Bioconductor Msbackendmassbank
bioMate-AI/biomate-bioconductor-kb
Mass spectrometry (MS) data backend supporting import and export of MS/MS library spectra from MassBank record files.
Official agent skill
Biomarker Database Analysis
by aws-samples in aws-samples/amazon-bedrock-agents-healthcare-lifesciences
A skill your agent uses when a researcher needs to query biomedical databases for biomarker discovery, build target profiles from UniProt/Open Targets/STRING, rank biomarker candidates by evidence…
Install Biomarker Database Analysis
$ npx skills add aws-samples/amazon-bedrock-agents-healthcare-lifesciences --skill biomarker-database-analysis -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install aws-samples/amazon-bedrock-agents-healthcare-lifesciences biomarker-database-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-database-analysis .claude/skills/biomarker-database-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-database-analysis" agent skill from https://github.com/aws-samples/amazon-bedrock-agents-healthcare-lifesciences/tree/main/skills/biomarker-database-analysis into .claude/skills/biomarker-database-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "biomarker-database-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-database-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-database-analysis -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install aws-samples/amazon-bedrock-agents-healthcare-lifesciences biomarker-database-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-database-analysis .agents/skills/biomarker-database-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-database-analysis" agent skill from https://github.com/aws-samples/amazon-bedrock-agents-healthcare-lifesciences/tree/main/skills/biomarker-database-analysis into .agents/skills/biomarker-database-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "biomarker-database-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-database-analysis -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install aws-samples/amazon-bedrock-agents-healthcare-lifesciences biomarker-database-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-database-analysis .cursor/skills/biomarker-database-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-database-analysis" agent skill from https://github.com/aws-samples/amazon-bedrock-agents-healthcare-lifesciences/tree/main/skills/biomarker-database-analysis into .cursor/skills/biomarker-database-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "biomarker-database-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-database-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-database-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-database-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-database-analysis .gemini/skills/biomarker-database-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-database-analysis" agent skill from https://github.com/aws-samples/amazon-bedrock-agents-healthcare-lifesciences/tree/main/skills/biomarker-database-analysis into .gemini/skills/biomarker-database-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "biomarker-database-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-database-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-database-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-database-analysis .github/skills/biomarker-database-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-database-analysis" agent skill from https://github.com/aws-samples/amazon-bedrock-agents-healthcare-lifesciences/tree/main/skills/biomarker-database-analysis into .github/skills/biomarker-database-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "biomarker-database-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-database-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-database-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-database-analysis .opencode/skills/biomarker-database-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-database-analysis" agent skill from https://github.com/aws-samples/amazon-bedrock-agents-healthcare-lifesciences/tree/main/skills/biomarker-database-analysis into .opencode/skills/biomarker-database-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "biomarker-database-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-database-analysis- GitHub stars
- 274
- Token cost
- ~1.1k tokens
- SKILL.md length
- 397 words
- Files
- 3 (incl. scripts, 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 query biomedical databases for biomarker discovery, build target profiles from UniProt/Open Targets/STRING, rank biomarker candidates by evidence…
- Works in 5 steps: Understand the schema before querying → Formulate and refine the SQL query → Execute and interpret results → …
- A researcher needs to query biomedical databases for biomarker discovery
- SKILL.md covers When to use this skill, MCP Servers Used, Workflow: Query Clinical… and Query Patterns, plus 1 more section
- Build target profiles from UniProt/Open Targets/STRING
What it does
Biomarker Database 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 query biomedical databases for biomarker discovery, build target profiles from UniProt/Open Targets/STRING, rank biomarker candidates by evidence strength, or generate SQL queries against clinical genomic databases.
Its SKILL.md is about 1.1k tokens, which your agent loads only when the skill is triggered. The skill folder holds 4 other files, including scripts and reference files.
It sits in Research & Science, covering Bioinformatics and SQL. It works with SQL and UniProt. The licence is MIT-0.
When your agent uses it
- A researcher needs to query biomedical databases for biomarker discovery
- Build target profiles from UniProt/Open Targets/STRING
- Rank biomarker candidates by evidence strength
- Generate SQL queries against clinical genomic databases
Example prompts
- “/biomarker-database-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
Ships 1 file in scripts/, which the agent can run.
