利用Lotka-Volterra方程構建小腦組織發(fā)育中基因的調控網絡
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,現在科學家們研究的重點逐漸轉向了探討基因功能以及它們之間相互調控網絡關系的研究。近幾年發(fā)展起來的基因芯片技術為我們進行大規(guī)模、平行的基因實驗提供了重要的手段。作為一種高通量的測量方法,基因芯片技術可以在大規(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控,這種相互促進或相互制約的調控關系構成了一個復雜的基因表達調控網絡。因此,要認識生命的本質,必須從整體出發(fā),探索基因之間相互調控網絡關系。本研究基于基因表達數據,針對小腦組織發(fā)育過程中基因的調控網絡關系,從數學模型的角度出發(fā),描述基因之間的調控關系。 方法:首先,根據GO數據庫選擇了在7個時間點上均有表達的40個與小腦組織發(fā)育過程相關的基因。然后,從生物種群系統(tǒng)動力學的角度出發(fā),采用Lotka-Volterra方程建立基因之間的調控關系網絡。最后,通過求解方程,得到了每個基因表達的內稟增長率和所選基因之間的調控矩陣,并進行了圖像可視化研究。 結果:利用Lotka-Volterra方程最終得到了每個基因表達的內稟增長率和所選基因之間的調控矩陣,并進行了圖像可視化描述。 結論:生物種群系統(tǒng)動力學思想能夠合理地描述基因之間的調控關系,其結果符合生物學實際,并為進一步的生物學實驗提供了依據。
[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.
【學位授予單位】:重慶醫(yī)科大學
【學位級別】:碩士
【學位授予年份】:2007
【分類號】:R346
本文編號:2137009
[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.
【學位授予單位】:重慶醫(yī)科大學
【學位級別】:碩士
【學位授予年份】:2007
【分類號】:R346
【參考文獻】
相關期刊論文 前10條
1 谷俊峰,王希誠,趙金城;多序列漸進比對算法及其改進算法的研究與比較[J];大連大學學報;2005年02期
2 蔣太交,薛艷紅,徐濤;系統(tǒng)生物學——生命科學的新領域[J];生物化學與生物物理進展;2004年11期
3 侯雙興;鄧艷春;王小木;段麗;劉新平;藥立波;饒志仁;;發(fā)育相關基因ndrg2在胎兒小腦發(fā)育早期的表達[J];中華神經外科疾病研究雜志;2006年04期
4 王龍會,石峰;遺傳神經網絡及其在蛋白質二級結構預測中的應用[J];數學雜志;2002年02期
5 靳利霞,唐煥文;模擬退火算法的一種改進及其在蛋白質結構預測中的應用[J];系統(tǒng)工程理論與實踐;2002年09期
6 殷志祥,張家秀;神經網絡在蛋白質結構預測中的應用[J];中國科技信息;2005年11期
7 易東,楊夢蘇,李輝智,黃明輝,王文昌;相關分析在建立基因調控網絡中的應用[J];中國衛(wèi)生統(tǒng)計;2003年03期
8 雷耀山,史定華,王翼飛;基因調控網絡的生物信息學研究[J];自然雜志;2004年01期
9 李學禮,呂立夏,楊翠香,徐磊,吳曉春,向娟,王堯;新生大鼠小腦內發(fā)育相關基因的篩選[J];中國神經科學雜志;2002年02期
10 易東,李輝智;基因調控網絡研究與數學模型的建立[J];中國現代醫(yī)學雜志;2003年24期
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