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To systematically assess the functional validity of our predictions, we analyzed the functional annotation of the predicted genes in the literature.
To evaluate the reliability of those predictions, we analyzed publicly available sequencing data in cv.
To generate our predictions we analyzed the model using time-dependent uncertainty analyses [ 1- 5], [ 11- 13].
To test the importance of the QTL-linked SNPs in predictions, we analyzed the accuracies by excluding the 42 QTL-linked markers from the 808 common markers.
Clustering of Probes and Functional Predictions We analyzed only probes significantly regulated (|log2 fold-change)|log2 fold-change1) in end-stage M marinum samples (Dionne et al., 2006 ).
In order to test the accuracy of GX-FBA's predictions, we analyzed a set of experimentally measured flux changes for yeast growing on 4 different carbon sources [ 50].
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To test this prediction, we analyzed the structure of EBV genomes in two lymphoblastoid cells derived from NBS1 mutated patients (Fig. 3B).
In the search of possible reasons for errors in the V3 loop-based coreceptor prediction we analyzed an additional dataset of phenotyped sequence spanning both V2 and V3 regions.
Therefore, to increase the specificity of novel miRNA prediction, we analyzed miRNA levels in Ago1-silenced mosquitoes.
To test this prediction we analyzed gene expression profiles from clonal colony fragments reciprocally transplanted between distinct natural habitats.
In order to externally validate the relative contribution of CD4 and CD8 expression to pCR prediction, we analyzed six public genomic datasets comprising 1,001 patients treated with NCT.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com