First, we used the generalized predictive control to predict the target position.
To further improve on the power of NGSmirPlant, future development will implement the microRNA target prediction tools to predict the target genes of identified microRNAs in plant.
To screen the target mRNAs of the miRNAs as in the top 1% of FCs, we used prediction tools to predict the target mRNAs of the miRNAs listed in Tables 2 and 3, respectively.
Three types of miRNA target prediction software, TargetScan, PicTar, miRanda, were used to predict the target genes of 30 neural tissue specifically expressed miRNAs.
We used the miRNA target prediction software miRanda (http://www.microrna.org/microrna/home.do) to predict the target genes of miR-222, miR-21, and miR-146a.
To predict the target mRNAs of the differentially expressed miRNAs, we performed target prediction for the differentially expressed miRNAs identified in the BxPC-3 cells using three different types of online software: TargetScan, PicTar and miRanda.
It is important to have an empirical strategy to adequately predict the target variable.
Indoor localization problem can be formulated as an optimization problem to predict the target.
Because the FCECR algorithm will predict the target user, it needs linear equivalence for a similar item set.
PV-DM uses the average of text embedding and word embeddings in the local window to predict the target word.
And experts predict the target to end child poverty by 2020 is likely to be missed unless more is done to address inequality.
