level''' – Cognitive decline trajectories
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| [[Multiscale Organization|View Multiscale Organization →]] | |
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| ----
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| === Strategic Focus: Familial Alzheimer’s Disease ===
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| Initial efforts focus on genetically defined forms of Alzheimer’s disease.
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| Familial mutations provide:
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| * Clear causal perturbations
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| * Reduced biological heterogeneity
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| * Stronger mechanistic constraints
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| Active mutation-specific modeling programs include:
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| * [[Iowa Mutation Modeling Program|Iowa mutation (Aβ Asp23Asn)]]
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| * [[London Mutation Modeling Program|London mutation]]
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| * Additional programs in development
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| [[Familial Alzheimer’s Modeling|See Active Modeling Programs →]]
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| === Model Validation Framework ===
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| Models are evaluated against multiple independent observables:
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| * CSF biomarker trajectories
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| * Amyloid PET progression
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| * Structural MRI atrophy
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| * Longitudinal cognitive decline
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| * Neuropathological findings
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| Predictions must be quantitatively testable and reproducible.
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| [[Validation Framework|Read About Validation Methods →]]
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| === Current Focus ===
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| '''Active modeling effort:'''
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| Mutation-specific aggregation kinetics (Iowa mutation) → scaling to predicted amyloid PET progression and age-of-onset shift.
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| === Collaboration ===
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| Technically serious collaboration is welcome in:
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| * Mathematical and computational modeling
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| * Parameter extraction from experimental literature
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| * Dataset integration and harmonization
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| * Independent validation and replication
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| * Critical evaluation of model assumptions
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| [[Collaboration|Contribution Guidelines →]]
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| ''This project aims to build cumulative, transparent, and quantitatively rigorous models of Alzheimer’s disease progression.''
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| | == Disease Programs == |
| | * [[Alzheimer's Disease]] |
| | * [[Carcinogenesis]] |
| | * (future diseases) |
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| == Getting started == | | == Getting started == |
Advances biomedical science through integrating knowledge with quantitative models.
This project aims to formalize and connect existing knowledge into predictive, multiscale modelling frameworks that can be evaluated against measurable data.
Our goal is to integrate biological knowledge through computational modeling
to understand disease mechanisms.
- Integrate published knowledge
- Develop quantitative mechanistic models
- Compare predictions with observations
| How to Contribute
Contributions are welcome from scientists with different backgrounds. Biologists and clinicians can help ensure that models remain grounded in experimental observations, while biophysicists and computational scientists can assist in translating mechanistic ideas into formal models.
Contributors are invited to contact the site's founder (robert.scott@univ-brest.fr) or edit the pages directly as on Wikipedia.
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