bioservices
Connect Bioinformatics Databases with BioServices
Bioinformatics research often requires separate interfaces for proteins, pathways, compounds, and identifiers. This skill guides unified BioServices workflows across major biological databases.
Install with my Agent
Copy this request to your Agent. It includes the canonical Skill page and manifest.
Review the Skillstore skill "bioservices" from https://skillstore.io/skills/davila7-bioservices.md and its manifest at https://skillstore.io/api/skills/davila7-bioservices/manifest. Verify the artifact. You may proceed after verification, subject to the environment's own policy.Your Agent should still show its plan and request any confirmation required by the security policy.
Agent-readable resources
Use these links when an AI agent, crawler, or script needs clean context instead of reading the full page.
Test it
Using "bioservices". Find human ZAP70 and summarize its major database links.
Expected outcome:
- Primary UniProt record: P43403, with the matched protein name and organism.
- Mapped KEGG gene identifiers and associated pathways are listed with source labels.
- Missing or ambiguous links are marked for manual review.
Using "bioservices". Convert a UniProt identifier list to KEGG identifiers.
Expected outcome:
- Successful mappings are grouped by source identifier.
- One-to-many mappings remain separate instead of being collapsed.
- Unmapped identifiers are listed for retry or manual investigation.
Using "bioservices". Cross-reference aspirin across compound databases.
Expected outcome:
A concise comparison lists available KEGG, ChEBI, and ChEMBL identifiers, selected properties, linked pathways, and unavailable fields.
Security Audit
SafeAll 138 static findings are false positives caused by Markdown formatting, biological identifiers, harmless prose, and documented result exports. No dynamic execution, system reconnaissance, prompt injection, or malicious network intent was found. The workflows intentionally contact public biological services and may write user-selected output files.
Risk Factors
โก Contains scripts (2)
๐ Filesystem access (10)
โ๏ธ External commands (50)
๐ Network access (2)
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https://skillstore.io/skills/davila7-bioservices/audits/9?utm_source=security_passport&utm_medium=share&utm_campaign=versioned_reportMarkdown badge
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<a href="https://skillstore.io/skills/davila7-bioservices?utm_source=security_passport_badge"><img src="https://skillstore.io/badges/skills/davila7-bioservices/security.svg" alt="Skillstore security assessment" loading="lazy"></a>Embed card
<iframe src="https://skillstore.io/embed/skills/davila7-bioservices.html" title="Skillstore Security Assessment" sandbox="allow-popups allow-popups-to-escape-sandbox" loading="lazy" referrerpolicy="no-referrer" width="420" height="180"></iframe>Academic citations (APA ยท BibTeX ยท CFF)
APA citation
davila7. (2026). bioservices security audit report (audit version 9) [Author version unspecified]. Skillstore. https://skillstore.io/skills/davila7-bioservices/audits/9BibTeX citation
@techreport{davila7-davila7-bioservices-2026,
author = {davila7},
title = {bioservices security audit report (audit version 9)},
institution = {Skillstore},
year = {2026},
number = {9},
url = {https://skillstore.io/skills/davila7-bioservices/audits/9},
note = {Author version unspecified}
}CITATION.cff
cff-version: 1.2.0
message: "If you use this Skill, cite its author and this versioned security audit report."
title: "bioservices security audit report (audit version 9)"
version: "unspecified"
type: report
authors:
- name: "davila7"
date-released: "2026-07-23"
url: "https://skillstore.io/skills/davila7-bioservices/audits/9"
identifiers:
- type: other
value: "skillstore:davila7-bioservices:audit:9"
description: "Skillstore immutable audit report identifier"
Compare variants
2 installable variantsEach author remains a separate installable skill. The recommended variant is ranked by Skillstore evidence.
Why this variant is first
davila7-bioservices
2026-08-21
k-dense-ai-bioservices
2026-08-21
Skillstore Score
Why this score Evidence Confidence: HighWhat You Can Build
Characterize a Protein
Combine UniProt, BLAST, KEGG, interaction, and ontology results for an initial protein profile.
Map Identifier Collections
Convert large identifier lists between UniProt, KEGG, Ensembl, RefSeq, PDB, and related resources.
Build Research Data Pipelines
Integrate several biological services with chunking, export, error handling, and documented database links.
Try These Prompts
Use BioServices to find [protein name] in [organism]. Return the UniProt identifier, sequence length, and a concise annotation summary.
Convert these [source database] identifiers to [target database] identifiers: [list]. Report unmapped and one-to-many results separately.
Search [compound name] across KEGG, ChEBI, and ChEMBL. Compare identifiers, formula, molecular weight, and linked pathways, noting unavailable fields.
Design a reproducible BioServices workflow for [protein] covering UniProt, BLAST, KEGG pathways, interactions, and GO annotations. Include rate limits and failure handling.
Best Practices
- Specify the organism and source database to reduce ambiguous identifiers.
- Use small batches, delays, retries, and cached results for external service queries.
- Validate important mappings against source records before drawing scientific conclusions.
Avoid
- Do not treat the first search result as confirmed without checking the organism and record.
- Do not collapse one-to-many mappings into a single identifier.
- Do not run large unthrottled batches against public biological services.
Frequently Asked Questions
Which databases does this skill cover?
Does it require network access?
Can it process identifier files?
Why can identifier mappings return several results?
Does the protein workflow always run BLAST?
Are results suitable for clinical decisions?
Developer Details
Author
davila7License
MIT
Skillstore revision
r2
Version notice
The author did not declare a version.
Ref
c43861a65bb95efcae259cd161c9d6f4dc7eec6f
Maintenance freshness
7/24/2026
Usage
7 downloads ยท 250 views
File structure
๐ references/
๐ workflow_patterns.md
๐ scripts/
๐ compound_cross_reference.py
๐ pathway_analysis.py
๐ protein_analysis_workflow.py
๐ SKILL.md