The Experts below are selected from a list of 183831 Experts worldwide ranked by ideXlab platform
Irene A Chen - One of the best experts on this subject based on the ideXlab platform.
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analysis of in vitro evolution reveals the Underlying Distribution of catalytic activity among random sequences
Nucleic Acids Research, 2017Co-Authors: Abe Pressman, Janina E Moretti, Gregory W Campbell, Ulrich F Muller, Irene A ChenAbstract:The emergence of catalytic RNA is believed to have been a key event during the origin of life. Understanding how catalytic activity is distributed across random sequences is fundamental to estimating the probability that catalytic sequences would emerge. Here, we analyze the in vitro evolution of triphosphorylating ribozymes and translate their fitnesses into absolute estimates of catalytic activity for hundreds of ribozyme families. The analysis efficiently identified highly active ribozymes and estimated catalytic activity with good accuracy. The evolutionary dynamics follow Fisher's Fundamental Theorem of Natural Selection and a corollary, permitting retrospective inference of the Distribution of fitness and activity in the random sequence pool for the first time. The frequency Distribution of rate constants appears to be log-normal, with a surprisingly steep dropoff at higher activity, consistent with a mechanism for the emergence of activity as the product of many independent contributions.
Abe Pressman - One of the best experts on this subject based on the ideXlab platform.
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analysis of in vitro evolution reveals the Underlying Distribution of catalytic activity among random sequences
Nucleic Acids Research, 2017Co-Authors: Abe Pressman, Janina E Moretti, Gregory W Campbell, Ulrich F Muller, Irene A ChenAbstract:The emergence of catalytic RNA is believed to have been a key event during the origin of life. Understanding how catalytic activity is distributed across random sequences is fundamental to estimating the probability that catalytic sequences would emerge. Here, we analyze the in vitro evolution of triphosphorylating ribozymes and translate their fitnesses into absolute estimates of catalytic activity for hundreds of ribozyme families. The analysis efficiently identified highly active ribozymes and estimated catalytic activity with good accuracy. The evolutionary dynamics follow Fisher's Fundamental Theorem of Natural Selection and a corollary, permitting retrospective inference of the Distribution of fitness and activity in the random sequence pool for the first time. The frequency Distribution of rate constants appears to be log-normal, with a surprisingly steep dropoff at higher activity, consistent with a mechanism for the emergence of activity as the product of many independent contributions.
Ping Peng - One of the best experts on this subject based on the ideXlab platform.
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all admissible linear predictors in the finite populations with respect to inequality constraints under a balanced loss function
Journal of Multivariate Analysis, 2015Co-Authors: Ping Peng, Guikai Hu, Jian LiangAbstract:Under a balanced loss function, we investigate the admissible linear predictors of finite population regression coefficient in the inequality constrained superpopulation models with and without the assumption that the Underlying Distribution is normal. In Model I (non-normal case) with parameter space T1, the relation between admissible homogeneous linear predictors and admissible inhomogeneous linear predictors is characterized. Moreover, for Model I with parameter space T0, necessary and sufficient conditions for an inhomogeneous linear prediction to be admissible in the class of inhomogeneous linear predictors are given. In Model II (normal case) with parameter space T0, necessary conditions for an inhomogeneous linear predictor to be admissible in the class of all predictors are derived.
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linear admissible prediction of finite population regression coefficient under a balanced loss function
Journal of Mathematics, 2014Co-Authors: H U Guikai, Ping PengAbstract:In this paper, under a balanced loss function we investigate admissible prediction of finite population regression coefficient in superpopulation models with and without the assumption that the Underlying Distribution is normal, respectively. By using the statistical decision theory, necessary and sufficient conditions for a homogeneous linear predictor to be admissible in the class of homogeneous linear predictors are obtained in the non-normal case, we also obtain a sufficient and necessary condition for a homogeneous linear predictor to be admissible in the class of all predictors in the normal case, which generalize some relative results under quadratic loss to balanced loss function.
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Minimax estimator of regression coefficient in normal Distribution under balanced loss function
Linear Algebra and its Applications, 2012Co-Authors: Guikai Hu, Qingguo Li, Ping PengAbstract:Abstract This article investigates linear minimax estimators of regression coefficient in a linear model with an assumption that the Underlying Distribution is a normal one with a nonnegative definite covariance matrix under a balanced loss function. Some linear minimax estimators of regression coefficient in the class of all estimators are obtained. The result shows that the linear minimax estimators are unique under some conditions.
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all admissible linear estimators of a regression coefficient under a balanced loss function
Journal of Multivariate Analysis, 2011Co-Authors: Guikai Hu, Ping PengAbstract:Admissibility of linear estimators of a regression coefficient in linear models with and without the assumption that the Underlying Distribution is normal is discussed under a balanced loss function. In the non-normal case, a necessary and sufficient condition is given for linear estimators to be admissible in the space of homogeneous linear estimators. In the normal case, a sufficient condition is provided for restricted linear estimators to be admissible in the space of all estimators having finite risks under the balanced loss function. Furthermore, the sufficient condition is proved to be necessary in the normal case if additional conditions are assumed.
Andres E Houseman - One of the best experts on this subject based on the ideXlab platform.
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blood based profiles of dna methylation predict the Underlying Distribution of cell types a validation analysis
Epigenetics, 2013Co-Authors: Devin C Koestler, Brock C Christensen, Margaret R Karagas, Carmen J Marsit, Scott M Langevin, Karl T Kelsey, John K Wiencke, Andres E HousemanAbstract:The potential influence of Underlying differences in relative leukocyte Distributions in studies involving blood-based profiling of DNA methylation is well recognized and has prompted development of a set of statistical methods for inferring changes in the Distribution of white blood cells using DNA methylation signatures. However, the extent to which this methodology can accurately predict cell-type proportions based on blood-derived DNA methylation data in a large-scale epigenome-wide association study (EWAS) has yet to be examined. We used publicly available data deposited in the Gene Expression Omnibus (GEO) database (accession number GSE37008), which consisted of both blood-derived epigenome-wide DNA methylation data assayed using the Illumina Infinium HumanMethylation27 BeadArray and complete blood cell (CBC) counts among a community cohort of 94 non-diseased individuals. Constrained projection (CP) was used to obtain predictions of the proportions of lymphocytes, monocytes and granulocytes for each...
Janina E Moretti - One of the best experts on this subject based on the ideXlab platform.
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analysis of in vitro evolution reveals the Underlying Distribution of catalytic activity among random sequences
Nucleic Acids Research, 2017Co-Authors: Abe Pressman, Janina E Moretti, Gregory W Campbell, Ulrich F Muller, Irene A ChenAbstract:The emergence of catalytic RNA is believed to have been a key event during the origin of life. Understanding how catalytic activity is distributed across random sequences is fundamental to estimating the probability that catalytic sequences would emerge. Here, we analyze the in vitro evolution of triphosphorylating ribozymes and translate their fitnesses into absolute estimates of catalytic activity for hundreds of ribozyme families. The analysis efficiently identified highly active ribozymes and estimated catalytic activity with good accuracy. The evolutionary dynamics follow Fisher's Fundamental Theorem of Natural Selection and a corollary, permitting retrospective inference of the Distribution of fitness and activity in the random sequence pool for the first time. The frequency Distribution of rate constants appears to be log-normal, with a surprisingly steep dropoff at higher activity, consistent with a mechanism for the emergence of activity as the product of many independent contributions.
