Results 1  10
of
6,480
Improved prediction of signal peptides  SignalP 3.0
 J. MOL. BIOL.
, 2004
"... We describe improvements of the currently most popular method for prediction of classically secreted proteins, SignalP. SignalP consists of two different predictors based on neural network and hidden Markov model algorithms, where both components have been updated. Motivated by the idea that the cle ..."
Abstract

Cited by 654 (7 self)
 Add to MetaCart
We describe improvements of the currently most popular method for prediction of classically secreted proteins, SignalP. SignalP consists of two different predictors based on neural network and hidden Markov model algorithms, where both components have been updated. Motivated by the idea
Regularization and variable selection via the Elastic Net.
 J. R. Stat. Soc. Ser. B
, 2005
"... Abstract We propose the elastic net, a new regularization and variable selection method. Real world data and a simulation study show that the elastic net often outperforms the lasso, while enjoying a similar sparsity of representation. In addition, the elastic net encourages a grouping effect, wher ..."
Abstract

Cited by 973 (11 self)
 Add to MetaCart
, where strongly correlated predictors tend to be in (out) the model together. The elastic net is particularly useful when the number of predictors (p) is much bigger than the number of observations (n). By contrast, the lasso is not a very satisfactory variable selection method in the p n case
Classifier fitness based on accuracy
 Evolutionary Computation
, 1995
"... In many classifier systems, the classifier strength parameter serves as a predictor of future payoff and as the classifier’s fitness for the genetic algorithm. We investigate a classifier system, XCS, in which each classifier maintains a prediction of expected payoff, but the classifier’s fitness is ..."
Abstract

Cited by 350 (17 self)
 Add to MetaCart
In many classifier systems, the classifier strength parameter serves as a predictor of future payoff and as the classifier’s fitness for the genetic algorithm. We investigate a classifier system, XCS, in which each classifier maintains a prediction of expected payoff, but the classifier’s fitness
Pyrosequencingbased assessment of soil pH as a predictor of soil bacterial community structure at the continental scale
 APPLIED AND ENVIRONMENTAL MICROBIOLOGY
, 2009
"... Soils harbor enormously diverse bacterial populations, and soil bacterial communities can vary greatly in composition across space. However, our understanding of the specific changes in soil bacterial community structure that occur across larger spatial scales is limited because most previous work h ..."
Abstract

Cited by 189 (21 self)
 Add to MetaCart
communities in 88 soils from across North and South America, obtaining an average of 1,501 sequences per soil. We found that overall bacterial community composition, as measured by pairwise UniFrac distances, was significantly correlated with differences in soil pH (r � 0.79), largely driven by changes
Predictors of or
, 2011
"... www.fruitsjournal.org RESUMEN ESPAÑOL, p. 136 Article published by EDP ScienPredictors of organoleptic quality of boiled and dried pulp of safou (Dacryodes edulis) and the shelf life of its fresh fruits. Abstract — Introduction. The high intraspecific variation in safou traits and the perishable n ..."
Abstract
 Add to MetaCart
www.fruitsjournal.org RESUMEN ESPAÑOL, p. 136 Article published by EDP ScienPredictors of organoleptic quality of boiled and dried pulp of safou (Dacryodes edulis) and the shelf life of its fresh fruits. Abstract — Introduction. The high intraspecific variation in safou traits and the perishable
AS PREDICTORS OF
"... Gallbladder carcinoma is the fi fth most common malignancy of the gastrointestinal tract. O e absolute characteristics of the disease are the high mortality rate due to the late discovery of a tumor and the low therapeutic possibilities except by surgical intervention. In oncology we can predict the ..."
Abstract
 Add to MetaCart
are the denominators (markers). O e author searched extensively for the expression and infl uence of markers included in chronic infl ammation and early carcinogenesis, cell cycle regulation and tissue hypoxia: cyclooxygenase (COX), p gene and glucose transporter protein (GLUT). O e author discusses
Bayesian Factor Regression Models in the "Large p, Small n" Paradigm
 Bayesian Statistics
, 2003
"... TOR REGRESSION MODELS 1.1 SVD Regression Begin with the linear model y = X# + # where y is the nvector of responses, X is the n p matrix of predictors, # is the pvector regression parameter, and # , # I) is the nvector error term. Of key interest are cases when p >> n, when X is & ..."
Abstract

Cited by 184 (16 self)
 Add to MetaCart
TOR REGRESSION MODELS 1.1 SVD Regression Begin with the linear model y = X# + # where y is the nvector of responses, X is the n p matrix of predictors, # is the pvector regression parameter, and # , # I) is the nvector error term. Of key interest are cases when p >> n, when X
Hjortdahl P: Predictors of job satisfaction among doctors, nurses and auxiliaries in Norwegian hospitals: relevance for micro unit culture. Human Resources for Health 2006
"... in Norwegian hospitals: relevance for micro unit culture ..."
Abstract

Cited by 8 (0 self)
 Add to MetaCart
in Norwegian hospitals: relevance for micro unit culture
Selfdetermination and persistence in a reallife setting: Toward a motivational model of high school dropout.
 Journal of Personality and Social Psychology,
, 1997
"... The purpose of this study was to propose and test a motivational model of high school dropout. The model posits that teachers, parents, and the school administration's behaviors toward students influence students' perceptions of competence and autonomy. The less autonomy supportive the so ..."
Abstract

Cited by 183 (19 self)
 Add to MetaCart
on this variable. The analyses were conducted with this transformed variable. 5 We also conducted a regression analysis to predict behavioral intentions from the motivation scales. Results revealed that four predictors were significant (p < .01): amotivation (/3 = .50), identification (0 = .11), intrinsic
BINOMIAL PREDICTORS
, 2009
"... For a prime p and nonnegative integers n, k, consider the set A (p) n, k = {x ∈ [0, 1,..., n] : pk   () n x}. Let the expansion of n + 1 in base p be: n + 1 = α0p ν + α1p ν−1 +... + αν, where 0 ≤ αi ≤ p − 1, i = 0,..., ν. Then the number n is called a binomial predictor in base p, if A (p) n, ..."
Abstract
 Add to MetaCart
For a prime p and nonnegative integers n, k, consider the set A (p) n, k = {x ∈ [0, 1,..., n] : pk   () n x}. Let the expansion of n + 1 in base p be: n + 1 = α0p ν + α1p ν−1 +... + αν, where 0 ≤ αi ≤ p − 1, i = 0,..., ν. Then the number n is called a binomial predictor in base p, if A (p) n
Results 1  10
of
6,480