Hypothesis Generation
spacering-net/codeg
Structured hypothesis formulation from observations. An agent skill from spacering-net/codeg.
Official agent skill
Biomarker Pathway Analysis
by aws-samples in aws-samples/amazon-bedrock-agents-healthcare-lifesciences
A skill your agent uses when a researcher needs to analyze biological pathways for biomarker discovery, map disease mechanisms to druggable targets using Reactome/KEGG, identify pathway enrichment…
Install Biomarker Pathway Analysis
$ npx skills add aws-samples/amazon-bedrock-agents-healthcare-lifesciences --skill biomarker-pathway-analysis -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install aws-samples/amazon-bedrock-agents-healthcare-lifesciences biomarker-pathway-analysis --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/aws-samples/amazon-bedrock-agents-healthcare-lifesciences.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/biomarker-pathway-analysis .claude/skills/biomarker-pathway-analysis && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "biomarker-pathway-analysis" agent skill from https://github.com/aws-samples/amazon-bedrock-agents-healthcare-lifesciences/tree/main/skills/biomarker-pathway-analysis into .claude/skills/biomarker-pathway-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "biomarker-pathway-analysis", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/aws-samples/amazon-bedrock-agents-healthcare-lifesciences/tree/main/skills/biomarker-pathway-analysisType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add aws-samples/amazon-bedrock-agents-healthcare-lifesciences --skill biomarker-pathway-analysis -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install aws-samples/amazon-bedrock-agents-healthcare-lifesciences biomarker-pathway-analysis --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/aws-samples/amazon-bedrock-agents-healthcare-lifesciences.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/biomarker-pathway-analysis .agents/skills/biomarker-pathway-analysis && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "biomarker-pathway-analysis" agent skill from https://github.com/aws-samples/amazon-bedrock-agents-healthcare-lifesciences/tree/main/skills/biomarker-pathway-analysis into .agents/skills/biomarker-pathway-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "biomarker-pathway-analysis", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add aws-samples/amazon-bedrock-agents-healthcare-lifesciences --skill biomarker-pathway-analysis -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install aws-samples/amazon-bedrock-agents-healthcare-lifesciences biomarker-pathway-analysis --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/aws-samples/amazon-bedrock-agents-healthcare-lifesciences.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/biomarker-pathway-analysis .cursor/skills/biomarker-pathway-analysis && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "biomarker-pathway-analysis" agent skill from https://github.com/aws-samples/amazon-bedrock-agents-healthcare-lifesciences/tree/main/skills/biomarker-pathway-analysis into .cursor/skills/biomarker-pathway-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "biomarker-pathway-analysis", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/aws-samples/amazon-bedrock-agents-healthcare-lifesciences.git --path skills/biomarker-pathway-analysis--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add aws-samples/amazon-bedrock-agents-healthcare-lifesciences --skill biomarker-pathway-analysis -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install aws-samples/amazon-bedrock-agents-healthcare-lifesciences biomarker-pathway-analysis --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/aws-samples/amazon-bedrock-agents-healthcare-lifesciences.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/biomarker-pathway-analysis .gemini/skills/biomarker-pathway-analysis && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "biomarker-pathway-analysis" agent skill from https://github.com/aws-samples/amazon-bedrock-agents-healthcare-lifesciences/tree/main/skills/biomarker-pathway-analysis into .gemini/skills/biomarker-pathway-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "biomarker-pathway-analysis", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install aws-samples/amazon-bedrock-agents-healthcare-lifesciences biomarker-pathway-analysisInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add aws-samples/amazon-bedrock-agents-healthcare-lifesciences --skill biomarker-pathway-analysis -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/aws-samples/amazon-bedrock-agents-healthcare-lifesciences.