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 Database Analysis loads about 1.1k tokens when it runs. Until then it costs about 69 tokens; SKILL.md has 397 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); the scripts in this folder 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). 397 words, ~1,140 tokens.
Download SKILL.mdSave it as
.claude/skills/biomarker-database-analysis/SKILL.md (or your agent's skills folder). This skill also uses 2 other files; get the full folder from GitHub.- name
- biomarker-database-analysis
- description
- Use when a researcher needs to query biomedical databases for biomarker discovery, build target profiles from UniProt/Open Targets/STRING, rank biomarker candidates by evidence strength, or generate SQL queries against clinical genomic databases.
Biomarker Database Analysis
When to use this skill
- Researcher asks to find biomarkers associated with a disease or cancer type
- Query clinical genomic databases for survival, gene expression, or mutation data
- Build protein/target profiles from biomedical databases
- Rank biomarker candidates by statistical evidence (p-value, effect size)
- Generate or optimize SQL for biomarker data retrieval
MCP Servers Used
biomni-research— for external biomedical database queries (UniProt, Open Targets, STRING, ClinVar)- Clinical genomic databases may use separate tools (Redshift/Athena) depending on deployment
Workflow: Query Clinical Genomic Database
Step 1: Understand the schema before querying
Always retrieve the database schema first to understand available tables and columns.
Tool: get_schema
Purpose: Retrieve table names, column names, data types, and descriptionsKey columns in a typical clinical genomic table:
case_id-- patient identifiersurvival_status-- alive/dead (boolean or 0/1)survival_duration-- time in days or years- Gene expression columns (e.g.,
gdf15,lrig1,cdh2,postn,vcan) - Clinical metadata:
age_at_histological_diagnosis,smoking_status,chemotherapy,histology
Step 2: Formulate and refine the SQL query
Decision tree for query type:
- Patient demographics -> Simple SELECT with WHERE/GROUP BY
- Biomarker expression -> SELECT gene columns with clinical filters
- Survival correlation -> SELECT survival_status, survival_duration, biomarker columns
- Cohort comparison -> GROUP BY with aggregation (COUNT, AVG)
Rules:
- Write queries as single lines (no newlines)
- Never modify column names from the schema
- Use aggregation (COUNT, AVG, GROUP BY) to reduce output size
- Always validate with
refine_sqlbefore execution
Tool: refine_sql
Input: sql (the query), question (rationale for this step -- not the user's original question)
Purpose: Optimize for efficiency, add aggregation, fix column referencesStep 3: Execute and interpret results
Tool: query_redshift (or query_database)
Input: The refined SQL query
Output: Row-level results from the clinical databaseShow full SKILL.md (173 more words)Show less
Step 4: Build target profiles from external databases
For deeper biomarker validation, use the biomni-research MCP server with natural language queries:
| Database | Query approach |
|---|---|
| UniProt | "CDK4 protein function, domains, post-translational modifications" |
| Open Targets | "CDK4 disease associations and genetic evidence scores" |
| STRING | "CDK4 protein-protein interaction network" |
| ClinVar | "CDK4 pathogenic variants and clinical significance" |
Step 5: Rank candidates by evidence strength
Scoring framework for biomarker prioritization:
| Evidence type | Weight | Source |
|---|---|---|
| Statistical significance (p < 0.05) | High | Cox regression from clinical data |
| Known pathogenic association | High | ClinVar, Open Targets |
| Protein interaction in disease network | Medium | STRING (confidence > 0.7) |
| Literature support (3+ publications) | Medium | PubMed |
| Gene expression differential | Medium | Clinical database |
| Functional annotation match | Low | UniProt |
Query Patterns
Find top biomarkers for survival:
SELECT survival_status, survival_duration, gdf15, lrig1, cdh2, postn, vcan FROM clinical_genomic WHERE chemotherapy = 'Yes'Cohort demographics:
SELECT smoking_status, COUNT(DISTINCT case_id) AS num_patients FROM clinical_genomic WHERE age_at_histological_diagnosis > 50 GROUP BY smoking_statusDisease-specific expression:
SELECT survival_status, COUNT(*) AS count FROM clinical_genomic WHERE histology = 'Adenocarcinoma' GROUP BY survival_statusKey Conventions
- Map survival_status:
False/Alive = 0,True/Dead = 1 - Expression values are continuous (higher = more expressed in tumor)
- Always include quality filters and use parameterized queries when available
- Store query results in shared memory for downstream agents (statistician, pathway analyst)
- When results exceed 100 rows, summarize with aggregation before presenting to user
© 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 2 other files (scripts, references) in skills/biomarker-database-analysis of aws-samples/amazon-bedrock-agents-healthcare-lifesciences.
