Large scale prediction of the performance of genotypes is fundamental for understanding genotype by environmental interactions (G × E), predicting accurately genotypic performance in specific environments, and increasing our knowledge to develop future crop varieties.
Similar observations were reported in transcriptomic studies of C. sativus and E. grandis, wherein 454 pyrosequencing was shown to be an excellent method for large scale prediction of molecular markers for future genetic linkage and QTL analysis in non-model organisms [13], [16].
We describe a bioinformatic approach (genome neighborhood network; GNN) that enables large scale prediction of the in vitro enzymatic activities and in vivo physiological functions (metabolic pathways) of uncharacterized enzymes in protein families.
Examples of large-scale predictions of environmental concentrations of many chemicals have already been presented in [52, 53].
Therefore, large-scale predictions of soil carbon fluxes in response to fire in the boreal region must explicitly incorporate topographic features.
Compared with biochemical assays, the bioinformatics is more convenient and rapid for large-scale predictions of protein lncRNA associations.
Vaccine design: the selection of peptides for epitope-based vaccines is a typical application for large-scale predictions of MHC binding peptides.
This approach has been previously described by Osterman and Overbeek [ 16], and a computational method has been developed for automated large-scale predictions of protein function [ 18].
Here, we introduce a novel implementation of the ccSOL method, called ccSOL omics, to perform large-scale predictions of endogenous and heterologous expression in E. coli.
Furthermore, recent advances in computational functional genomics have enabled the large-scale prediction of domain-domain interactions and have led to repositories of known and predicted domain-domain interactions such as DOMINE [ 23] and InterDom [ 24, 25].
Integration of a plethora of genomic and biochemical data enables large-scale prediction of cellular functions.
