Sentence examples for benchmarks we used from inspiring English sources

With the Gene Ontology (GO) annotations [33] and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway annotations [34] as benchmarks, we used annotation overlap rates (see Methods and Materials) to validate the reliability of the protein pair ranking from P1, and preliminarily determined functionally associated protein pairs (i.e., significant protein pairs).

For all benchmarks, we used one or more dedicated Dell Blade M605 compute nodes with 2 quad-core Opteron 2.33 GHz processors and 24 GB of random access memory.

As benchmarks we used not only the DREAM4 In Silico Network challenge but also a novel and unprecedented synthetic compendium consisting of several realistic 5000-gene networksimulateded with varying biological and measurement error variances resulting in a total of 270 datasets.

We performed benchmarking tests on a large set of nucleic acid and protein sequences For protein benchmarks we used the benchmark database BALIBASE 3 and an updated release of the database IRMBASE 2 for assessing the quality on globally and locally related sequences, respectively.

As benchmarks, we use BRUTE, the 'brute force' method using the Bonferroni correction, BRUTE-WY, the Westfall Young version of BRUTE, and UFE, the univariate Fisher's Exact Test, which only checks for a significant difference in single SNPs.

For all benchmarks, we use four structure alignment tools to generate reference alignments: TM-align (Zhang and Skolnick, 2005), Matt (Menke et al., 2008), Dali (Holm and Sander, 1993) and our in-house structure alignment tool DeepAlign.

As a benchmark we used the discriminative power to detect the seizure-generating hemisphere in medically intractable mesial temporal lobe epilepsy.

As a benchmark, we used the approach of choosing the three closest nodes, as in [1], which is popular because of its simplicity.

As a measure of the relative performance of two fingerprints A and B on a benchmark, we used the net difference between the number of times A performed better than B minus the number of times it performed worse.

For the site benchmark we used all available peak data; for each peak we annotated a 20.000 bp region randomly around the peak region as the test region.

As a comparison benchmark, we used experimental protein interactions determined mostly from HTP screens.