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/biomarker-pathway-analysis .github/skills/biomarker-pathway-analysis && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "biomarker-pathway-analysis" agent skill from https://github.com/aws-samples/amazon-bedrock-agents-healthcare-lifesciences/tree/main/skills/biomarker-pathway-analysis into .github/skills/biomarker-pathway-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "biomarker-pathway-analysis", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add aws-samples/amazon-bedrock-agents-healthcare-lifesciences --skill biomarker-pathway-analysis -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install aws-samples/amazon-bedrock-agents-healthcare-lifesciences biomarker-pathway-analysis --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/aws-samples/amazon-bedrock-agents-healthcare-lifesciences.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/biomarker-pathway-analysis .opencode/skills/biomarker-pathway-analysis && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "biomarker-pathway-analysis" agent skill from https://github.com/aws-samples/amazon-bedrock-agents-healthcare-lifesciences/tree/main/skills/biomarker-pathway-analysis into .opencode/skills/biomarker-pathway-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "biomarker-pathway-analysis", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
biomarker-pathway-analysis- GitHub stars
- 274
- Token cost
- ~1.2k tokens
- SKILL.md length
- 484 words
- Files
- 2 (incl. references)
- Skills in repo
- 12
- Repo updated
- First seen
- Licence
- MIT-0
At a glance
A skill your agent uses when a researcher needs to analyze biological pathways for biomarker discovery, map disease mechanisms to druggable targets using Reactome/KEGG, identify pathway enrichment…
- Works in 5 steps: Identify the gene set of interest → Query pathway databases → Map pathway hierarchy → …
- A researcher needs to analyze biological pathways for biomarker discovery
- SKILL.md covers When to use this skill, MCP Server: biomni-research, Workflow: Pathway-Based… and Pathway Analysis Patterns, plus 2 more sections
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
What it does
Biomarker Pathway Analysis is an agent skill from aws-samples/amazon-bedrock-agents-healthcare-lifesciences, published by the product's own GitHub organization. Use when a researcher needs to analyze biological pathways for biomarker discovery, map disease mechanisms to druggable targets using Reactome/KEGG, identify pathway enrichment from gene sets, or understand mechanism-of-action for candidate biomarkers.
Its SKILL.md is about 1.2k tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files, including reference files.
It sits in Research & Science. The licence is MIT-0.
When your agent uses it
- A researcher needs to analyze biological pathways for biomarker discovery
- Map disease mechanisms to druggable targets using Reactome/KEGG
- Identify pathway enrichment from gene sets
- Understand mechanism-of-action for candidate biomarkers
Example prompts
- “/biomarker-pathway-analysis”
Workflow steps
5 steps, taken from the step headings in SKILL.md.
What it can do on your machine
Read from SKILL.md and the folder at commit 9960565. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
No scripts in the folder and no shell commands in SKILL.md.
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Biomarker Pathway Analysis loads about 1.2k tokens when it runs. Until then it costs about 70 tokens; SKILL.md has 484 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
SKILL.md
The full file from aws-samples/amazon-bedrock-agents-healthcare-lifesciences at commit 9960565, republished under its MIT-0 licence (© aws-samples). 484 words, ~1,186 tokens.
Download SKILL.mdSave it as
.claude/skills/biomarker-pathway-analysis/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.- name
- biomarker-pathway-analysis
- description
- Use when a researcher needs to analyze biological pathways for biomarker discovery, map disease mechanisms to druggable targets using Reactome/KEGG, identify pathway enrichment from gene sets, or understand mechanism-of-action for candidate biomarkers.
Biomarker Pathway Analysis
When to use this skill
- Researcher asks which pathways a gene/biomarker belongs to
- Identify druggable targets within a disease pathway
- Map metagene clusters to biological mechanisms
- Understand mechanism-of-action for candidate biomarkers
- Perform pathway enrichment analysis on a gene set
MCP Server: biomni-research
Pathway analysis uses the biomni-research MCP server. Tools are discovered automatically — ask your question naturally and Claude will find the right tool.
