Claude Skills by BioTender-max

> 2015年诺贝尔生理学或医学奖得主 | 阿维菌素/伊维菌素发现者 | 天然产物化学巨匠 ---

> 2025年诺贝尔生理学或医学奖得主，调节性T细胞（Treg）发现者，外周免疫耐受机制的奠基人。 ---

诺贝尔奖得主山中伸弥（Shinya Yamanaka）的认知框架。iPS诱导多能干细胞发现者，2012年诺贝尔生理学或医学奖。 核心镜片：临床痛点驱动的减法科学家——从24个因子削减到4个，从外科手术室走向诺贝尔奖。 触发词：「山中伸弥」「Yamanaka」「iPS细胞」「减法思维」「临床驱动研究」「化繁为简」。 调研来源：15+一手来源（Nobel官方、Cell论文、CiRA官网、多个采访），6个研究文件。 心智模型：4个 | 决策启发式：7条 | 诚实边界：5条

> 蒸馏自诺奖官网、学术论文、权威媒体。黑名单：知乎/微信/百度百科。 > 最后更新：2026-04-06 ---

> ⚕️ 2007年诺贝尔生理学或医学奖得主 | 胚胎干细胞先驱 | 基因打靶技术奠基人 > "I don't think I've ever not been a scientist." — Martin Evans

> 2019年诺贝尔生理学或医学奖得主，细胞氧气感知与适应机制（HIF/VHL/脯氨酰羟化酶通路）的发现者 ---

> 1997年诺贝尔生理学或医学奖 | 朊病毒/蛋白感染因子的发现

> 🧬 2022年诺贝尔生理学或医学奖 · 古基因组学之父 · "不可能的任务"专家 > *dna: anthropologist + molecular biologist + memoirist* ---

> 2018年诺贝尔生理学或医学奖得主 | PD-1免疫检查点发现者 | 京都大学

> 2013年诺贝尔生理学或医学奖得主，发现突触囊泡神经递质释放的分子机器（SNARE/Synaptotagmin机制）

诺贝尔医学奖得主屠呦呦（Tu Youyou, 2015）的思维框架蒸馏。 核心镜片：从传统智慧中提取科学灵感的"古今转化"思维；低温突破决策。 警告：信息密度低（公开演讲/访谈极少），心智模型基于有限素材推断，诚实边界篇幅大。 触发词：「屠呦呦视角」「青蒿素思维」「古今转化」「传统中药现代化」。

2024年诺贝尔生理学或医学奖得主Victor Ambros的思维框架与表达方式。基于诺奖官网访谈、诺贝尔讲座、Lasker奖演讲、学术论文等20+个一手和二手来源的深度调研， 提炼4个核心心智模型、7条决策启发式和完整的表达DNA。 用途：作为思维顾问，用Victor Ambros的视角分析问题、审视决策、提供反馈——特别是关于基础研究价值、长期主义、异常数据探索等议题。 当用户提到「用Ambros的视角」「Ambros会怎么看」「microRNA思维」「基础研究价值」「长期主义科学」时使用。

> **蒸馏对象**: William Cecil Campbell > **获奖年份**: 2015 > **获奖理由**: 与 Satoshi Ōmura 共享一半奖项，"发现针对线虫寄生虫感染的新型疗法" > **蒸馏引擎**: 女娲蒸馏引擎 v1 > **蒸馏日期**: 2026-04-06 ---

> 2019年诺贝尔生理学或医学奖 | 细胞感知与适应氧气供应 (HIF通路) | VHL抑癌蛋白→氧感知分子机制 ---

> 2016年诺贝尔生理学或医学奖得主，细胞自噬机制发现者。一人一显微镜，用酵母揭开细胞"自我吞噬"的奥秘。 ---

Browser automation via agent-browser CLI for web navigation, form filling, screenshots, scraping, login flows, and UI testing.

Critically review, score, compare, and rank one or more AI scientist outputs for biology, bioinformatics, computational life science, or adjacent research tasks. Trigger when the user asks to evaluate notebooks, code, figures, analyses, manuscripts, software, or final reports produced by AI scientists; compare multiple AI scientists on the same task; judge publication readiness; or audit rigor, reproducibility, novelty, and task completion. Do not use this skill to perform the original resear...

Search arXiv preprints through the official arXiv API and turn arXiv IDs into local Markdown summaries. Use when you need CS, math, physics, or quantitative biology preprints, especially recent submissions that may not yet appear in peer-reviewed literature indexes.

