A stochastic approximation algorithm with Markov chain Monte-Carlo method for incomplete data estimation problems

We propose a general procedure for solving incomplete data estimation problems. The procedure can be used to find the maximum likelihood estimate or to solve estimating equations in difficult cases such as estimation with the censored or truncated regression model, the nonlinear structural measurement error model, and the random effects model. The procedure is based on the general principle of stochastic approximation and the Markov chain Monte-Carlo method. Applying the theory on adaptive algorithms, we derive conditions under which the proposed procedure converges. Simulation studies also indicate that the proposed procedure consistently converges to the maximum likelihood estimate for the structural measurement error logistic regression model.

Protein Information Resource: a community resource for expert annotation of protein data

The Protein Information Resource, in collaboration with the Munich Information Center for Protein Sequences (MIPS) and the Japan International Protein Information Database (JIPID), produces the most comprehensive and expertly annotated protein sequence database in the public domain, the PIR-International Protein Sequence Database. To provide timely and high quality annotation and promote database interoperability, the PIR-International employs rule-based and classification-driven procedures based on controlled vocabulary and standard nomenclature and includes status tags to distinguish experimentally determined from predicted protein features. The database contains about 200 000 non-redundant protein sequences, which are classified into families and superfamilies and their domains and motifs identified. Entries are extensively cross-referenced to other sequence, classification, genome, structure and activity databases. The PIR web site features search engines that use sequence similarity and database annotation to facilitate the analysis and functional identification of proteins. The PIR-Inter­national databases and search tools are accessible on the PIR web site at http://pir.georgetown.edu/ and at the MIPS web site at http://www.mips.biochem.mpg.de. The PIR-International Protein Sequence Database and other files are also available by FTP.

Sequence tag identification of intact proteins by matching tanden mass spectral data against sequence data bases.

Molecular and fragment ion data of intact 8- to 43-kDa proteins from electrospray Fourier-transform tandem mass spectrometry are matched against the corresponding data in sequence data bases. Extending the sequence tag concept of Mann and Wilm for matching peptides, a partial amino acid sequence in the unknown is first identified from the mass differences of a series of fragment ions, and the mass position of this sequence is defined from molecular weight and the fragment ion masses. For three studied proteins, a single sequence tag retrieved only the correct protein from the data base; a fourth protein required the input of two sequence tags. However, three of the data base proteins differed by having an extra methionine or by missing an acetyl or heme substitution. The positions of these modifications in the protein examined were greatly restricted by the mass differences of its molecular and fragment ions versus those of the data base. To characterize the primary structure of an unknown represented in the data base, this method is fast and specific and does not require prior enzymatic or chemical degradation.