General solution of normal equations in the general intra-block analysis of partially balanced incomplete block designs involving four associates is presented in this talk as they are quite useful in practice. Only in...General solution of normal equations in the general intra-block analysis of partially balanced incomplete block designs involving four associates is presented in this talk as they are quite useful in practice. Only intra-block estimates are given as the necessary formulae for inter-block estimates can be derived from them by changing the parameters as discussed in Rao[5]. We have obtained the general formulae for computation of four types of efficiencies, the average efficiency factor and the variance of the estimated elementary treatment contrast of the four types of comparisons irrespective of the type of association scheme a PBIB Design follows.展开更多
Chloroplasts are organelles found in plant cells that conduct photosynthesis. The subchloroplast locations of proteins are correlated with their functions. With the availability of a great number of protein data, it i...Chloroplasts are organelles found in plant cells that conduct photosynthesis. The subchloroplast locations of proteins are correlated with their functions. With the availability of a great number of protein data, it is highly desired to develop a com- putational method to predict the subchloroplast locations of chloroplast proteins. In this study, we proposed a novel method to predict subchloroplast locations of proteins using tripeptide compositions. It first used the binomial distribution to optimize the feature sets. Then the support vector machine was selected to perform the prediction of subchloroplast locations of proteins. The proposed method was tested on a reliable and rigorous dataset including 259 chloroplast proteins with sequence identity ≤ 25%. In the jack-knife cross-validation, 92.21% envelope proteins, 93.20% thylakoid mem- brane, 52.63% thylakoid lumen and 85.00% stroma can be correctly identified. The overall accuracy achieves 88.03% which is higher than that of other models. Based on this method, a predictor called ChloPred has been built and can be freely available from http：//cobi.uestc.edu.cn/people/hlin/tools/ChloPred/. The predictor will provide important information for theoretical and experimental research of chloroplast proteins.展开更多
文摘General solution of normal equations in the general intra-block analysis of partially balanced incomplete block designs involving four associates is presented in this talk as they are quite useful in practice. Only intra-block estimates are given as the necessary formulae for inter-block estimates can be derived from them by changing the parameters as discussed in Rao[5]. We have obtained the general formulae for computation of four types of efficiencies, the average efficiency factor and the variance of the estimated elementary treatment contrast of the four types of comparisons irrespective of the type of association scheme a PBIB Design follows.
文摘Chloroplasts are organelles found in plant cells that conduct photosynthesis. The subchloroplast locations of proteins are correlated with their functions. With the availability of a great number of protein data, it is highly desired to develop a com- putational method to predict the subchloroplast locations of chloroplast proteins. In this study, we proposed a novel method to predict subchloroplast locations of proteins using tripeptide compositions. It first used the binomial distribution to optimize the feature sets. Then the support vector machine was selected to perform the prediction of subchloroplast locations of proteins. The proposed method was tested on a reliable and rigorous dataset including 259 chloroplast proteins with sequence identity ≤ 25%. In the jack-knife cross-validation, 92.21% envelope proteins, 93.20% thylakoid mem- brane, 52.63% thylakoid lumen and 85.00% stroma can be correctly identified. The overall accuracy achieves 88.03% which is higher than that of other models. Based on this method, a predictor called ChloPred has been built and can be freely available from http：//cobi.uestc.edu.cn/people/hlin/tools/ChloPred/. The predictor will provide important information for theoretical and experimental research of chloroplast proteins.
