SWISS-PROT sequence data base

The second postprocessing step is the automated enhancement of the TrEMBL annotation to bring TrEMBL entries closer to SWISS-PROT standard. There is an increasing need for reliable automatic functional annotation to cope with the rapidly increasing amount of sequence data. Most of the current approaches are still based on sequence similarity searches against known proteins. Some groups try to collect the results of different prediction tools in a simple way, e.g., PEDANT (Frishman and Mewes, 1997) or GeneQuiz (Scharf et al., 1994). However, several pitfalls of these methods have been reported (Bork and Koonin, 1998). 

FIGURE 10.3 The LOCkey algorithm. A sequence unique data set of localization annotated SWISS-PROT proteins was first compiled. Keywords were extracted for these proteins and merged with any keywords found in homologues. The keywords were represented as binary vectors in the Trusted Vector Set. An unknown query was first annotated with keywords through identification of SWISS-PROT homologues. Keywords for the query were represented as binary vectors. All possible keyword combinations were constructed (the SUB vectors). The best matching vector was found based on entropy criteria (see Methods). This vector was used to infer localization for the query. 

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