Bioconductor Keggrest logo

Bioconductor Keggrest

Organization
bioMate-AI
bioconductor-keggrest

A package that provides a client interface to the Kyoto Encyclopedia of Genes and Genomes (KEGG) REST API. Only for academic use by academic users belonging to academic institutions (see <https://www.kegg.jp/kegg/rest/>). Note that KEGGREST

Overview

PublisherbioMate-AI
Repositorybiomate-bioconductor-kb
Skill namebioconductor-keggrest
Stars
804
Forks
66
Bundled files
Instructions only
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by bioMate-AI on GitHub. Read the source before you install it.

Installation

Install the Bioconductor Keggrest AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/bioMate-AI/biomate-bioconductor-kb/tree/main/skills/genomics/keggrest
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/bioMate-AI/biomate-bioconductor-kb.git /tmp/biomate-bioconductor-kb
mkdir -p .claude/skills
cp -r /tmp/biomate-bioconductor-kb/skills/genomics/keggrest .claude/skills/bioconductor-keggrest
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Bioconductor Keggrest in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Bioconductor Keggrest on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Bioconductor Keggrest is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

KEGGREST

Dependencies & Environment

Package-intrinsic requirements from the Bioconductor landing page — reproduce in any R environment.

  • Version: 1.52.0 · Bioconductor: 3.23 · R: ≥ 4.6
  • Imports: httr, png, Biostrings
  • Install: BiocManager::install("KEGGREST")

When to Use

  • Exploring available KEGG databases and organisms using listDatabases() and keggList().
  • Retrieving specific KEGG entries, including amino acid (aaseq) or nucleotide (ntseq) sequences as AAStringSet or DNAStringSet objects using keggGet().
  • Downloading KEGG pathway maps as PNG images using keggGet() with the "image" option.
  • Searching for genes or compounds by keywords, chemical formulas, or exact mass using keggFind().
  • Converting between KEGG identifiers and external database IDs (e.g., NCBI Gene ID) using keggConv().

When NOT to Use

  • For commercial applications, use ReactomePA instead because the KEGG API is strictly restricted to academic use by academic institutions.
  • For offline or high-throughput batch queries of thousands of genes, use local annotation packages like org.Hs.eg.db instead to avoid server-side limitations.
  • For complex pathway network topology analyses, use KEGGgraph or ROntoTools instead.

Data Requirements

  • Valid Identifiers: Input queries must be valid KEGG identifiers (e.g., "hsa:10458", "path:hsa00010", "cpd:C00493") or supported external identifiers.
  • Internet Connection: An active internet connection is required to query the live KEGG REST API.

Key Parameters

  • database: The target KEGG database to query (e.g., "pathway", "organism", "compound", "genes").
  • query: The search term, identifier, or vector of identifiers to retrieve (e.g., "hsa:10458").
  • option: Specific query options for keggGet() (e.g., "aaseq", "ntseq", "image") or keggFind() (e.g., "formula", "exact_mass", "mol_weight").

Best Practices

  • Verify the target organism's official KEGG code (e.g., "hsa" for human, "eco" for E. coli) using keggList("organism") before running queries.
  • Limit keggGet() queries to a maximum of 10 identifiers at once, as the server restricts larger batches.
  • Use keggLink() to find relationships across databases, such as retrieving all pathways associated with specific genes.

Common Pitfalls

  • Truncated results from keggGet(): Occurs when supplying more than 10 inputs to keggGet(); fix this by batching requests into chunks of 10 or fewer.
  • Invalid organism code: Using common names instead of the official 3-4 letter KEGG code returns empty results; fix this by looking up the code with keggList("organism").
  • Commercial use violation: Occurs when using the package for non-academic purposes; fix this by switching to open-source databases like Reactome.

Alternatives

  • ReactomePA: For pathway analysis using the open-source, commercially unrestricted Reactome database.
  • clusterProfiler: For comprehensive enrichment analysis integrating KEGG and GO annotations locally.
  • AnnotationDbi: For local, offline mapping of gene IDs without relying on web APIs.

Citations

  • Tenenbaum D (2024). KEGGREST: Client-side REST access to the Kyoto Encyclopedia of Genes and Genomes (KEGG). R package version 1.46.0.
  • Kanehisa M, Goto S (2000). KEGG: kyoto encyclopedia of genes and genomes. Nucleic Acids Research, 28(1), 27-30.

References


Run this on BioMate

This skill is the knowledge layer — when, why, and how to use keggrest. To run this analysis on your own data with managed compute, automated QC, and reproducible outputs, use BioMate — free to start.

▶ Open keggrest on BioMate →

Frequently asked questions

What does the Bioconductor Keggrest AI skill do?

A package that provides a client interface to the Kyoto Encyclopedia of Genes and Genomes (KEGG) REST API. Only for academic use by academic users belonging to academic institutions (see <https://www.kegg.jp/kegg/rest/>). Note that KEGGREST

Why use Bioconductor Keggrest on TypingMind?

Because you install it once and use it with any model. Bioconductor Keggrest is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Bioconductor Keggrest in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/bioMate-AI/biomate-bioconductor-kb/tree/main/skills/genomics/keggrest. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Bioconductor Keggrest?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Bioconductor Keggrest?

As many as you like. As long as a model supports skills, you can use Bioconductor Keggrest with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Bioconductor Keggrest AI skill free?

It is published on GitHub by bioMate-AI. Check the repository for licensing terms. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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