Universal Protein Knowledgebase

The Global Protein Knowledgebase from The Data Developers is a definitive, AI-ready protein intelligence source delivered directly into your Snowflake environment. It is designed to eliminate hundreds of hours of data preparation by providing a pre-built, expert-validated solution that transforms complex UniProt data into a query-ready relational format. We perform the ongoing integration, cleaning, and harmonization of UniProt, making its rich data instantly accessible. This provides a unified view across multiple, logically linked tables, allowing your team to immediately explore: - **Core Protein Identity:** Access primary and secondary accession numbers , recommended protein names , and EC numbers in theproteins_data table. - **Deep Functional Annotations:** The comments_data table provides extensive details on protein function, including disease associations (disease_id, disease_description) , subcellular locations , biochemical reactions (reaction) , kinetic parameters , and tissue specificity. - **Genetic Information:** Connect proteins to their genetic origins with gene_name andsynonyms from thegenes_data table. - **Literature Evidence:** Seamlessly link proteins to their scientific evidence with direct access to publication titles , authors , and PubMed / PubMed Central IDs (pmid) in thereferences_data table. - **Sequence & Features:** Analyze protein sequences, stored in sequence_data , and investigate specific domains, sites, and regions with coordinates from thefeatures_data table. - **Integrated Database Cross-References:** Leverage pre-joined links to dozens of other critical life science databases via the database_references_data table. **Key Value & Features:** - **Accelerated AI & Analytics:** Utilize structured data containing full protein sequences (sequence_data) and detailed annotations (features_data, comments_data) to build superior ML models and run complex bioinformatics pipelines. - **Rich, Queryable Context:** Instantly join tables to connect proteins to diseases, genetic origins, cellular functions, and supporting literature from PubMed Central—all within a single, powerful SQL query. - **Zero ETL & Maintenance:** Through Snowflake Secure Data Sharing, you get instant, zero-copy access to a live dataset that is always current. This removes the need to build, manage, or maintain data pipelines. - **Intuitive Relational Schema:** Data is organized into clear, relational tables (e.g., proteins_data, comments_data, genes_data, references_data) making it easy for data scientists and analysts to drive discovery. **Top Use Case: Accelerated Drug Target Validation** Rapidly identify and validate novel drug targets. By joining protein data (proteins_data) with disease associations (comments_data) and literature evidence (references_data), researchers can quickly pinpoint proteins implicated in specific diseases and assess the strength of the supporting scientific evidence, dramatically shortening the early phases of drug discovery.

原始信息汇总

Universal Protein Knowledgebase 数据集概述

数据集基本信息

• 提供方: The Data Developers LLC
• 试用信息: 7天免费试用
• 更新频率: 每月
• 时间覆盖范围: 最近6个月
• 云区域可用性: AWS US West (Oregon)

数据集描述

• 核心内容: 全球蛋白质知识库，提供AI-ready的蛋白质智能数据
• 数据来源: UniProt数据集成、清理和协调
• 主要特点:
  • 预构建、专家验证的解决方案
  • 查询就绪的关系型格式
  • 提供统一的跨多表逻辑链接视图

数据表结构

• proteins_data: 核心蛋白质身份信息
• comments_data: 深度功能注释
• genes_data: 遗传信息
• references_data: 文献证据
• sequence_data: 蛋白质序列
• features_data: 序列特征
• database_references_data: 集成数据库交叉引用

关键价值与特点

• 加速AI与分析: 结构化数据包含完整蛋白质序列和详细注释
• 丰富的可查询上下文: 可即时连接蛋白质与疾病、遗传起源、细胞功能等
• 零ETL和维护: 通过Snowflake安全数据共享提供实时访问
• 直观的关系模式: 数据组织清晰，便于数据科学家和分析师使用

主要应用场景

• 加速药物靶点验证
• AI驱动的药物再利用
• 生命科学商业化
• 生物标志物驱动的临床试验设计

使用示例

1. 优先考虑未充分表征的疾病靶点

   • 识别与疾病相关的人类蛋白质
   • 查询示例包含蛋白质条目名称、推荐蛋白质名称、蛋白质存在证据等字段

2. 比较蛋白质组学用于宿主-病原体或进化研究

   • 提取和比较基于生物体和详细分类谱系的蛋白质信息
   • 查询示例包含蛋白质条目名称、推荐蛋白质名称、生物体名称等字段

联系方式

• 销售: [e-mail]
• 支持: [e-mail]

搜集汇总

背景与挑战

背景概述

Universal Protein Knowledgebase是一个基于UniProt的AI就绪蛋白质知识库，以关系型表结构在Snowflake环境中提供预清理和整合的数据，涵盖蛋白质身份、功能注释、遗传信息及文献证据等。它支持零ETL访问和丰富查询，旨在加速药物靶点验证等生物信息学分析，帮助研究人员快速获取蛋白质相关疾病和科学证据。