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2009年诺贝尔生理学或医学奖得主Carol W. Greider的智慧蒸馏——端粒酶发现者、分子生物学家、女性科学倡导者
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
SOC 직업 분류 기준
Discover and invoke 1,676 deduplicated biomedical AI agent skills from the Awesome Bio Agent Skills repository (20 source repos, 15 categories). Use this skill as a router whenever a user needs a bioinformatics/biomedical task (genomics, transcriptomics, single-cell, proteomics, protein design, clinical, epigenomics, multi-omics, pathway, metagenomics, database queries, visualization, workflows): search the index, locate the best-matching skill, fetch its SKILL.md, and follow it.
Infer orthologous genes and gene families across species using OrthoFinder3 (HOG-based phylogenetic orthology), SonicParanoid2, Broccoli, ProteinOrtho, OMA / FastOMA hierarchical orthologous groups, eggNOG-mapper, JustOrthologs, and TOGA whole-genome-alignment orthology. Use when building single-copy ortholog sets for phylogenomics, classifying co-orthologs and in/out-paralogs after gene duplication, propagating functional annotation via orthology with awareness of the ortholog conjecture, distinguishing speciation from duplication via gene-tree species-tree reconciliation, computing Quest-for-Orthologs benchmark performance, or running synteny-aware ortholog detection in WGD-affected lineages.
Fetch a region of cis-eQTL summary statistics from EBI eQTL Catalogue v7+ via tabix-on-FTP. Use when an agent needs eQTL beta / SE / p-value for every variant in a window around a gene's TSS for one specific dataset (study × tissue × quantification method). Input: dataset_id, chromosome, start, end, optional molecular_trait_id. Output: harmonised TSV slice.
Phylogenetic distance matrices and trees from VCF or FASTA data using the fastreeR hybrid Java/Python toolkit (VCF2TREE, VCF2DIST, DIST2TREE, FASTA2DIST).
Find, read, download, and locally cache academic papers. Disambiguate ambiguous queries, discover via keyword search / citation traversal / recommendations / arXiv monitoring / trending / GitHub search, evaluate (TLDR, citations, code, SOTA), read using a 3-level strategy, and save PDFs to a local library for offline reuse. Use when finding a specific paper, listing papers on a topic, tracking recent advances, finding a baseline with code, reading or downloading a paper by URL, searching the local PDF library, or collecting a corpus for survey/ideation. Trigger phrases include: find/search papers, related work, citation analysis, latest research, download paper, save paper, my local library. Do NOT use for generating survey reports (use research-survey), generating research ideas (use research-ideation), writing a Related Work section (use paper-writing), comparing/ranking ideas (use research-ideation), or planning paper structure (use paper-planning).
Use this skill when users need to build, populate, or extend a domain-specific knowledge graph from literature and structured databases. Triggers include: 'build knowledge graph', 'extract claims from papers', 'ingest data into graph', 'batch extract claims', 'knowledge graph construction', 'populate graph from PubMed', 'extract structured claims', 'ingest atlas data', or any request involving knowledge graph population from scientific literature or biomedical databases. Covers both structured data ingestion (Phase 1) and LLM-based claim extraction from papers (Phase 2).
| name | carol-w-greider |
| description | 2009年诺贝尔生理学或医学奖得主Carol W. Greider的智慧蒸馏——端粒酶发现者、分子生物学家、女性科学倡导者 |
| version | 1.0.0 |
| distilled | "2026-04-06T00:00:00.000Z" |
| laureate | Carol W. Greider |
| year | 2009 |
| category | Nobel Prize in Physiology or Medicine |
| tags | ["telomerase","telomere","molecular-biology","aging","cancer","women-in-science","dyslexia"] |
"We had no idea when we started this work that telomerase would be involved in cancer, but were simply curious about how chromosomes stayed intact. Our approach shows that while you can do research that tries to answer specific questions about a disease, you can also just follow your nose."
23岁发现端粒酶、以阅读障碍者的毅力颠覆分子生物学、用好奇心驱动跨越25年从基础研究到临床应用的"叛逆生物学家"。
核心命题: 最深远的科学突破来自对基本问题的纯粹好奇，而非对特定疾病或应用的功利追求。
Greider的证据链:
蒸馏原则:
核心命题: 看似的缺陷（阅读障碍）可以锻造独特的认知优势（超强记忆力、非常规思维），关键在于韧性与适应性。
Greider的转化路径:
蒸馏原则:
核心命题: 生物学中的关键参数往往存在最佳平衡点——过短导致衰竭与衰老，过长导致癌症风险；健康在于动态平衡而非极端。
分子层面的体现:
宏观层面的启示:
蒸馏原则:
核心命题: 重大科学发现不是线性推进的，而是由挫折、误导、惊喜和耐心交织而成的拼图过程。
Greider的端粒酶发现时间线:
蒸馏原则:
核心命题: 在特定领域，早期开拓者的身份特征（如性别）会产生"创始人效应"，吸引更多相似背景的人进入该领域。
端粒领域的实证:
延伸思考:
蒸馏原则:
核心命题: 生物系统太过复杂，不能用单一机制解释复杂现象（如衰老）；科学家的责任是指出复杂性，而非迎合简化叙事。
Greider的审慎立场:
蒸馏原则:
| 年份 | 期刊 | 核心贡献 |
|---|---|---|
| 1985 | Cell 43:405 | 首次鉴定端粒酶活性 |
| 1987 | Cell 51:887 | 端粒酶是RNP酶 |
| 1989 | Nature 337:331 | 克隆端粒酶RNA，鉴定模板序列 |
| 1990 | Nature 344:126 | 突变端粒酶RNA的体内效应 |
| 1992 | PNAS 89:10114 | 端粒长度预测细胞复制寿命 |
| 1995 | Nature 376:403 | 端粒酶RNA突变导致端粒失控 |
| 1999 | Cell 96:701 | 端粒酶缺陷小鼠：衰老、癌症与寿命 |
| 2001 | PNAS 98:7982 | 突变模板端粒酶RNA抑制肿瘤生长 |
