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SSPs are often highly species-specific, lacking similarity to known proteins, making functional predictions difficult.
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Here, we used a combination of EST sequencing, clustering, annotation of conserved domains and a search for ESTs encoding proteins related to the domain-predicted pathways to make functional predictions of these particular tardigrade-specific EST sequences.
We have designed a series of algorithms that make functional predictions of genes based on orthology and set theory, but our approach to predicting gene function requires no previous knowledge of homolog function.
We highlight the advantages and disadvantages of each type of search, provide examples of large-scale searches of the entire Protein Data Base and make functional predictions.
These data were used by AutoAnnotate to make functional predictions for proteins, which were then made available in the Manatee interface for manual evaluation of the predicted function.
These data used by AutoAnnotate to make functional predictions for proteins were then made available in the Manatee interface for manual evaluation of the predicted function.
Assessing the MR algorithm on the same target dataset that we used in CSIDOP, MR made functional predictions with an accuracy of 59.50% (Table 1).
In the present paper we do not focus on the network topology or study structural properties thereof but utilize its topology to make functional predictions regarding genes that are cell cycle regulated.
Both domain architecture and operon analysis have been used extensively to make functional predictions of poorly characterized domains or genes [ 26- 29].
This shows that information on how the different interactions influencing a species are combined is necessary to make functional predictions on a node's state.
Levesque et al. [ 29] have suggested a series of algorithms that make functional predictions on the basis of phyletic vectors and set theory.
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