Sentence examples for matrices to predict from inspiring English sources

We applied position weight matrices to predict HNF4α consensus sites and confirmed the predictions experimentally by EMSA assays to determine its DNA binding activity.

The algorithm factorizes each network to obtain features using graph communicability, and then collapses the feature matrices to predict temporal links.

In this REU program, two groups of undergraduate students studied certain RNA sequences related to viral and mammalian mRNA regulatory regions and used lattice walks modeled by Riordan matrices to predict RNA secondary structures.

The results obtained by the students were that they established direct links between lattice walks and primary RNA sequences of YF and epilepsy and used lattice walks modeled by Riordan matrices to predict more stable RNA secondary sequences related to these two diseases.

3 4 Indeed, several studies have recently attempted to construct clinically useful risk matrices to predict so-called 'rapid radiographic progression' (RRP), corresponding to an increase in Sharp-van der Hejde score (SHS) of ≥5 after 1 year, based on both early RA trials 5 6 and cross-sectional cohorts 7; their performance has been tested in both early 8 and unselected 9 RA populations.

SVD uses the low level rating matrix to predict the true score matrix.

The central composite design methodology (CCD) was used as the design matrix to predict the optimal level of these parameters.

Finally, we use the concept of cortical magnification matrix to predict a selective increase of cortical magnification along the horizon due to cortical folding.

We conclude that the NLR increase is greater following TKA compared to UKA and could serve as a matrix to predict or identify a patient susceptible of sustaining VTE after TKA. 3. Osteoarthritis (OA) is the most common degenerative joint disease [1] and the knee is one of the most commonly affected sites.

Because the UKF is able to obtain the posterior mean and covariance accurately by using the second-order Taylor series expansion through the sampled sigma points that are propagated by using the true nonlinear system, its performance can be better than that of the extended Kalman filter (EKF), which uses the linearized state transition matrix to predict the covariance.

The variance-covariance matrix of random effects (trees) in the linear mixed model is replaced by the A matrix to predict breeding values.