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This functional label agrees with our predicted function.
Extension here is used as a functional label representing combinations of semantic choices in the system of PHASE.
A protein without a specific functional label might merely be due to lack of evidence experiment.
These methods constructed a composite network for each functional label.
A dataflow diagram of the functional label generation is presented in Figure 6.
The functional label is a set of keyword IDs assigned to a particular protein.
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First, Evolutionary Trace Annotation, or ETA, identifies which proteins have local evolutionary and structural features in common; next, these proteins are linked together into a proteomic network of ETA similarities; then, starting from proteins with known functions, competing functional labels diffuse link-by-link over the entire network.
Next, we obtained gene-function associations and the ontology of functional labels from the GO Consortium (Ashburner et al., 2000).
Since protein functions are inter-correlated and most functional labels often have a relatively small number of member proteins, these algorithms ignore the interrelationship among labels, which can often be used to boost the prediction accuracy [ 3, 19].
Results: We propose a novel function prediction algorithm, clusDCA, which transfers information between similar functional labels to alleviate the overfitting problem for sparsely annotated functions.
In addition, MNet takes into account the unbalanced label problem in protein function prediction, and incorporates a label weighted scheme into the unified objective function to give more emphasis to the functional labels with fewer proteins.
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CEO of Professional Science Editing for Scientists @ prosciediting.com