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🛠️ Uniprotデータベース

uniprot-database

??ンパク質の情報を集めたデータベース「Uni

⏱ RAG構築 1週間 → 1日

📺 まず動画で見る(YouTube)

▶ 【衝撃】最強のAIエージェント「Claude Code」の最新機能・使い方・プログラミングをAIで効率化する超実践術を解説! ↗

※ jpskill.com 編集部が参考用に選んだ動画です。動画の内容と Skill の挙動は厳密には一致しないことがあります。

📜 元の英語説明(参考)

Direct REST API access to UniProt. Protein searches, FASTA retrieval, ID mapping, Swiss-Prot/TrEMBL. For Python workflows with multiple databases, prefer bioservices (unified interface to 40+ services). Use this for direct HTTP/REST work or UniProt-specific control.

🇯🇵 日本人クリエイター向け解説

一言でいうと

??ンパク質の情報を集めたデータベース「Uni

※ jpskill.com 編集部が日本のビジネス現場向けに補足した解説です。Skill本体の挙動とは独立した参考情報です。

⚠️ ダウンロード・利用は自己責任でお願いします。当サイトは内容・動作・安全性について責任を負いません。

🎯 このSkillでできること

下記の説明文を読むと、このSkillがあなたに何をしてくれるかが分かります。Claudeにこの分野の依頼をすると、自動で発動します。

📦 インストール方法 (3ステップ)

  1. 1. 上の「ダウンロード」ボタンを押して .skill ファイルを取得
  2. 2. ファイル名の拡張子を .skill から .zip に変えて展開(macは自動展開可)
  3. 3. 展開してできたフォルダを、ホームフォルダの .claude/skills/ に置く
    • · macOS / Linux: ~/.claude/skills/
    • · Windows: %USERPROFILE%\.claude\skills\

Claude Code を再起動すれば完了。「このSkillを使って…」と話しかけなくても、関連する依頼で自動的に呼び出されます。

詳しい使い方ガイドを見る →
最終更新
2026-05-17
取得日時
2026-05-17
同梱ファイル
1

💬 こう話しかけるだけ — サンプルプロンプト

  • Uniprot Database を使って、最小構成のサンプルコードを示して
  • Uniprot Database の主な使い方と注意点を教えて
  • Uniprot Database を既存プロジェクトに組み込む方法を教えて

これをClaude Code に貼るだけで、このSkillが自動発動します。

📖 Claude が読む原文 SKILL.md(中身を展開)

この本文は AI(Claude)が読むための原文(英語または中国語)です。日本語訳は順次追加中。

UniProt Database

Overview

UniProt is the world's leading comprehensive protein sequence and functional information resource. Search proteins by name, gene, or accession, retrieve sequences in FASTA format, perform ID mapping across databases, access Swiss-Prot/TrEMBL annotations via REST API for protein analysis.

When to Use This Skill

This skill should be used when:

  • Searching for protein entries by name, gene symbol, accession, or organism
  • Retrieving protein sequences in FASTA or other formats
  • Mapping identifiers between UniProt and external databases (Ensembl, RefSeq, PDB, etc.)
  • Accessing protein annotations including GO terms, domains, and functional descriptions
  • Batch retrieving multiple protein entries efficiently
  • Querying reviewed (Swiss-Prot) vs. unreviewed (TrEMBL) protein data
  • Streaming large protein datasets
  • Building custom queries with field-specific search syntax

Core Capabilities

1. Searching for Proteins

Search UniProt using natural language queries or structured search syntax.

Common search patterns:

# Search by protein name
query = "insulin AND organism_name:\"Homo sapiens\""

# Search by gene name
query = "gene:BRCA1 AND reviewed:true"

# Search by accession
query = "accession:P12345"

# Search by sequence length
query = "length:[100 TO 500]"

# Search by taxonomy
query = "taxonomy_id:9606"  # Human proteins

# Search by GO term
query = "go:0005515"  # Protein binding

Use the API search endpoint: https://rest.uniprot.org/uniprotkb/search?query={query}&format={format}

Supported formats: JSON, TSV, Excel, XML, FASTA, RDF, TXT

2. Retrieving Individual Protein Entries

Retrieve specific protein entries by accession number.

