However, this limitation is probably common to most large-scale analysis methods.
Thus, up until now, most large-scale analysis of phenotype on micro- and nanoscale systems has been a gigantic undertaking [ 8– 10].
Currently, amino-acid substitution is the most feasible way to conduct a large scale analysis of phospho-modifications [ 37].
Most large-scale geographic analysis of disease in developing countries is done at a relatively coarse geographic resolution, using provinces, municipalities, or districts as the level of analysis.
Most large-scale efforts involve reverse genetic analysis of candidate genes that are either orthologs of essential genes in other organisms, fail to generate a knockout homozygote, or share a common cellular process, metabolic pathway, or protein interactor with a known EMB gene product.
Whole genome sequencing has the capability of providing researchers the identity of every variant contained within the genome; however, it may still be too expensive (∼$1,500 2,000 per sample for sequencing only, not including data analysis) for most large-scale studies and may generate more data than required.
Most large-scale phenotypic analyses of the yeast gene deletion strains have been non-or semi-quantitative, based on end-point analysis of cell proliferation [ 10].
In most large-scale lotteries, a very large prize is offered along with many smaller ones.
Most large-scale companies are well into that these days.
First, most comprehensive analytical methods for large-scale analysis usually provide only relative quantities, although it is better to use absolute metabolite concentrations to construct a detailed model.
Inclusion in the > 70% PERF_ALIGN still indicates fair sequence similarity, and in most cases this is sufficient for large-scale analysis.
