《電子技術(shù)應(yīng)用》
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基于云計(jì)算的蛋白質(zhì)折疊空間結(jié)構(gòu)預(yù)測(cè)
電子技術(shù)應(yīng)用
徐勝超,,楊波,,王宏杰,毛明揚(yáng),,蔣金陵,,蔣大銳
廣州華商學(xué)院 數(shù)據(jù)科學(xué)學(xué)院
摘要: 構(gòu)建基于云計(jì)算的蛋白質(zhì)折疊空間結(jié)構(gòu)預(yù)測(cè)框架,通過(guò)數(shù)據(jù)云存儲(chǔ)設(shè)備獲取蛋白質(zhì)序列原始數(shù)據(jù),,采用HDFS(Hadoop Distributed File System)分布式存儲(chǔ)方式保存于云端,。資源和隊(duì)列管理器RQM(Resource Queue Management)開(kāi)啟云端虛擬機(jī)后,以之作為掃描節(jié)點(diǎn)(Sensor Node,, SN),,SN基于二維AB非格點(diǎn)模型建立最小蛋白質(zhì)分子能量?jī)?yōu)化函數(shù),采用局部搜索機(jī)制改進(jìn)的量子遺傳算法對(duì)其作優(yōu)化求解,。利用云端GPU設(shè)備處理模型訓(xùn)練數(shù)據(jù),,即可實(shí)現(xiàn)蛋白質(zhì)折疊空間結(jié)構(gòu)的自動(dòng)化預(yù)測(cè)。實(shí)驗(yàn)結(jié)果表明:蛋白質(zhì)序列能量勢(shì)函數(shù)計(jì)算結(jié)果更小,、執(zhí)行效率更高,、GDT-TS(Geothermal Development and Testing Tool Suite)評(píng)價(jià)指標(biāo)值更大。
中圖分類號(hào):TP393.4 文獻(xiàn)標(biāo)志碼:A DOI: 10.16157/j.issn.0258-7998.244973
中文引用格式: 徐勝超,,楊波,,王宏杰,等. 基于云計(jì)算的蛋白質(zhì)折疊空間結(jié)構(gòu)預(yù)測(cè)[J]. 電子技術(shù)應(yīng)用,,2024,,50(8):10-16.
英文引用格式: Xu Shengchao,Yang Bo,,Wang Hongjie,,et al. Cloud computing based spatial structure prediction of protein folding[J]. Application of Electronic Technique,2024,,50(8):10-16.
Cloud computing based spatial structure prediction of protein folding
Xu Shengchao,,Yang Bo,Wang Hongjie,,Mao Mingyang,,Jiang Jinling,Jiang Darui
School of Data Science,, Guangzhou Huashang College
Abstract: A prediction framework for the spatial structure of protein folding based on cloud computing is proposed and implemented. The original data of protein sequence is obtained through the data cloud storage unit and stored in the cloud using the HDFS distributed storage mode. After the resource and queue manager RQM (Requirements Quality Management) starts the cloud virtual machine, it is used as the Sensor Node which establishes the minimum protein molecular energy optimization function based on two-dimensional AB non-lattice model. The quantum genetic algorithm is adopted for local search mechanism to optimize its solution. The cloud GPU equipment is used to process the model training data to complete the automatic prediction of the spatial structure of protein folding. The experimental results show that the proposed approach can achieve the smaller calculation result of protein sequence energy potential function, the higher execution efficiency, and the higher GDT-TS (Geothermal Development and Testing Tool Suite) evaluation index value.
Key words : cloud computing,;protein folding;spatial structure prediction,;HDFS distributed storage,;local search mechanism,;quantum genetic algorithm

引言

蛋白質(zhì)定義為由共價(jià)鍵實(shí)現(xiàn)若干種氨基酸相連的多肽鏈,是生命活動(dòng)不可缺少的重要物質(zhì)[1-2],,因其高度參與,,方使生命體具有活性[3]。分析蛋白質(zhì)結(jié)構(gòu)與功能對(duì)揭秘生物生命奧秘具有極其顯著的研究意義[4-6],。

蛋白質(zhì)分子具有較高的復(fù)雜度,,直接通過(guò)能量函數(shù)確定蛋白質(zhì)分子能量與結(jié)構(gòu)的關(guān)系描述難以實(shí)現(xiàn)[7],因此,,各種優(yōu)化算法應(yīng)運(yùn)而生,。謝騰宇等人[8]為了準(zhǔn)確確定蛋白質(zhì)折疊空間結(jié)構(gòu),設(shè)計(jì)了兩步構(gòu)象空間搜索框架,,該方法雖具有較好的局部搜索性能,,但數(shù)據(jù)處理量很高,難以取得突出的數(shù)據(jù)處理效率,。包晨等人[9]構(gòu)建的多尺度卷積和循環(huán)神經(jīng)網(wǎng)絡(luò)預(yù)測(cè)模型能夠充分捕獲氨基酸序列局部以及長(zhǎng)程特征信息,,將其作為多層雙向長(zhǎng)短期記憶網(wǎng)絡(luò)的輸入,實(shí)現(xiàn)蛋白質(zhì)折疊空間結(jié)構(gòu)的確定,。徐勝超[10]提出基于云計(jì)算的蛋白質(zhì)折疊模擬計(jì)算,,研究了PERM算法的運(yùn)行流程和面向MapReduce的子任務(wù)劃分方式。上述方法在蛋白質(zhì)折疊空間結(jié)構(gòu)預(yù)測(cè)上是可行的,,但受優(yōu)化算法以及網(wǎng)絡(luò)訓(xùn)練參數(shù)量的影響,,使得蛋白質(zhì)折疊空間結(jié)構(gòu)預(yù)測(cè)計(jì)算量較高,面對(duì)龐大規(guī)模的數(shù)據(jù)處理量,,如何提高算法執(zhí)行效率成為當(dāng)下急需解決的問(wèn)題,。

云計(jì)算技術(shù)采用虛擬化技術(shù),能高效地聚集多個(gè)物理節(jié)點(diǎn)并行化方式實(shí)現(xiàn)大規(guī)模數(shù)據(jù)的高效處理,,在高性能科學(xué)計(jì)算領(lǐng)域得到了廣泛的認(rèn)可[11-12],。因此,本文提出基于云計(jì)算的蛋白質(zhì)折疊空間結(jié)構(gòu)預(yù)測(cè)方法,,本文云計(jì)算平臺(tái)的軟件在版本上比文獻(xiàn)[10]已經(jīng)提高了很多,,在精準(zhǔn)獲取蛋白質(zhì)構(gòu)象的同時(shí)提高算法的運(yùn)行效率。


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作者信息:

徐勝超,,楊波,王宏杰,,毛明揚(yáng),,蔣金陵,蔣大銳

(廣州華商學(xué)院 數(shù)據(jù)科學(xué)學(xué)院,,廣東 廣州 511300)


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