由於近年來人類基因體的解碼，許多有關基因序列的研究大量地被發表。而生物學技術的進步，像是DNA microarrays以及在分子生物學上高產量的實驗，更促進了大量基因資料的散佈。這些豐富的知識大多以文獻記載的方式記錄下來。如何有效率並準確地擷取這些知識，已經是一個重要的課題。在如此大量的生物醫學文獻中，包含了許多基因的調控資訊。這些資訊對於生物醫學家來說，是相當重要又不易取得的。其中主要的困難來自於基因調控系統的複雜性。
對生物醫學家來說，如果要以人工從如此大量的文獻記錄中，擷取並獲得這些轉錄調控關係是非常地耗時耗力。因此，有效率的處理這些龐大且豐富的資源是必要的。我們的目標是發展一個自動化的基因調控關係探勘系統，藉由此系統能夠從大量的生物醫學文獻中，擷取出有包含調控關係資訊的文句。經由實驗的驗證，證明了我們所建立的系統能從大量的生物醫學文獻中，有效並準確地找出基因調控的資訊。

The decoding of human genome sequences and the improvement of biological techniques, like DNA microarrays, accelerates an overwhelming amount of biomedical knowledge recorded in texts. These texts often contain the latest finding in proteins, genes and small molecules. In these literatures, huge amounts of gene-related data are included, like the transcriptional regulation between the regulators and the target genes.
For the researchers, it takes lots of efforts to derive the information from the tremendous literatures. Therefore, we develop a precise and efficient system for retrieving the regulatory relationship from the tremendous literature. It automatically learning the writing styles of the regulatory sentences and apply a two-stage method to find out the correct sentences. Our system achieves a better precision rate than the existing systems in the first part of the ranked sentences.

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