進入後基因時代，蛋白質體學成為很多科學家有興趣的主題。蛋白質鑑定成為重要的一環，而質譜儀在縮氨酸分析及蛋白質鑑定中扮演重要的角色。腫瘤、卵巢癌及攝護腺癌等研究亦已成為質譜儀上的應用。Coombes 等人 (2004) 提出了一個線性的數學質譜儀模型，而且建議這個模型可被應用在建立質譜儀的模擬中。本文中，我們利用虛擬的質譜儀產生虛擬質譜資料並加以研究。虛擬的質譜實驗包括了前、後兩部份。樣本資料要放入虛擬質譜儀之前，可能出現的蛋白質其強度(intensity)必須先隨機地被決定，之後強度必須被轉換(calibration)變成離子化的個數(abundance) ；之後將樣本資料丟入虛擬質譜儀中，每一個蛋白值的飛行時間(time of flight， TOF) 將會被紀錄。另外一個轉換(calibration)是將飛行時間(TOF)轉成質量電荷比(mass-to-charge ratio，m/z)。質譜儀和兩個轉換都會在資料中產生誤差。在本文中，一個完整的模擬過程將會一步一步被介紹。同時，兩個轉換的方法所產生的誤差也會被探討。之後，我們將此模擬方法應用於模擬一組攝護腺癌中。 / Entering the post genomic era, proteomic has become the topic that scientists are interested in. The authentication of protein has been an important item of the topics. Mass spectrometry (MS) has become an important tool for peptide analysis or proteomic authentication. There are many applications of MS such as oncology, ovarian cancer, and prostate cancer. Coombes et al.(2004) proposed a mathematical model of a virtual spectrometer and suggested that the virtual spectrometer can be applied in conducting a MS simulation. In our study, we focus on designing a simulation study of spectrum data from a virtual MS experiment. The virtual experiment includes two stages: pre- and post-virtual spectrometer. Before the sample data are put into the virtual spectrometer, a virtual population of the intensity of all possible proteins should be determined; a virtual sample is randomly drawn; and the generated sample of intensity should be calibrated to abundance, which is the number of molecules ionized and desorbed from the biological sample. The sample data are then put into the virtual spectrometer and the time of flight (TOF) of each ionized molecule is recorded. Another calibration is employed to transfer a TOF to a mass-to-charge ratio (m/z). The spectrometer and the calibration processes produce variation in MS data. In this study, a complete simulation design of mass spectra will be introduced step by step. Moreover, the calibration effects caused from the two calibration procedures will be investigated. A simulation based on a real data set from a prostate cancer study will be also given as an illustration.