Sentence examples for prediction analyze from inspiring English sources

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Phylogenetic methods of orthology prediction analyze gene trees (or, more precisely, multi-gene trees containing groups of paralogs and orthologs) to localize duplication events on the tree and separate orthologs from paralogs; phylogenetic methods also enable biologists to perform more fine-tuned analyses, e.g. to discriminate between orthologs and super-orthologs [ 30].

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For example, for community dynamics, the in-class activity required students to make predictions, analyze data, and explain results based on Paine's (1966) classic Pisaster exclusion experiments from a rocky intertidal zone.

This suggests that the different predictions analyzed are complementary despite the unclear definition of transcriptional cooperativity.

JDO performed all computational predictions, analyzed the results, performed the experimental analysis, and wrote the manuscript.

The activities required students to perform one or more of the following tasks: making predictions, analyzing data, interpreting graphs, drawing models, explaining experimental results, and using evidence to support explanations of phenomena.

The 3,478 QRNA predictions analyzed by microarray were mapped to the mouse-human UCSC genomic alignments (mm6-hg17) and were subset to the same regions analyzed by Cheng et al. [ 9] (i.e. not repetitive regions, for example), which were determined from the probe positions used in the tiling analysis (coordinates were converted to the hg17 genome release using the UCSC LiftOver tool [ 17]).

From the viewpoint of long-term prediction, we analyze the sparsity of voiced speech signals and construct an adaptive sparsifying matrix.

We developed a novel method, called STAP (Sequence To Affinity Prediction), to analyze large scale TF-DNA binding data.

In this paper we use computational RNA secondary structure prediction to analyze the secondary structure of the RPS17B intron.

The result of prediction could analyze the character of the docking site and the efficacy of the drug.

Known as Vector Auto Regression, or VAR, Sims's methodology enables researchers to make predictions and analyze policy changes without committing to a particular economic theory, but, rather, by seeking to let the data speak for itself.

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