UniProt数据库API使用指南：蛋白质序列搜索、ID映射与批量检索教程

uniprot-database by davila7/claude-code-templates

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安装命令

npx skills add https://github.com/davila7/claude-code-templates --skill uniprot-database

生物信息学数据处理 API

🇨🇳中文介绍

UniProt 数据库

概述

UniProt 是全球领先的综合性蛋白质序列和功能信息资源。可通过名称、基因或登录号搜索蛋白质，以 FASTA 格式检索序列，跨数据库进行 ID 映射，通过 REST API 访问 Swiss-Prot/TrEMBL 注释以进行蛋白质分析。

何时使用此技能

此技能应在以下情况使用：

通过名称、基因符号、登录号或生物体搜索蛋白质条目
以 FASTA 或其他格式检索蛋白质序列
在 UniProt 和外部数据库（Ensembl、RefSeq、PDB 等）之间映射标识符
访问蛋白质注释，包括 GO 术语、结构域和功能描述
高效批量检索多个蛋白质条目
查询已审核（Swiss-Prot）与未审核（TrEMBL）的蛋白质数据
流式传输大型蛋白质数据集
使用特定字段搜索语法构建自定义查询

核心功能

1. 搜索蛋白质

使用自然语言查询或结构化搜索语法搜索 UniProt。

常见搜索模式：

# 按蛋白质名称搜索
query = "insulin AND organism_name:\"Homo sapiens\""

# 按基因名称搜索
query = "gene:BRCA1 AND reviewed:true"

# 按登录号搜索
query = "accession:P12345"

# 按序列长度搜索
query = "length:[100 TO 500]"

# 按分类学搜索
query = "taxonomy_id:9606"  # 人类蛋白质

# 按 GO 术语搜索
query = "go:0005515"  # 蛋白质结合

使用 API 搜索端点：https://rest.uniprot.org/uniprotkb/search?query={query}&format={format}

支持的格式： JSON, TSV, Excel, XML, FASTA, RDF, TXT

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2. 检索单个蛋白质条目

通过登录号检索特定的蛋白质条目。

登录号格式：

经典格式：P12345, Q1AAA9, O15530 (6 个字符：字母 + 5 个字母数字)
扩展格式：A0A022YWF9 (较新条目为 10 个字符)

检索端点： https://rest.uniprot.org/uniprotkb/{accession}.{format}

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

3. 批量检索和 ID 映射

在不同数据库系统之间映射蛋白质标识符，并高效检索多个条目。

ID 映射工作流程：

提交映射任务至：https://rest.uniprot.org/idmapping/run
检查任务状态：https://rest.uniprot.org/idmapping/status/{jobId}
检索结果：https://rest.uniprot.org/idmapping/results/{jobId}

支持映射的数据库：

UniProtKB AC/ID
基因名称
Ensembl, RefSeq, EMBL
PDB, AlphaFoldDB
KEGG, GO 术语
以及更多（参见 /references/id_mapping_databases.md）

每个任务最多 100,000 个 ID
结果存储 7 天

4. 流式传输大型结果集

对于超过分页限制的大型查询，请使用流式端点：

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

流式端点返回所有结果而无需分页，适用于下载完整数据集。

5. 自定义检索字段

精确指定要检索的字段，以实现高效的数据传输。

accession - UniProt 登录号
id - 条目名称
gene_names - 基因名称
organism_name - 生物体
protein_name - 蛋白质名称
sequence - 氨基酸序列
length - 序列长度
go_* - 基因本体注释
cc_* - 注释字段（功能、相互作用等）
ft_* - 特征注释（结构域、位点等）

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

完整字段列表请参见 /references/api_fields.md。

对于程序化访问，请使用提供的辅助脚本 scripts/uniprot_client.py，它实现了以下功能：

search_proteins(query, format) - 使用任何查询搜索 UniProt
get_protein(accession, format) - 检索单个蛋白质条目
map_ids(ids, from_db, to_db) - 在标识符类型之间映射
batch_retrieve(accessions, format) - 检索多个条目
stream_results(query, format) - 流式传输大型结果集

其他 Python 包：

Unipressed：用于 UniProt REST API 的现代、类型化的 Python 客户端
bioservices：全面的生物信息学网络服务客户端

布尔运算符：

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

特定字段搜索：

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

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

gene:BRCA*
protein_name:kinase*

全面的语法文档请参见 /references/query_syntax.md。

尽可能使用已审核条目：使用 reviewed:true 过滤 Swiss-Prot（人工管理）条目
明确指定格式：选择最合适的格式（序列用 FASTA，表格数据用 TSV，程序解析用 JSON）
使用字段选择：仅请求需要的字段以减少带宽和处理时间
处理分页：对于大型结果集，实现适当的分页或使用流式端点
缓存结果：本地存储频繁访问的数据以最小化 API 调用
速率限制：尊重 API 资源；为大型批量操作实施延迟
检查数据质量：TrEMBL 条目是计算预测；Swiss-Prot 条目是人工审核的

uniprot_client.py - Python 客户端，包含用于常见 UniProt 操作的辅助函数，包括搜索、检索、ID 映射和流式传输。

api_fields.md - 可用于自定义查询的完整字段列表
id_mapping_databases.md - 支持 ID 映射操作的数据库
query_syntax.md - 包含高级示例的全面查询语法
api_examples.md - 多种语言（Python, curl, R）的代码示例

API 文档：https://www.uniprot.org/help/api
交互式 API 浏览器：https://www.uniprot.org/api-documentation
REST 教程：https://www.uniprot.org/help/uniprot_rest_tutorial
查询语法帮助：https://www.uniprot.org/help/query-fields
SPARQL 端点：https://sparql.uniprot.org/（用于高级图查询）

2026 年 1 月 21 日

🇺🇸English

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:

Submit mapping job to: https://rest.uniprot.org/idmapping/run
Check job status: https://rest.uniprot.org/idmapping/status/{jobId}
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

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

API Documentation : https://www.uniprot.org/help/api
Interactive API Explorer : https://www.uniprot.org/api-documentation
REST Tutorial : https://www.uniprot.org/help/uniprot_rest_tutorial
Query Syntax Help : https://www.uniprot.org/help/query-fields
SPARQL Endpoint : https://sparql.uniprot.org/ (for advanced graph queries)

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31,500 周安装

UniProt数据库API使用指南：蛋白质序列搜索、ID映射与批量检索教程

🇨🇳中文介绍

UniProt 数据库

概述

何时使用此技能

核心功能

1. 搜索蛋白质

相关 Skills

2. 检索单个蛋白质条目

3. 批量检索和 ID 映射

4. 流式传输大型结果集

5. 自定义检索字段

Python 实现

查询语法示例

最佳实践

资源

scripts/

references/

附加资源

🇺🇸English

UniProt Database

Overview

When to Use This Skill

Core Capabilities

1. Searching for Proteins

2. Retrieving Individual Protein Entries

3. Batch Retrieval and ID Mapping

4. Streaming Large Result Sets

5. Customizing Retrieved Fields

Python Implementation

Query Syntax Examples

Best Practices

Resources

scripts/

references/

Additional Resources

最新 Skills