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Ideker et al. [ 2] have developed a method called Active Modules, which employs simulated annealing to search for connected components of a protein-protein interaction (PPI) network that are significantly changed according to some microarray dataset, thus giving an insight into how a coordinated response occurs in the PPI network without the need for such predefined pathways or gene-sets.
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Following robust statistical selection of differentially expressed genes, results were compared with publicly available microarray datasets, thus creating a unique list of likely disease modifiers.
In addition, the present method can achieve high detection rates of a period of interest for DNA microarray datasets, thus satisfying the expectations for biological data.
However, a more recent modification of that algorithm [ 30] permits the analysis of limited microarray datasets, thus widening the applicability of NCA.
The dimensions of the microarray dataset were thus 63 (rows) × 1701 (columns).
Together with the confident annotations we provide for the genes represented on the trout microarray, this dataset thus constitutes a necessary and solid basis to further investigate the control of spermatogenesis in fish.
Among these 102 genes, 84 were only measured by real-time RT-PCR and these gene expression profiles were thus added to the microarray dataset.
The results confirmed the similar transcriptional response for all six genes tested with two independent techniques, namely, DNA microarray and RT-PCR assays, thus proving the accuracy and reproducibility of our DNA microarray dataset.
Thus, in order to add physiological meaning to this observation, the whole microarray dataset was subjected to a linear regression analysis with each of the continuous covariates shown in Table 1.
The simulated dataset thus derived has a more balanced representation of features from the two modalities (microarray and image).
These software tools are based on superimposing a single microarray dataset on a biochemical pathway database, in order to visualise the expression of each individual gene per pathway and thus establish the state of individual pathways.
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