【摘要】：隨著人類基因工程的高效進行,基因組測序數(shù)據(jù)快速的增加,產(chǎn)生了一門新興交叉學科——生物信息學。在生物信息學中人們不可能對所有的生物學數(shù)據(jù)進行實驗驗證,為了能進行更加有效地實驗,充分利用有限的實驗資源,對這些生物數(shù)據(jù)進行分析、整理和有效地預測就顯得十分的重要。 B淋巴細胞是人體內(nèi)十分重要的免疫細胞,其分化成熟于骨髓,進而在Th細胞輔助下,在外周的淋巴組織內(nèi)與抗原特異性結(jié)合,進一步分化為漿細胞,從而分泌抗體,進行免疫活動。B細胞成熟的重要標志就是細胞膜表達了免疫球蛋白IgM、IgD和Igα/Igβ鏈構(gòu)成的B細胞受體(BCR)。免疫球蛋白IgM、IgD能特異性的識別抗原,與抗原結(jié)合后,再通過電信號形式將信息傳遞給Igα/Igβ鏈,由Igα/Igβ鏈把信號傳遞到細胞內(nèi)部,促使B細胞的進一步分化,實現(xiàn)免疫應答。B細胞只有識別抗原(antigen)之后,在抗原的刺激作用下,才能啟動免疫應答,免疫作用得以發(fā)揮。由此可知,抗原在免疫系統(tǒng)中起著十分重要的作用�？乖且欢蔚鞍踪|(zhì)片段,它在免疫應答中能夠與免疫細胞受體結(jié)合,在免疫應答中起關(guān)鍵作用。通常將能與B淋巴細胞特異性結(jié)合的抗原,稱為B細胞表位。由此可見對B細胞表位的預測是特別的重要。 B細胞表位分為連續(xù)表位和不連續(xù)表位,對于不連續(xù)表位的預測需要確定抗原的空間三維結(jié)構(gòu),因此存在著很大的困難,目前國際上多數(shù)都是對連續(xù)B細胞表位進行理論篩選。為了對連續(xù)B細胞表位做出快速有效地初步理論篩選,提高鑒定實驗的成功率,本文應用改進的BP神經(jīng)網(wǎng)絡進行連續(xù)B細胞表位理論預測研究,并最終建立了B細胞表位的預測模型,與國內(nèi)外現(xiàn)有的同類預測模型相比,本模型具有更為優(yōu)越的預測表現(xiàn)(AUC=0.723)。為了進一步驗證模型的性能,本文應用建立的模型對環(huán)子孢子蛋白進行了預測,取得了更為滿意的效果。
[Abstract]:With the high efficiency of human genetic engineering, genome sequencing data increase rapidly, which has produced a new cross-discipline-bioinformatics. In bioinformatics, it is impossible to verify all the biological data. In order to be able to experiment more effectively and make full use of the limited experimental resources, we can analyze these biological data. B lymphocytes are the most important immune cells in the human body, which differentiate and mature in bone marrow, and then are assisted by Th cells. In peripheral lymphoid tissues, antigen-specific binding, further differentiation into plasma cells, secretion of antibodies, and maturation of immunoglobulin IgMN IgD and Ig 偽 / Ig 尾 chain B cell receptor (BCR). Is an important marker for the maturation of immunoglobulin. The immunoglobulin IgMU IgD can specifically recognize the antigen, bind to the antigen, then transmit the information to the Ig 偽 / Ig 尾 chain in the form of electrical signals, and the signal is transmitted to the cell interior by the Ig 偽 / Ig 尾 chain, which promotes the further differentiation of the B cell. The immune response. B cells can initiate the immune response only after the antigen (antigen) has been recognized and the immune response can be brought into play under the stimulation of the antigen. Therefore, antigens play a very important role in the immune system. Antigen is a fragment of protein that binds to immune cell receptors in immune responses and plays a key role in immune responses. B-cell epitopes are commonly referred to as B-cell epitopes that specifically bind to B lymphocytes. Therefore, the prediction of B cell epitopes is particularly important. B cell epitopes are divided into continuous epitopes and discontinuous epitopes. For the prediction of discontinuous epitopes, it is necessary to determine the three-dimensional structure of antigens. Therefore, there are great difficulties. At present, most of the continuous B cell epitopes are screened theoretically. In order to make rapid and effective theoretical screening of continuous B cell epitopes and improve the success rate of identification experiments, the improved BP neural network is used to predict the continuous B cell epitopes. Finally, the prediction model of B cell epitopes is established. Compared with the existing prediction models, this model has more superior prediction performance (AUC=0.723). In order to further verify the performance of the model, the model has been used to predict the ring sporozoite protein, and more satisfactory results have been obtained.
【學位授予單位】：大連理工大學
【學位級別】：碩士
【學位授予年份】：2011
【分類號】：R392

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1 蔣良孝 ,李超群;基于BP神經(jīng)網(wǎng)絡的函數(shù)逼近方法及其MATLAB實現(xiàn)[J];微型機與應用;2004年01期

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