Workflow: Pathway-Based Biomarker Discovery
Step 1: Identify the gene set of interest
Sources for gene sets:
- Output from
biomarker-database-analysis(top genes by p-value) - Known cancer driver genes (e.g., EGFR, KRAS, TP53, BRCA1/2)
- Metagene clusters from expression analysis
- Differentially expressed genes from cohort comparison
Step 2: Query pathway databases
Use the biomni-research server with natural language queries:
| Goal | Query approach |
|---|---|
| Find pathways for a gene | "EGFR signaling pathways in Reactome" |
| Find disease pathways | "pathways involved in non-small cell lung cancer" |
| Get pathway interactions | "protein interaction network for CDK4" via STRING |
| Validate drug targets | "CDK4 drug target tractability" via Open Targets |
| Cross-reference function | "CDK4 molecular function and biological process" via UniProt |
Step 3: Map pathway hierarchy
Reactome organizes pathways hierarchically. Navigate from broad to specific:
Top-level: Signal Transduction
-> RAS signaling
-> KRAS activation
-> Downstream effectors (RAF, MEK, ERK)Decision tree for pathway depth:
- Broad overview needed -> Query top-level pathways only
- Mechanism-of-action -> Drill into sub-pathways with specific reactions
- Drug target identification -> Find terminal nodes with known inhibitors
Step 4: Identify druggable targets in pathway
For each pathway hit, assess druggability:
Query Open Targets for tractability assessment:
- Small molecule tractable
- Antibody tractable
- Other modalities (PROTAC, gene therapy)
Check existing drugs:
- Approved drugs targeting this pathway node
- Clinical trial compounds (Phase I-III)
- Tool compounds for validation
Prioritize by:
- Distance from disease-associated node (closer = better)
- Number of approved drugs (validated target)
- Safety profile of existing modulators
Show full SKILL.md (197 more words)Show less
Step 5: Build pathway-to-biomarker rationale
Connect pathway findings back to biomarker candidates:
Gene (biomarker candidate)
-> Pathway membership (Reactome)
-> Disease relevance (pathway implicated in condition)
-> Mechanistic explanation (how gene contributes to disease)
-> Clinical utility (can measure this to stratify patients)Pathway Analysis Patterns
EGFR pathway in NSCLC:
- Query: EGFR, KRAS, ALK, ROS1, BRAF, MET, HER2, RET
- Pathways: RTK signaling, RAS-MAPK, PI3K-AKT-mTOR
- Biomarker implication: Mutation status predicts TKI response
Metagene cluster interpretation:
- Cluster of co-expressed genes -> query each for pathway membership
- Identify shared pathways -> that pathway drives the co-expression
- Example: GDF15, POSTN, VCAN cluster -> TGF-beta / extracellular matrix remodeling
Survival-associated pathway enrichment:
- Take top 10 genes by Cox regression p-value
- Query Reactome for each gene
- Count pathway overlaps (enrichment)
- Pathways with 3+ genes = significantly enriched
Decision Framework: When to Use Pathway Analysis
| Scenario | Recommended approach |
|---|---|
| Single gene of interest | Query Reactome + UniProt for function context |
| Gene panel (5-20 genes) | Pathway enrichment: find shared pathways |
| Drug target validation | Open Targets tractability + existing drugs |
| Mechanism explanation | Full pathway walk: gene -> pathway -> disease |
| Novel biomarker discovery | Combine pathway + expression + survival data |
Conventions
- Always report pathway evidence level (curated vs. inferred)
- Include Reactome stable IDs (R-HSA-xxxxx) for reproducibility
- For STRING interactions, use confidence threshold >= 0.7 (high confidence)
- When multiple pathways match, rank by: disease relevance > gene count > evidence level
- Cross-reference pathway findings with literature (PubMed) for validation
© aws-samples, MIT-0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
SKILL.md and 1 other file (references) in skills/biomarker-pathway-analysis of aws-samples/amazon-bedrock-agents-healthcare-lifesciences.
