The development of many different TM-helix prediction algorithms and the recent upsurge of GPCR structures (for a review, please see Venkatakrishnan and coworkers 42) have prompted us to consult multiple prediction programs and alternate templates for TM-helix prediction and in homology modeling, respectively.
This missense Arg258Gln mutation that localizes in exon 5, within the Sac1 domain of the protein, is predicted to be damaging by multiple prediction programs, and the arginine in position 258 is conserved in thirteen SYNJ1 orthologs and five Sac1-like domains containing proteins [ 3, 4].
By examining a wide range of networks from mouse, human and yeast, as well as multiple prediction methods and evaluation metrics, we provide evidence that this problem is pervasive and does not reflect the failings of any particular algorithm or data type.
Empirical evidence for the proposed mechanism from both molecular evolution and evolution at the organismal level is discussed, and multiple predictions are offered by which it may be tested.
Neither variations in a patient's blood volume, the number of nurses making observations, nor large variations in the nurses' estimates alter the facts that multiple observations were obtained from some patients and multiple predictions were made by some nurses.
The same virtual compound can appear in different SAR matrices, and therefore multiple predictions can be made for the same compound and the level of consistency could be a good indicator for deciding to make he actual compound.
To evaluate the relative gains to be expected from conducting genomic selection for carotenoid traits in maize grain, we tested multiple prediction methods and marker sets.
The effects of multiple predictions are greater for genes relative to species for both systems, and influence precision and recall differentially for text2genome and GNAT.
Explore more problems: Data scientists need the ability to rapidly define and explore multiple prediction problems, quickly and easily.
Multiple imputation uses multiple predictions of missing clinical endpoints based on patient characteristics and the baseline value of the clinical outcome variables [ 16].
