生醫分析系統之語意整合

[[abstract]]這計畫提議建立一個知識系統，允許生物醫學的研究人員透過以自然語言查詢方 式，綜合查詢複雜的生物資訊數據及影像訊息。我們的數據庫的目標是使數據的輸 入更有效率的，更有組織性，容易取回，及使操作和綜合變得容易。此系統以阿茲海 默症作為研究的對象。這一個知識系統與傳統知識系統的基本的區別在於它支援複雜 的數據組織和一個強大的查詢界面。 SemanticObjects 是由美國加州大學Irvine 分校和日本NEC 共同開發的一個物件 相關的平台，目的是為建造一物件知識系統。它允許使用者有效的組織及儲存生物學 模式和數據成階層式的複雜物件。使用者可利用結構性的自然語言來查詢及利用此知 識系統的數據。 最後，我們將迅速地把這個以SemanticObjects 為主的知識系統成為網站應用。這 使其它的研究人員可分享及獲得是項研究的結果。 我們提議的系統由以下的數個模組組成，a) 文字採礦模組，b) microarry/SNP 模 組，c) 基因網路模組，d)影像模組和e)實驗模組。 This proposal suggests building a knowledge system that allows biomedical researchers to synthesize complex bioinformatics information and images data via natural language query. The goal of our database is to facilitate efficient data entry, organization, retrieval, manipulation and integration. The Alzheimer』s Disease was chosen as our study case. A fundamental distinction of the biological database addressed in this research and the others is that it supports both complex data organization and a powerful querying facility. SemanticObjects is an object-relational platform that has been jointly developed by University of California, Irvine and NEC Soft, Japan as a tool for building object knowledge systems. It allows users to efficiently organize and store biological models and data as complex objects that are hierarchically structured. User can query and manipulate the data in Structured Natural Language (SNL). Finally, we will rapidly deploy this SemanticObjects database into a web application. This makes it easy for the research community to share the results obtained from proposed research. Our proposed system consists of: a) a text mining module, b) a microarry/SNP module, c) a gene network module, d) an image module, and e) a web laboratory module