Subsurface system analysis derived from the hydrologic community emphasizes conceptual model development through model verification, validation, uncertainty quantification, benchmarking and meta-analysis.
While characterizing how similar descriptor sets perceive amino acid space is one important requirement to select the best descriptor set to use in PCM, another important quantification comes from benchmarking on PCM sets.
These standards can serve as a benchmark for protein quantification and for normalization of run-to-run variation.
Teng, M. et al. A benchmark for RNA-seq quantification pipelines.
The purpose of this paper is to replace such ad-hoc expert judgment of the uncertainty information of TRACE physical model parameters with inverse Uncertainty Quantification (UQ) based on OECD/NRC BWR Full-size Fine-Mesh benchmarksts (BFBT) benchmark steady-state void fraction data.
Dose predictions, clinical trial design optimization, facilitation of covariate analysis (e.g., What patient-specific data should be collected during the clinical investigation?), and quantification of enzyme ontogeny for a benchmark drug are examples of pediatric PBPK model applications.
The reference mass spectrometric maps provide benchmarks for proteome identification and quantification by any MS strategy.
In this work, we design a series of benchmark problems for subsurface flow uncertainty quantification.
Real-time quantitative PCR (qPCR) has become the benchmark technology for the detection and quantification of nucleic acids in a research, diagnostic, forensic and biotechnology setting.
Their physical degradation is strongly felt and observed, but its quantification is difficult owing to a lack of benchmark data.
For any existing and newly developed uncertainty quantification methods, which are not (fully) verified, the designed benchmark problems in this work can facilitate the verification process of those methods.
