在人類基因體計劃的推動之下而產生大量新的生物數據，並且生物本體論已能提供生物概念模型而得以形成一個語意框架。此語意框架可以用來鞏固知識管理（KM）機制，促成生物研究中的有效地知識儲存，共享與資訊溝通。針對 DNA 序列分析，研究通常始於生物學家取得新的DNA 序列。在本研究中提出一個使用基因本體論(GO)於模糊相似度量測的知識組織機制來協助研究人員克服龐大資料分析的困難，並提供洞察許多生物組織的功能性為何。基於獨特地不斷延伸的本體論，一個加值型的知識庫與以語意為基礎的知識引擎將提供使用者量身訂作的精確分析結果。

Faced with the immensity of new biological data spurred by the Human Genome Project,
bio-ontologies have been generated to provide models of biological concepts to form a
semantic framework. Such a semantic framework can be used to underpin a knowledge
management (KM) mechanism to facilitate effective knowledge storage, sharing, and
communication across computers for biological research. With regards to DNA sequences,
the research process usually starts when biologists acquire new sequences. We propose a
knowledge organization mechanism using fuzzy measure similarity with Gene Ontology
(GO) to assist researchers by alleviating the difficulties of parsing through an immense
amount of data and providing insight into how various organisms function. Based on
particular evolving ontologies, a value-added knowledge base and semantic-based
knowledge agent were established to return precise results tailored for the user.