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Integrative approaches for microRNA target prediction: combining sequence information and the paired mRNA and miRNA expression profiles
target prediction expression profile integrative analysis
2016/1/20
Gene regulation is a key factor in gaining a full understanding of molecular biology. microRNA (miRNA), a novel class of non-coding RNA, has recently been found to be one crucial class of post-transac...
Combining Dynamic Predictions from Joint Models for Longitudinal and Time-to-Event Data using Bayesian Model Averaging
Prognostic Modeling Risk Prediction
2013/4/27
The joint modeling of longitudinal and time-to-event data is an active area of statistics research that has received a lot of attention in the recent years. More recently, a new and attractive applica...
Unified Analysis of Transmit Antenna Selection/Space-Time Block Coding with Receive Selection and Combining over Nakagami-m Fading Channels in the Presence of Feedback Errors
Space-Time Block Coding (STBC) Transmit Antenna Selection (TAS) Receive Antenna Selection (RAS) Maximal-ratio Combining (MRC) Selection Combining (SC) Nakagami-m fading Feedback Errors
2012/9/18
Examining the effect of imperfect transmit antenna selection (TAS) caused by the feedback link errors on the performance of hybrid TAS/space-time block co ding (STBC) with selection combining (SC) (i....
Combining Predictive Distributions
calibration coherent combination formula density forecast
2011/7/5
Predictive distributions need to be aggregated when probabilistic forecasts are merged, or when expert opinions expressed in terms of probability distributions are fused.
Reduced long-range dependence combining Poisson bursts with on--off sources
Teletraffic fractional Brownian motion on–off process
2011/7/5
A workload model using the infinite source Poisson model for bursts is combined with the on--off model for within burst activity. Burst durations and on--off durations are assumed to have heavy-tailed...
Testing a precise null hypothesis by combining experiments
a precise null hypothesis combining experiments
2009/9/22
The problem of combining experimental results to test
sharp null hypotheses is considered from a Bayesian viewpoint.
Relying on results of Berger and Sellke [S], lower bounds on the
posterior proba...
Combining multiple maps of line features to infer true position
GIS linear features lines maps positional error
2009/9/22
Map positional error refers to the dierence between a feature coordinate pair on a map and the corresponding true, unknown coordinate pair. In a geographic information system (GIS), this error is pro...
Combining Experimental Data and Computer Simulations, With an Application to Flyer Plate Experiments
calibration computer experiments flyer plate experiments Gaussian process model validation predictability predictive science
2009/9/21
A flyer plate experiment involves forcing a plane shock wave through
stationary test samples of material and measuring the free surface velocity of the
target as a function of time. These experiment...
COMBINING METHODS IN SUPERVISED CLASSIFICATION：A COMPARATIVE STUDY ON DISCRETE AND CONTINUOUS PROBLEMS
Gaussian classification eigenvalue decomposition multinomial classification conditional independence model convex combining hierarchical combining
2009/2/25
Often in discriminant analysis several models are estimated but based on some validation
criterion, a single model is selected. In the purpose of taking profit from several
potential models, classif...
Improving small area estimation by combining surveys：new perspectives in regional statistics
composite estimator complementary survey mean squared error official statistics regional statistics small areas
2009/2/23
A national survey designed for estimating a specific population quantity is sometimes used for
estimation of this quantity also for a small area, such as a province. Budget constraints do not allow a...
A Bayesian Framework for Combining Valuation Estimates
value investing financial statement analysis equity valuation
2010/4/30
Obtaining more accurate equity value estimates is the starting point for stock
selection, value-based indexing in a noisy market, and beating benchmark indices
through tactical style rotation. Unfor...
Combining domain knowledge and statistical models in time series analysis
time series analysis domain knowledge empirical models mechanisticmodels combined substantive-empirical approach basis function
2010/4/27
This paper describes a new approach to time series modeling that
combines subject-matter knowledge of the system dynamics with statistical
techniques in time series analysis and regression. Applicat...