本文選題：模糊著色Petri網(wǎng)　切入點：模糊Petri網(wǎng)　出處：《天津科技大學(xué)》2016年碩士論文　論文類型：學(xué)位論文

【摘要】：基因芯片及高吞吐量的DNA測序機(jī)技術(shù)的發(fā)展導(dǎo)致了超大規(guī)模的基因組數(shù)據(jù)的集成,而將這些數(shù)據(jù)轉(zhuǎn)化為有價值的生物信息是目前人們面臨的最大挑戰(zhàn),同時也成為基因調(diào)控網(wǎng)絡(luò)研究中的一個新領(lǐng)域。此外研究和了解基因調(diào)控網(wǎng)絡(luò)因果關(guān)系以及對DNA序列功能的評價對人們生活具有重要意義。相對于國外,我國在這一新興領(lǐng)域的研究水平還是處于落后階段,因此本文將從兩個方面對基因調(diào)控的研究進(jìn)行完善:DNA序列可信度的預(yù)測和基因表達(dá)水平影響程度的預(yù)測。針對DNA序列可信度的預(yù)測問題,將模糊Petri網(wǎng)(FPN)與有色Petri網(wǎng)(CPN)相結(jié)合,提出了一種基于模糊有色Petri網(wǎng)(FCPN)的方法來對DNA堿基序列可信度預(yù)測的模糊推理過程進(jìn)行建模。模型中使用三個輸入變量來確定DNA堿基序列的可信度,分別為height,peakness和spacing。模型中的組成部分分別對應(yīng)著不同類型的模糊操作,如If—parts和Then-parts等規(guī)則。FCPN模型在模糊Petri網(wǎng)的基礎(chǔ)上結(jié)合了有色Petri網(wǎng),這就使FCPN方法在保證等量信息的同時,可以克服原有網(wǎng)絡(luò)規(guī)模大、計算步驟冗余、時間長的缺點,從而提供完整的結(jié)構(gòu)化表示。再此基礎(chǔ)上建立了 DNA堿基可信度推理的FCPN模型,并得出了最終結(jié)果,與FPN方法進(jìn)行比較,FCPN模型表現(xiàn)出較好的適應(yīng)性,簡化了模型的同時提高了預(yù)測的準(zhǔn)確性。針對基因表達(dá)水平影響程度的預(yù)測問題,提出一種基于逆向推理和模糊Petri網(wǎng)思想的算法來對激活/抑制和目標(biāo)基因間的調(diào)控關(guān)系進(jìn)行建模,即根據(jù)輸入的激活/抑制(activator/repressor)基因的表達(dá)水平來預(yù)測目標(biāo)基因表達(dá)水平值。該方法通過FPN模型對激活/抑制和目標(biāo)基因三基因的正向推理得出目標(biāo)基因表達(dá)值后,采用逆向推理理論對模型進(jìn)行返溯,并對結(jié)果和模型進(jìn)行分析。該模型不僅可以準(zhǔn)確的預(yù)測目標(biāo)基因的表達(dá)水平,很好的模擬了基因調(diào)控網(wǎng)絡(luò)的因果關(guān)系,而且得到了規(guī)則庫中具體的作用規(guī)則以及輸入基因?qū)δ繕?biāo)基因表達(dá)的影響程度,從而有助于制藥,疾病診斷等領(lǐng)域的研究與探索。最后通過實例對該模型進(jìn)行了驗證和分析。
[Abstract]:The development of gene chip and high throughput DNA sequencer technology has led to the integration of large scale genomic data, and transforming this data into valuable biological information is the biggest challenge that people are facing. It is also a new field in the research of gene regulation network. In addition, studying and understanding the causality of gene regulation network and evaluating the function of DNA sequence are of great significance to people's life. China's research level in this emerging field is still lagging behind. Therefore, in this paper, we will improve the prediction of the reliability of DNA sequences and the degree of influence of gene expression from two aspects. In order to predict the reliability of DNA sequences, we will combine fuzzy Petri nets with colored Petri nets. A method based on fuzzy colored Petri nets (FCPN) is proposed to model the fuzzy reasoning process of DNA base sequence reliability prediction. Three input variables are used to determine the reliability of DNA base sequence. The components of the model correspond to different types of fuzzy operations, such as If-parts and Then-parts rules. The model combines colored Petri nets on the basis of fuzzy Petri nets, which makes the FCPN method guarantee the same amount of information at the same time. It can overcome the shortcomings of large scale of original network, redundant calculation steps and long time, thus providing a complete structured representation. On this basis, the FCPN model of DNA base credibility reasoning is established, and the final result is obtained. Compared with the FPN method, the FCPN model has better adaptability, simplifies the model and improves the accuracy of prediction. An algorithm based on reverse reasoning and fuzzy Petri nets is proposed to model the relationship between activation / suppression and target genes. The expression level of target gene is predicted according to the expression level of activator / inhibitor / repressor.Then the target gene expression value is obtained by positive inference of activation / inhibition and target gene by FPN model. The reverse reasoning theory is used to backtrack the model, and the results and model are analyzed. The model can not only accurately predict the expression level of target gene, but also simulate the causality of gene regulation network. Moreover, the specific action rules in the rule base and the influence of input genes on the expression of target genes are obtained, which is helpful for the research and exploration of pharmaceutical and disease diagnosis fields. Finally, the model is verified and analyzed by an example.
【學(xué)位授予單位】：天津科技大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2016
【分類號】：Q811.4;TP301.1

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