Create publication-quality matplotlib/seaborn charts with readable axes, tight layout, and curated palettes.

Functional annotation and taxonomy inference from sequence homology.

Assemble genomes/metagenomes and produce assembly QC artifacts.

Perform metagenomic binning with QuickBin, refinement, and QC with completeness/contamination checks.

Initialize a bioinformatics project scaffold with reproducible environments, schemas, and data cataloging. Use for new projects or repo setup.

Call genes and annotate basic features for prokaryotes, viruses, and eukaryotes.

Evaluate scientific rigor, methods, biases, and evidence quality for claims, papers, and study designs.

Build marker gene alignments and phylogenetic trees.

Design and scaffold bioinformatics pipelines using Prefect+Dask for local/distributed execution or Nextflow for HPC schedulers.

Cluster proteins into orthogroups and derive pangenome matrices.

Ingest, QC, and map reads with reproducible outputs. Use for raw read processing and coverage stats.

Aggregate results, train ML models, and produce reports with validated references.

Structure prediction and structure-based annotation.

Detect, classify, and QC viral contigs.

Generate reproducible Methods documentation from workflow run artifacts (Nextflow/Snakemake/CWL), including exact commands, versions, parameters, QC gates, and outputs.

Search bioRxiv preprints through the official bioRxiv API and locally filter titles, abstracts, and authors for keyword queries. Use when you need recent biology preprints, bioRxiv-native metadata, date-range scans, DOI lookups, or author shortlists that may not yet appear in peer-reviewed literature indexes.

Query the Crossref REST API for DOI validation, title search, citation metadata, and bibliography audits. Use when you need DOI lookup, title-to-DOI matching, or reference metadata cleanup.

Fetch current API and SDK documentation with the chub CLI. Use when writing or reviewing code against fast-changing APIs, especially when the user asks for the latest or current docs.

Queries JGI Lakehouse (Dremio) for genomics metadata from GOLD, IMG, Mycocosm, Phytozome. Downloads genome files from JGI filesystem using IMG taxon OIDs and links JGI taxon OIDs to read files through PMO/GOLD identifiers and JAMO. Use when working with JGI data, GOLD projects, IMG annotations, or downloading genomes.

Run a multi-agent scientific manuscript review with parallel specialist reviewers, disagreement checks, and an editor meta-review. Use when reviewing a manuscript, preprint, revision, or rebuttal in Codex or Claude Code.

Author, execute, and deliver reproducible analysis notebooks in marimo (default) or Jupyter, with all cells run end-to-end and figures embedded. Also converts between marimo and Jupyter on request.

Build production-ready Plotly Dash dashboards with consistent theming, clear layouts, and performant callbacks.

Search the PMC Open Access literature with polars-dovmed. Author structured JSON queries directly, then use the hosted API when an API key is available or fall back to local dovmed scan over PMC, bioRxiv, or both parquet corpora.

Structured, decision-ready review framework for AI/ML, computational biology, and bioscience proposals. Use when evaluating grant, project, or funding proposals.

Assess paper and journal impact using OpenAlex citation counts, optional Altmetric data, and curated journal impact-factor references. Use when comparing papers, journals, or literature shortlists by reach and influence.

Track and reconcile taxonomy updates across NCBI, GTDB, ICTV, and community eukaryote frameworks with versioned provenance.

Systematic workflow for clustering biological samples, features, or any quantitative data matrix. Implements multiple clustering algorithms with rigorous validation, comparison, and interpretation to identify meaningful data groupings.

Core DESeq2 workflow for RNA-seq differential expression analysis with count data.

✅ **Use when:** - You have an annotated scRNA-seq dataset (Seurat object with cell type labels) - You want to identify ligand-receptor interactions between cell types - You want to visualize communication networks (chord diagrams, bubble plots) - You want to find dominant sender/receiver cell populations - **Chains from** `scrnaseq-seurat-core-analysis` output (`seurat_processed.rds`)

Compare two groups of experiments to identify differential peak regions (DPR) or differentially methylated regions (DMR) using the ChIP-Atlas Diff Analysis API.

Find ChIP-seq peak enrichment near your genes using the official ChIP-Atlas Enrichment Analysis API.

Find target genes for any transcription factor using pre-computed ChIP-Atlas public ChIP-seq data.