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Importantly, correlations using the whole mean volume of young normal adult mice revealed that the numbers of cells generated in silico with the mathematical model fall within the range of total thymocyte numbers seen in these animals.
Since the data has been generated in silico with known structure (see Fig. 2) and parameters we can compute the accuracy of the recovered model structures.
In both challenges, a budget was provided to buy experimental data generated in silico with the model and mimicking the features of different common experimental techniques, such as microarrays and fluorescence microscopy.
This observation corresponded with predictions generated in silico with a kinetic model of yeast glycolysis, when the catalytic capacities of all glycolytic enzymes were set to share the same normalized temperature dependency.
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Input data from those procedures were generated in-silico by introducing two virtual dimeric enzymes with defined, complex deactivation mechanisms.
Single-molecule maps were aligned with a map generated in silico based on the EBV reference sequence (strain B95-8; GenBank: V01555.2).
We further identified LHT seminal proteins using a combination of mass spectrometry and bioinformatics as follows: First, we compared the peptide sequences from tryptic digests of our long hyaline tubule SFP-enriched fractions with peptide sequences generated in silico from a translation of the LHT transcriptome.
We generated in silico data to evaluate our algorithm and compare it with several widely used indel detection methods.
IM-MS experiments generate CCS values used in our computational approach for comparison with the calculated CCSs of candidate structures generated in silico.
Program-specific algorithms compare theoretically derived peptide fragment pattern (generated in silico) to experimental peptide data [44]-[46] [44]-[46]
MetFrag assigns fragment structures generated in silico to experimental MS/MS spectra using a defined mass difference.
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