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Huttenhower, C. et al. The impact of incomplete knowledge on evaluation: an experimental benchmark for protein function prediction.
Gβ1 is a small protein that is a suitable benchmark for protein design algorithms (Georgiev and Donald, 2007).
These standards can serve as a benchmark for protein quantification and for normalization of run-to-run variation.
Unused Prot-Score >1.3 (95%) as threshold with at least more than one peptide above the 95% confidence was considered as benchmark for protein identification.
> -wrap-foot> Thus, it must be appreciated that with the availability of an ever increasing number of genomes acting as reference, i.e. providing composite background protein sequences, this approach can become a benchmark for protein interaction research.
Since proteins encoded by sORFs largely escape standard genome annotations, we examined evolutionary conservation in combination with computational approaches to screen for ORFs conserved in kinetoplastidae and representative eukaryotes as a benchmark for protein expression.
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To provide a benchmark for protein-engineering experiments involving GghA, a three-enzyme continuous assay (performed at 85 °C), linking wild-type GghA, Glk, and Gpd, measured glucose produced from GghA's hydrolysis of cellobiose, one of GghA's secondary substrates.
We compared our DACO approach to the most recent versions of the popular complex prediction tools MCODE (Bader and Hogue, 2003), MCL (Enright et al., 2002) and ClusterONE (Nepusz et al., 2012) using common benchmarks for protein complex prediction in yeast and the weighted high-quality yeast protein interaction network PrePPI (Zhang et al., 2013).
Our goal was to extend this principle to other databases and to design standardized benchmark datasets for protein classification.
As input we used benchmark datasets for protein kinases.
We evaluate our methods for classification on the SCOP PDB-40D benchmark dataset for protein fold recognition.
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