Correct identification of a peptide sequence from MS/MS data is still a challenging research problem, particularly in proteomic analyses of higher eukaryotes where protein databases are large. The scoring methods of search programs often generate cases where incorrect peptide sequences score higher than correct peptide sequences (referred to as distraction). Because smaller databases yield less distraction and better discrimination between correct and incorrect assignments, we developed a method for editing a peptide-centric database (PC-DB) to remove unlikely sequences and strategies for enabling search programs to utilize this peptide database. Rules for unlikely missed cleavage and nontryptic proteolysis products were identified by data mining 11 849 high-confidence peptide assignments. We also evaluated ion exchange chromatographic behavior as an editing criterion to generate subset databases. When used to search a well-annotated test data set of MS/MS spectra, we found no loss of critical information using PC-DBs, validating the methods for generating and searching against the databases. On the other hand, improved confidence in peptide assignments was achieved for tryptic peptides, measured by changes in DeltaCN and RSP. Decreased distraction was also achieved, consistent with the 3-9-fold decrease in database size. Data mining identified a major class of common nonspecific proteolytic products corresponding to leucine aminopeptidase (LAP) cleavages. Large improvements in identifying LAP products were achieved using the PC-DB approach when compared with conventional searches against protein databases. These results demonstrate that peptide properties can be used to reduce database size, yielding improved accuracy and information capture due to reduced distraction, but with little loss of information compared to conventional protein database searches.

Absfract-Complex approximation with a generalized Remez algorithm is used to design FIR digital filters with nonconjugate symmetric frequency responses. The minimax criterion is used and the Chebychev approximation is posed as a linear optimization problem. The primal problem is converted to its dual and is solved using an efficient, quadratically convergent algorithm developed by Tang [l]. Optimal Chebychev real-coefficient FIR filters with group delay smaller than half the filter length can be designed with slightly better magnitude responses compared to linear-phase filters. Linear-phase filters can also be designed when the group delay is specified to be half the filter length. Most importantly, the design method is capable to produce filters with complex coefficients that approximate noncoqjugate symmetric frequency responses.

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This paper presents a method for the design of FIR Hilbert transformers and differentiators in the complex domain. The method can be used to obtain conjugate-symmetric designs with smaller group delay compared to linear-phase designs. Non-conjugate symmetric Hilbert transformers are also designed. This paper is an extension of our previous work [1], which presented the algorithm for the design of standard frequency selective filters. The minimax criterion is used and the Chebychev approximation is posed as a linear optimization problem. The primal problem is converted to its dual and is solved using an efficient quadratically convergent algorithm developed by Tang [2]. When a constant group delay is specified, the filter designs have almost linear phase in the passbands. When the specified group delay is half the filter length, the algorithm results in exactly linear-phase designs.