- SKILL.md
- references/.gitkeep
- scripts/.gitkeep
Open the folder on GitHubat commit 9960565
Compare with similar skills
Biomarker Database 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 Database Analysis this skillaws-samples/amazon-bedrock-agents-healthcare-lifesciences | 274 | — | ~1.1k | Automated safety check: Pass | MIT-0 | |
| Bioconductor MsbackendmassbankbioMate-AI/biomate-bioconductor-kb | 804 | — | ~1k | Automated safety check: Pass | Custom licence | |
| Jgi LakehouseBioTender-max/awesome-bio-agent-skills | 197 | — | ~3.7k | Automated safety check: Pass | Custom licence | |
| SQL On Fhiraehrc/pathling | 137 | — | ~2.3k | Automated safety check: Pass | Apache-2.0 | |
| Pathling Pythonaehrc/pathling | 137 | — | ~4k | Automated safety check: Pass | Apache-2.0 | |
| AWS Storageaws/agent-toolkit-for-aws | 2.8k | — | ~5.8k | Automated safety check: Pass | Apache-2.0 |
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Questions about Biomarker Database Analysis
What does Biomarker Database Analysis do?
A skill your agent uses when a researcher needs to query biomedical databases for biomarker discovery, build target profiles from UniProt/Open Targets/STRING, rank biomarker candidates by evidence…. Biomarker Database 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 query biomedical databases for biomarker discovery, build target profiles from UniProt/Open Targets/STRING, rank biomarker candidates by evidence strength, or generate SQL queries against clinical genomic databases.
When should I use Biomarker Database Analysis?
Biomarker Database Analysis fits situations like: A researcher needs to query biomedical databases for biomarker discovery; build target profiles from UniProt/Open Targets/STRING; rank biomarker candidates by evidence strength; generate SQL queries against clinical genomic databases.
How do I install Biomarker Database Analysis in Claude Code?
Run `npx skills add aws-samples/amazon-bedrock-agents-healthcare-lifesciences --skill biomarker-database-analysis -a claude-code`. Or copy the skill folder (skills/biomarker-database-analysis in aws-samples/amazon-bedrock-agents-healthcare-lifesciences) into .claude/skills/biomarker-database-analysis in your project. Claude Code loads it when a task matches its description.
How do I install Biomarker Database Analysis in Codex?
Run `npx skills add aws-samples/amazon-bedrock-agents-healthcare-lifesciences --skill biomarker-database-analysis -a codex`. Or copy the skill folder (skills/biomarker-database-analysis in aws-samples/amazon-bedrock-agents-healthcare-lifesciences) into .agents/skills/biomarker-database-analysis in your project. Codex loads it when a task matches its description.
Can I use Biomarker Database 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-database-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-database-analysis, .gemini/skills/biomarker-database-analysis, .github/skills/biomarker-database-analysis and .opencode/skills/biomarker-database-analysis in your project.
What does Biomarker Database Analysis need to run?
SKILL.md names no scripts, command-line tools or credentials: Biomarker Database Analysis is instructions for the agent only.
Does Biomarker Database 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 Database 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. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.
What licence does Biomarker Database Analysis use?
Biomarker Database 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 Database Analysis use?
About 1.1k tokens (SKILL.md is roughly 4.6k 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 Database Analysis?
Skills that share tags, products or a category with Biomarker Database Analysis: Bioconductor Msbackendmassbank (bioMate-AI/biomate-bioconductor-kb, 804 stars), Jgi Lakehouse (BioTender-max/awesome-bio-agent-skills, 197 stars), SQL On Fhir (aehrc/pathling, 137 stars) and Pathling Python (aehrc/pathling, 137 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Biomarker Database 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.