Sentence examples for based on gene networks from inspiring English sources

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Another important point here is that the horizontal gene transfer (HGT) has little influence on building a phylogenetic tree based on gene networks.

However, previous studies were mostly based on gene networks in invertebrate species, and they had the inherent shortcoming of not being able to provide information on how the duplication-divergence process proceeded along the time axis during major speciation events.

These analyses illustrate how a systems biology approach based on gene networks can yield insights into the molecular mechanisms of neural development and function, and provide clues as to the functional impact of the downstream effects of Ca2+ signaling dysregulation on transcription.

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An unsupervised and unbiased approach was used to nominate potential regulatory candidates for these modules based on gene network connectivity.

These results reinforce the idea that PAX9 is not the unique gene involved in the dental development and that only an approach based on gene network can lead to a more comprehensive view of the complex biology involved.

The evaluation experiment is based on gene network containing 34,364 interactions between 8919 genes, the phenotypic similarity matrix between 5080 phenotype entities calculated by using MimMiner, and 1428 gene-phenotype links between 937 genes and 1216 phenotype entities.

We sought to define the issue using an integrated transcriptome analysis based on gene network-approaches that has successfully been proven to identify associations not previously apparent [ 10, 34– 34].

Here we extracted information from all of the included studies on DEGs in EAT samples and performed a meta-analysis based on gene-networks consisting of upregulated and downregulated genes in EAT to identify genes that may be involved in disease pathogenesis.

Furthermore, none of these top-performing methods, including the one by a different team, are based on gene regulatory networks, which seems to suggest that accurately modeling gene expression using gene regulatory networks is unfortunately still a difficult task.

The T-helper and EMT examples are based on gene regulatory networks previously published [ 15, 16].

Hypothesizing that the current regulatory network model may not be accurate enough to make quantitative predictions (see Discussion), I opted to use a different strategy, based on gene co-expression networks.

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