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| 1 | A novel vector of topological and structural information for amino acids and its QSAR applications for peptides and analogues显示文摘A new descriptor, called vector of topological and structural information for coded and noncoded amino acids (VTSA), was derived by principal component analysis (PCA) from a matrix of 66 topological and structural variables of 134 amino acids. The VTSA vector was then applied into two sets of peptide quantitative structure-activity relationships or quantitative sequence-activity modelings (QSARs/ QSAMs). Molded by genetic partial least squares (GPLS), support vector machine (SVM), and immune neural network (INN), good results were obtained. For the datasets of 58 angiotensin converting en-zyme inhibitors (ACEI) and 89 elastase substrate catalyzed kinetics (ESCK) , the R2, cross-validation R2, and root mean square error of estimation (RMSEE) were as follows: ACEI, R2cu≥0.82, Q2cu≥0.77, Ermse≤0.44 (GPLS+SVM); ESCK, R2cu≥0.84, Q2cu≥0.82, Ermse≤0.20 (GPLS+INN), respectively. | LI ZhiLiang LI GenRong SHU Mao SUN JiaYing YANG ShanBin MEI Hu ZHANG MengJun ZHOU Ping WU ShiRong CHEN GuoHua LU FengLin LU TingTing | 2008 | Science China Chemistry2008，51，10： | 2 |
| 2 | Application of the standard addition method for the determination of acrylamide in heat-processed starchy foods by gas chromatography with electron capture detector显示文摘 | Zhu Yonghong Li Genrong Duan Yunpeng | 2008 | Food Chemistry2008，109，： | 1 |
| 3 | Direct determination of free tryptophan contents in soy sauces and its application as an index of soy sauce adulteration显示文摘 | Yonghong Zhu Yan Yang Zhaoxu Zhou Genrong Li Mei Jiang Chun Zhang Shiqi Chen | 2009 | Food Chemistry2009，，1： | 1 |
| 4 | Integration of genetic virtual screening patterns and latent multivariate modeling techniques for QSAR optimization based on combinations and/or interactions between peptides and proteins显示文摘Both the concept and the model of snug quantitative structure-activity relationship (QSAR) were pro-posed and developed for molecular design through constructing QSAR based on some known mode of receptor/ligand interactions. Many disadvantages of traditional models can be avoided by using the proposed method because the traditional models only determined upon molecular structural features in sample sets themselves. A genetic virtual screening of peptide/protein combinations (GVSPPC) is proposed for the first time by utilizing this idea to examine peptide/protein affinity activities. A genetic algorithm (GA) was developed for screening combinative targets with an interaction mode for virtual receptors. GVSPPC succeeds in disposing difficulties in rational QSAR,in order to search for the ligand/receptor interactions on conditions of unknown structures. Some bioactive oligo-/poly-peptide systems covering 58 angiotensin converting enzyme (ACE) inhibitors and 18 double site mutation residues in camel antibody protein cAb-Lys3 were investigated by GVSPPC with satisfactory results (R 2 cu>0.91,Q 2 cv > 0.86,ERMS=0.19-0.95),respectively,which demonstrates that GVSPPC is more inter-pretable in the ligand-receptor interaction than the traditional QSAR method. | LI ZhiLiang TIAN FeiFei WU ShiRong YANG ShanBin YANG ShengXi ZHOU Yuan ZHANG QiaoXia QIN RenHui MEI Hu CHEN Gang LI GenRong | 2008 | Science China Chemistry2008，51，5： | 0 |
| 5 | Research Status of Toxicity and Residue Detection of High-risk Pesticide Adjuvants显示文摘The toxicity and environmental toxicity of high risk adjuvants in pesticide and their harms to human were introduced,and the detection methods of pesticide adjuvant residues in food in recent years were reviewed.The management status of pesticide adjuvants in various countries was also summarized.In view of risk monitoring results of pesticide(EC)adjuvants in Chongqing market,the potential effects of pesticide adjuvants on agricultural products were focused,to protect environment and prevent human from toxic pesticide adjuvants that missing risk assessments. | Li Genrong Yu Wenqin Xiao Zhaojing Gong Yingkun Lu Jiali Wang Jiansong | 2019 | Plant Diseases and Pests2019，10，4： | 0 |
| 6 | Recognition for avian influenza virus proteins based on support vector machine and linear discriminant analysis显示文摘Total 200 properties related to structural characteristics were employed to represent structures of 400 HA coded proteins of influenza virus as training samples. Some recognition models for HA proteins of avian influenza virus (AIV) were developed using support vector machine (SVM) and linear discriminant analysis (LDA). The results obtained from LDA are as follows: the identification accuracy (Ria) for training samples is 99.8% and Ria by leave one out cross validation is 99.5%. Both Ria of 99.8% for training samples and Ria of 99.3% by leave one out cross validation are obtained using SVM model, respectively. External 200 HA proteins of influenza virus were used to validate the external predictive power of the resulting model. The external Ria for them is 95.5% by LDA and 96.5% by SVM, respectively, which shows that HA proteins of AIVs are preferably recognized by SVM and LDA, and the performances by SVM are superior to those by LDA. | LIANG GuiZhao CHEN ZeCong YANG ShanBin MEI Hu ZHOU Yuan YANG Li ZHOU Peng YANG ShengXi SHU Mao LIAO ChunYang WU ShiRong LI GenRong HE Liu GAO JianKun Gan MengYu LI DeJing CHEN GuoPing WANG GuiXue LONG Sha JING JuHua ZHENG XiaoLin ZENG Hui ZHANG QiaoXia ZHANG MengJun YANG Qi TIAN FeiFei TONG JianBo WANG JiaoNa LIU YongHong LI Bo QIU LiangJia CAI ShaoXi ZHAO Na YANG Yan SU XiaLi SONG Jian CHEN MeiXia ZHANG XueJiao SUN JiaYing LI JingWei CHEN GuoHua CHEN Gang DENG Jie PENG ChuanYou ZHU WanPing XU LuoNan WU YuQuan LIAO LiMin LI Zhi LI Jun LU DaJun SU QinLiang HUANG ZhengHu ZHOU Ping LI ZhiLiang | 2008 | Science China Chemistry2008，51，2： | 0 |
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