neuroresearch

Neuroscience research copilot, full pipeline: hypothesis generation -> literature review -> bioinformatics -> experiment design -> statistics & figures -> manuscript writing -> peer review -> submission -> NSFC grants. Hypothesis generation applies 11 innovation operators (assumption inversion, far-domain analogy, ontological reframe, anomaly-first...) yielding original candidates + a kill order, decoupled from evaluation. Domains: neurodegeneration, cerebrovascular disease, TBI/SCI, neuroinflammation, neuropsychiatry, neuro-oncology, glia/neurons/synapses, RNA-seq/scRNA-seq, PRISMA meta-analysis. Triggers: 文献/开题/生信/ 实验设计/统计作图/论文写作/标书 + neuroscience keywords. Standards: verifiable citations (PMID/DOI), versioned+seeded reproducible scripts, effect size + multiple-comparison correction. Python engine (matplotlib/scipy/statsmodels) with dependency self-check; R for bioinformatics. Deliverables default to Word (.docx). Excludes clinical diagnosis/treatment advice.

模型生成摘要（rules/v1 · 2026-09-21 20:39）：Neuroscience research copilot, full pipeline: hypothesis generation -> literature review
这是模型对公开材料的总结，不是官方声明，请以原链内容为准。

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版本	存档时间	内容哈希	内容
v1	2026-09-21 20:37	96dbd616	可取

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