發(fā)布時間：2018-07-21 22:07

【摘要】： 研究背景:隨著多基因組測序計劃的完成,現(xiàn)在科學(xué)家們研究的重點逐漸轉(zhuǎn)向了探討基因功能以及它們之間相互調(diào)控網(wǎng)絡(luò)關(guān)系的研究。近幾年發(fā)展起來的基因芯片技術(shù)為我們進行大規(guī)模、平行的基因?qū)嶒炋峁┝酥匾氖侄�。作為一種高通量的測量方法,基因芯片技術(shù)可以在大規(guī)模的基因組甚至全基因組水平上同時檢測基因的表達情況。在生物的發(fā)展過程中,由于基因的表達不是孤立地進行的,而是要受到其它基因的調(diào)控,這種相互促進或相互制約的調(diào)控關(guān)系構(gòu)成了一個復(fù)雜的基因表達調(diào)控網(wǎng)絡(luò)。因此,要認識生命的本質(zhì),必須從整體出發(fā),探索基因之間相互調(diào)控網(wǎng)絡(luò)關(guān)系。本研究基于基因表達數(shù)據(jù),針對小腦組織發(fā)育過程中基因的調(diào)控網(wǎng)絡(luò)關(guān)系,從數(shù)學(xué)模型的角度出發(fā),描述基因之間的調(diào)控關(guān)系。 方法:首先,根據(jù)GO數(shù)據(jù)庫選擇了在7個時間點上均有表達的40個與小腦組織發(fā)育過程相關(guān)的基因。然后,從生物種群系統(tǒng)動力學(xué)的角度出發(fā),采用Lotka-Volterra方程建立基因之間的調(diào)控關(guān)系網(wǎng)絡(luò)。最后,通過求解方程,得到了每個基因表達的內(nèi)稟增長率和所選基因之間的調(diào)控矩陣,并進行了圖像可視化研究。 結(jié)果:利用Lotka-Volterra方程最終得到了每個基因表達的內(nèi)稟增長率和所選基因之間的調(diào)控矩陣,并進行了圖像可視化描述。 結(jié)論:生物種群系統(tǒng)動力學(xué)思想能夠合理地描述基因之間的調(diào)控關(guān)系,其結(jié)果符合生物學(xué)實際,并為進一步的生物學(xué)實驗提供了依據(jù)。
[Abstract]:Background: with the completion of the multi-genome sequencing project, the focus of scientists has gradually shifted to the study of gene function and their interregulatory networks. The gene chip technology developed in recent years provides an important means for us to carry out large-scale, parallel gene experiments. As a high-throughput measurement method, gene chip technology can simultaneously detect gene expression at the level of large genome and even whole genome. In the process of biological development, gene expression is not carried out in isolation, but is regulated by other genes. Therefore, in order to understand the nature of life, we must explore the relationship between genes. Based on the data of gene expression, this study describes the regulatory relationship between genes from the point of view of mathematical model, aiming at the regulatory network of genes during cerebellar tissue development. Methods: first, 40 genes related to cerebellar tissue development were selected according to go database. Then, the Lotka-Volterra equation is used to establish the regulatory network of genes from the point of view of population system dynamics. Finally, by solving the equation, the intrinsic growth rate of each gene expression and the regulatory matrix between the selected genes are obtained, and the image visualization is carried out. Results: by using Lotka-Volterra equation, the intrinsic growth rate of each gene expression and the regulatory matrix between the selected genes were obtained, and the image visualization was carried out. Conclusion: the idea of biological population system dynamics can reasonably describe the regulatory relationship between genes and the results are in line with the biological practice and provide a basis for further biological experiments.
【學(xué)位授予單位】：重慶醫(yī)科大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2007
【分類號】：R346

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