定量构效关系在毒理学的研究和实践中发挥着重要的作用。
Quantitative structure activity relationship (QSAR) plays an obvious role in the study and use of toxicology.
目的研究了CTL表位与MHC分子结合的定量构效关系模型。
Objective To study the model of the quantitative structure-activity relationship (QSAR) CTL epitopes binding to MHC molecule.
该方法为建立定量构效关系(QSAR)模型奠定了生物学检测基础。
The method established the biological foundation for building quantitative structure-activity relationship (QSAR) model.
根据受体学说，进行定量构效关系(QSAR)研究，建立了QSAR方程。
According to the acceptor theory, the quantitative structure-activity relationship was studied and the QSAR equation was established.
本论文的第一章主要对定量构效关系研究方法、进展及其应用等进行了综述。
In the first part of the paper, a review of QSAR on its studying methods, progress and applications is presented.
介绍了环境污染物定量构效关系模型研究进展，并探讨了各种模型的优缺点。
The advancement of QSAR study for environmental pollutants is introduced, and advantages and disadvantages of every model are discussed.
本论文的第一章主要对定量构效关系和分子对接研究方法、进展及其应用等进行了综述。
In the first chapter of the paper, a review of QSAR and docking methods, progress and applications is presented.
本文采用定量构效关系的研究方法，对松花江45种有毒有机物的毒性进行了预测与理论研究。
The paper forecasts and studies the toxicity of 45 noxious organic compounds in Songhuajiang river by the study method of quantitative structure-activity relationship.
目的：从电子水平上探讨具有抗肿瘤活性的核苷酸还原酶抑制剂的定量构效关系（QSAR）。
Purpose: To study the QSAR of the ribonucleotide reductase inhibitors on the electron level.
第三章致力于吲唑脲类辣椒素受体（TRPV1）通道拮抗剂的定量构效关系（QSAR）研究。
The third chapter was devoted to the study of quantitative structure-activity relationship(QSAR) for indazolyl ureas as TRPV1 antagonists.
建立定量构效关系模型第一步是计算大量的分子描述符，下一步则是对这些描述符进行变量选择。
The first step in building a QSAR model is to calculate a great number of molecular descriptors, then the second is to select the descriptors most correlated to the studied object.
目的研究碳青霉烯类化合物的定量构效关系(Q SAR)，并进行新的碳青霉烯类化合物的分子设计。
Objective To study the quantitative structure-activity relationship (QSAR) of carbapenems and the design of new compounds.
介绍了生物活性多肽定量构效关系（QSAR）中化学结构描述符和建立数学模型统计方法的研究概况。
This paper introduced the study general situation of the chemical structure descriptors and statistical method of mathematical modeling in bioactivity polypeptide QSAR research.
作为一种局部逼近方法，自适应神经模糊推理系统(ANFIS)适于为药物定量构效关系(QSAR)建模。
Adaptive neural fuzzy inference system (ANFIS), as a local approximation approach, could be used to model the quantitative structure-activity relationship (QSAR) of medicine.
四参数的定量构效关系显著性较好，神经网络模式识别总识别率为98%，可较精确地预测化合物的抗癌活性。
The BP artificial neural network pattern recognition has a 98% accuracy, which may predict the activities of taxol analogues.
在本文中，我们采用了一种新的三维定量构效关系研究方法——本征值方法对抗氧化剂的构效关系进行了研究。
In this paper, Eigen Value Analysis, a 3-dimensional quantitative structure activity relationship (3-d QSAR) method, was employed to study antioxidant SAAR.
定量构效关系在毒理学的研究和实践中发挥着重要的作用。综述了定量构效关系在化合物毒性研究中的应用进展。
Quantitative structure activity relationship (QSAR) plays an obvious role in the study and use of toxicology. The prospect of application of QSAR in chemical toxicity research is summarized.
本论文第二、第三章利用量子化学参数结合分子拓扑指数以及疏水性参数等研究了88个苯基烷胺类致幻剂的定量构效关系。
In chapter 2 and 3 of the thesis, quantum, topological, and hydrophobic descriptors were combined to study the quantitative structure - activity relationship of 88 phenylalkylamines.
从化学定量构效关系、模式识别法、人工神经网络、波谱化学、多元校正分析法等方面对化学计量学在分析化学中的应用进行了综述。
Application of chemical metrology in the analytical chemistry were summarized in aspects of QSAR, chemical pattern recognition, ANN, spectrum chemistry and multi-proofread.
分子结构表征是定量构效关系研究的一个关键环节，结构描述子能否反映分子与生物活性相关的结构信息，决定了定量构效关系研究的成败。
Structural description is a key step in the QSAR studies. Whether the structural descriptors can reflect the structural variations determines the success of QSAR studies.
在定量的构效关系研究中，多重回归分析选人的参数，多是用穷举所有方程实现的。
You can carry out different types of robust regression analysis when your data are not suitable for conventional multiple regression analysis.
在定量的构效关系研究中，多重回归分析选人的参数，多是用穷举所有方程实现的。
You can carry out different types of robust regression analysis when your data are not suitable for conventional multiple regression analysis.
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