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Therefore, exploiting multiple auxiliary sources of data is essential for predicting genes related to polygenic traits, and many existing methods have been developed for this purpose.
The ITER Tokamak requires multiple auxiliary systems to initiate, support, and monitor the fusion reaction.
Regression estimators for stratified sampling and multiple auxiliary variables are also considered.
In these systems, transient expression of auxiliary genes is responsible for permanent genomic modification.
The hox regulon contains the structural and auxiliary genes for hydrogenase assembly.
Because the coMCRF model may incorporate multiple auxiliary data sets, it may have multiple cross-field transition probability terms, which represent the cross-field relationships between the primary categorical field and multiple different auxiliary fields.
Even so, a large fraction of the auxiliary genes are still connected with fundamental cellular and metabolic processes.
In a situation with multiple auxiliary variables, we fit two working PH models to the midpoint imputed data to reduce multiple auxiliary variables into two scalars.
These genes may be auxiliary genes and give viruses a selective advantage in nature.
The auxiliary genes are non-essential for DNA replication, translation or viral particle formation.
This approach can handle a situation with multiple auxiliary variables by deriving two risk scores from two working PH models.
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