Sentence examples for model where proteins from inspiring English sources

Compared to a null model, where proteins are stochastically reshuffled between complexes, intra-complex paralogs are ~40-fold overrepresented (SGD modules, [ 14]).

As an illustration figure 7 shows the bootstrap distribution of correlation coefficients of expression levels in yeast for the correct Null model and for the model where proteins are paired completely at random.

Collectively, our results support a previously proposed model where proteins are essential because of their involvement in essential functional modules rather than because of specific topological features such as degree or centrality.

The conservative nature of interaction evolution after gene duplication is confirmed by the underrepresentation of bi-complex paralogs, compared to a null model where proteins are free to change their complex following the duplication (Table 1 and additional file 1, Table S2).

We therefore expect that some of the many feed-forward loops in transcription networks [ 3] will be explained by a new type of null model: A null model where proteins contributing to a given process are forced to remain close in the randomized network.

Although in principle the model can represent cells where proteins are present at different concentrations and interact with different affinities, here we focus on the topological properties of the network and we use a simple model where proteins are all present at the same concentration and interact with the same "strength".

Collectively, these results support a model where protein acetylation induced by HDACi increases the transcriptional activity of Sp1/Sp3-dependent complexes seated on the TNFSF9 promoter.

Together these data support a model where protein components are localized to the nuclear membrane but where we anticipate that they function abnormally similar to what we previously noted with nesprin-1 mutations [30], [31].

Solid lines are fits to a model where protein binding induces an allosteric effect that persists along the filament over a certain length scale (see 'Materials and methods' for details).

Therefore, based on the known complexes in CORUM database, we design a method to infer drug-complex-disease phenotype relationships using a network model, where protein complexes are related to not only drugs but also to the disease phenotype.

While a decade ago the fast mobility of proteins in the nucleoplasm lead to diffusion models, we are now envisioning models where proteins are guided on DNA or protein networks controlling their exploration properties (diffusion can be guided).