Prediction of protein functions from known genomic sequences is an important mission of bioinformatics. One approach is to classify proteins into functional catego- ries. We have therefore developed a method based on ...Prediction of protein functions from known genomic sequences is an important mission of bioinformatics. One approach is to classify proteins into functional catego- ries. We have therefore developed a method based on protein domain composition and the maximum likelihood estimation (MLE) algorithm to classify proteins according to functions. Using the Saccharomyces cerevisiae genome, we compared the effectiveness of the MLE approach with that of an intui- tive and simple method. The MLE method outperformed the simple method, achieving an estimated specificity of 75.45% and an estimated sensitivity of 40.26%. These results indicate that domain is an important feature of proteins and is closely related to protein function.展开更多
In generalized linear models with fixed design, under the assumption λ↑_n→∞ and other regularity conditions, the asymptotic normality of maximum quasi-likelihood estimator ^↑βn, which is the root of the quasi-li...In generalized linear models with fixed design, under the assumption λ↑_n→∞ and other regularity conditions, the asymptotic normality of maximum quasi-likelihood estimator ^↑βn, which is the root of the quasi-likelihood equation with natural link function ∑i=1^n Xi（yi -μ（Xi′β）） = 0, is obtained, where λ↑_n denotes the minimum eigenvalue of ∑i=1^nXiXi′, Xi are bounded p × q regressors, and yi are q × 1 responses.展开更多
文摘Prediction of protein functions from known genomic sequences is an important mission of bioinformatics. One approach is to classify proteins into functional catego- ries. We have therefore developed a method based on protein domain composition and the maximum likelihood estimation (MLE) algorithm to classify proteins according to functions. Using the Saccharomyces cerevisiae genome, we compared the effectiveness of the MLE approach with that of an intui- tive and simple method. The MLE method outperformed the simple method, achieving an estimated specificity of 75.45% and an estimated sensitivity of 40.26%. These results indicate that domain is an important feature of proteins and is closely related to protein function.
基金the National Natural Science Foundation of China under Grant Nos.10171094,10571001,and 30572285the Foundation of Nanjing Normal University under Grant No.2005101XGQ2B84+1 种基金the Natural Science Foundation of the Jiangsu Higher Education Institutions of China under Grant No.07KJD110093the Foundation of Anhui University under Grant No.02203105
文摘In generalized linear models with fixed design, under the assumption λ↑_n→∞ and other regularity conditions, the asymptotic normality of maximum quasi-likelihood estimator ^↑βn, which is the root of the quasi-likelihood equation with natural link function ∑i=1^n Xi（yi -μ（Xi′β）） = 0, is obtained, where λ↑_n denotes the minimum eigenvalue of ∑i=1^nXiXi′, Xi are bounded p × q regressors, and yi are q × 1 responses.
