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Variants were not validated with another method and predictions of function are theoretical only.
A main point of the current paper is that contrary to assumptions inherent in previous studies, most computational predictions of function are driven by the presence of multifunctionality.
A challenge in systems biology is to assign functions to genes from the information in large-scale datasets, maximizing the utility of available information to make predictions of function with verifiable performance.
The data generated through this method allows predictions of function to be made for previously uncharacterized genes based on the observation that genes with similar function often show a common expression pattern.
Although such an approach is theoretically fraught with uncertainties, realistic predictions of function in low-complexity environments were given.
In this study, we made predictions of function based on genome content using genome sequences of six human-derived L. reuteri strains that represent clades II and VI (see fig. 2 and supplementary fig. S1, Supplementary Material online).
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The most reliable prediction-of-function approaches for genomically sequenced protein orfs are obtained using the more computationally intensive HMM modelling and scoring utilities.
Data: Direct predictions of functions from structures [ 165- 167] have been developed only recently for proteins using computational methods that build on experimental data.
The 3D tractome map presented here describes inter-circuit relationships especially in convergent target areas, which may prove critical for the prediction of function.
With the present modality, the prediction of function via DTI seems promising.
Whilst prediction of function based on sequence homology can be misleading, a study of the domain architecture of RING and RING-like E3 ligases may highlight additional features.
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