- SKILL.md
- references/.gitkeep
Open the folder on GitHubat commit 9960565
Compare with similar skills
Biomarker Pathway Analysis next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Biomarker Pathway Analysis this skillaws-samples/amazon-bedrock-agents-healthcare-lifesciences | 274 | — | ~1.2k | Automated safety check: Pass | MIT-0 | |
| Hypothesis Generationspacering-net/codeg | 3.8k | 15 repos | ~3.6k | Automated safety check: Notes | MIT | |
| GitHub Deep Researchbytedance/deer-flow | 83k | 5 repos | ~1.3k | Automated safety check: Pass | MIT | |
| Nature Paper CardYuan1z0825/nature-skills | 46k | 2 repos | ~2.1k | Automated safety check: Pass | Apache-2.0 | |
| Read arXiv Paperkarpathy/nanochat | 58k | 2 repos | ~494 | Automated safety check: Pass | MIT | |
| Content Research Writerweapp-tailwindcss/weapp-tailwindcss | 1.9k | 25 repos | ~3.5k | Automated safety check: Pass | MIT |
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Categories
Questions about Biomarker Pathway Analysis
What does Biomarker Pathway Analysis do?
A skill your agent uses when a researcher needs to analyze biological pathways for biomarker discovery, map disease mechanisms to druggable targets using Reactome/KEGG, identify pathway enrichment…. Biomarker Pathway Analysis is an agent skill from aws-samples/amazon-bedrock-agents-healthcare-lifesciences, published by the product's own GitHub organization. Use when a researcher needs to analyze biological pathways for biomarker discovery, map disease mechanisms to druggable targets using Reactome/KEGG, identify pathway enrichment from gene sets, or understand mechanism-of-action for candidate biomarkers.
When should I use Biomarker Pathway Analysis?
Biomarker Pathway Analysis fits situations like: A researcher needs to analyze biological pathways for biomarker discovery; map disease mechanisms to druggable targets using Reactome/KEGG; identify pathway enrichment from gene sets; understand mechanism-of-action for candidate biomarkers.
How do I install Biomarker Pathway Analysis in Claude Code?
Run `npx skills add aws-samples/amazon-bedrock-agents-healthcare-lifesciences --skill biomarker-pathway-analysis -a claude-code`. Or copy the skill folder (skills/biomarker-pathway-analysis in aws-samples/amazon-bedrock-agents-healthcare-lifesciences) into .claude/skills/biomarker-pathway-analysis in your project. Claude Code loads it when a task matches its description.
How do I install Biomarker Pathway Analysis in Codex?
Run `npx skills add aws-samples/amazon-bedrock-agents-healthcare-lifesciences --skill biomarker-pathway-analysis -a codex`. Or copy the skill folder (skills/biomarker-pathway-analysis in aws-samples/amazon-bedrock-agents-healthcare-lifesciences) into .agents/skills/biomarker-pathway-analysis in your project. Codex loads it when a task matches its description.
Can I use Biomarker Pathway Analysis in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add aws-samples/amazon-bedrock-agents-healthcare-lifesciences --skill biomarker-pathway-analysis -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/biomarker-pathway-analysis, .gemini/skills/biomarker-pathway-analysis, .github/skills/biomarker-pathway-analysis and .opencode/skills/biomarker-pathway-analysis in your project.
What does Biomarker Pathway Analysis need to run?
SKILL.md names no scripts, command-line tools or credentials: Biomarker Pathway Analysis is instructions for the agent only.
Does Biomarker Pathway Analysis access the network?
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Is Biomarker Pathway Analysis safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
What licence does Biomarker Pathway Analysis use?
Biomarker Pathway Analysis is published under the MIT-0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Biomarker Pathway Analysis use?
About 1.2k tokens (SKILL.md is roughly 4.7k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
What are the alternatives to Biomarker Pathway Analysis?
Skills that share tags, products or a category with Biomarker Pathway Analysis: Hypothesis Generation (spacering-net/codeg, 3.8k stars), GitHub Deep Research (bytedance/deer-flow, 83k stars), Nature Paper Card (Yuan1z0825/nature-skills, 46k stars) and Read arXiv Paper (karpathy/nanochat, 58k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Biomarker Pathway Analysis?
aws-samples (a GitHub organization, an official publisher) maintains it in aws-samples/amazon-bedrock-agents-healthcare-lifesciences, which has 274 GitHub stars. The repository holds 12 skills in this directory. The repository was last updated on October 1, 2026.
Source: aws-samples/amazon-bedrock-agents-healthcare-lifesciences on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.