ITR: A Novel Graph Database Architecture for Mining Discoveries from the Human Genome

Sutter图形数据库架构的目标是帮助生物学家理解人类基因组，使他们能够搜索基因之间功能和结构关系模式的基因组序列比对。序列比对是发现不同生物数据之间有意义的联系的关键，从而使完整的人类基因组有意义。然而，目前没有数据库被设计成查询所需的详细序列比对关系。Sutter架构旨在为基因组比对数据提供一个快速、灵活和直观的查询系统，该系统基于将整个图形数据库存储在一组索引中，可以直接查找任何项目以找到其关系。通过专注于索引，Sutter可以摆脱关系系统的固定的、不灵活的模式（表结构），同时保留其速度的一些基础。Sutter的一个主要设计目标是高效地实现基因组数据对象，使其能够在RAM中存储完整的基因组数据库，并实现更快的查询性能。Sutter的第一个应用是为基因组研究界提供在线资源，用于挖掘单核苷酸多态性、它们对蛋白质功能的影响以及绘制疾病基因。

The goal of the Sutter graph database architecture is to help biologists make sense of the human genome, by enabling them to search genome sequence alignments for patterns of functional and structural relationships between genes. Sequence alignments are the key for discovering meaningful connections between diverse biological data, to make sense of the completed Human Genome. Yet no current database is designed to query detailed sequence alignment relationships as is needed. The Sutter architecture is designed to provide a fast, flexible, and intuitive query system for genomic alignment data, based on storing the entire graph database in a set of indexes, enabling direct lookup for any item to find its relationships. By focusing on indexing, Sutter can move away from the fixed, inflexible schema (table structure) of relational systems, while retaining some of the basis of their speed. A major design goal of Sutter is to implement genomic data objects efficiently, enabling it to store a full genome database in RAM, and achieve dramatically faster query performance. Sutter's first application is to serve the genome research community as an online resource for mining single-nucleotide polymorphisms, their effects on protein function, and mapping disease genes.