Accession number formats:

  • Classic: P12345, Q1AAA9, O15530 (6 characters: letter + 5 alphanumeric)
  • Extended: A0A022YWF9 (10 characters for newer entries)

Retrieve endpoint: https://rest.uniprot.org/uniprotkb/{accession}.{format}

Example: https://rest.uniprot.org/uniprotkb/P12345.fasta

3. Batch Retrieval and ID Mapping

Map protein identifiers between different database systems and retrieve multiple entries efficiently.

ID Mapping workflow:

  1. Submit mapping job to: https://rest.uniprot.org/idmapping/run
  2. Check job status: https://rest.uniprot.org/idmapping/status/{jobId}
  3. Retrieve results: https://rest.uniprot.org/idmapping/results/{jobId}

Supported databases for mapping:

  • UniProtKB AC/ID
  • Gene names
  • Ensembl, RefSeq, EMBL
  • PDB, AlphaFoldDB
  • KEGG, GO terms
  • And many more (see /references/id_mapping_databases.md)

Limitations:

  • Maximum 100,000 IDs per job
  • Results stored for 7 days

4. Streaming Large Result Sets

For large queries that exceed pagination limits, use the stream endpoint:

https://rest.uniprot.org/uniprotkb/stream?query={query}&format={format}

The stream endpoint returns all results without pagination, suitable for downloading complete datasets.

5. Customizing Retrieved Fields

Specify exactly which fields to retrieve for efficient data transfer.

Common fields:

  • accession - UniProt accession number
  • id - Entry name
  • gene_names - Gene name(s)
  • organism_name - Organism
  • protein_name - Protein names
  • sequence - Amino acid sequence
  • length - Sequence length
  • go_* - Gene Ontology annotations
  • cc_* - Comment fields (function, interaction, etc.)
  • ft_* - Feature annotations (domains, sites, etc.)

Example: https://rest.uniprot.org/uniprotkb/search?query=insulin&fields=accession,gene_names,organism_name,length,sequence&format=tsv

See /references/api_fields.md for complete field list.

Python Implementation

For programmatic access, use the provided helper script scripts/uniprot_client.py which implements:

  • search_proteins(query, format) - Search UniProt with any query
  • get_protein(accession, format) - Retrieve single protein entry
  • map_ids(ids, from_db, to_db) - Map between identifier types
  • batch_retrieve(accessions, format) - Retrieve multiple entries
  • stream_results(query, format) - Stream large result sets

Alternative Python packages:

  • Unipressed: Modern, typed Python client for UniProt REST API
  • bioservices: Comprehensive bioinformatics web services client

Query Syntax Examples

Boolean operators:

kinase AND organism_name:human
(diabetes OR insulin) AND reviewed:true
cancer NOT lung

Field-specific searches:

gene:BRCA1
accession:P12345
organism_id:9606
taxonomy_name:"Homo sapiens"
annotation:(type:signal)

Range queries:

length:[100 TO 500]
mass:[50000 TO 100000]

Wildcards:

gene:BRCA*
protein_name:kinase*

See /references/query_syntax.md for comprehensive syntax documentation.

Best Practices

  1. Use reviewed entries when possible: Filter with reviewed:true for Swiss-Prot (manually curated) entries
  2. Specify format explicitly: Choose the most appropriate format (FASTA for sequences, TSV for tabular data, JSON for programmatic parsing)
  3. Use field selection: Only request fields you need to reduce bandwidth and processing time
  4. Handle pagination: For large result sets, implement proper pagination or use the stream endpoint
  5. Cache results: Store frequently accessed data locally to minimize API calls
  6. Rate limiting: Be respectful of API resources; implement delays for large batch operations
  7. Check data quality: TrEMBL entries are computational predictions; Swiss-Prot entries are manually reviewed

Resources

scripts/

uniprot_client.py - Python client with helper functions for common UniProt operations including search, retrieval, ID mapping, and streaming.

references/

  • api_fields.md - Complete list of available fields for customizing queries
  • id_mapping_databases.md - Supported databases for ID mapping operations
  • query_syntax.md - Comprehensive query syntax with advanced examples
  • api_examples.md - Code examples in multiple languages (Python, curl, R)

Additional Resources

Limitations

  • Use this skill only when the task clearly matches the scope described above.
  • Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
  • Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.