Approximate extraction of late-time returns via morphological component analysis.

A fundamental challenge in acoustic data processing is to separate a measured time series into relevant phenomenological components. A given measurement is typically assumed to be an additive mixture of myriad signals plus noise whose separation forms an ill-posed inverse problem. In the setting of sensing elastic objects using active sonar, we wish to separate the early-time return from the object's geometry from late-time returns caused by elastic or compressional wave coupling. Under the framework of morphological component analysis (MCA), we compare two separation models using the short-duration and long-duration responses as a proxy for early-time and late-time returns. Results are computed for a broadside response using Stanton's elastic cylinder model as well as on experimental data taken from an in-air circular synthetic aperture sonar system, whose separated time series are formed into imagery. We find that MCA can be used to separate early and late-time responses in both the analytic and experimental cases without the use of time-gating. The separation process is demonstrated to be compatible with image reconstruction. The best separation results are obtained with a flexible, but computationally intensive, frame based signal model, while a faster Fourier transform based method is shown to have competitive performance.

Improving reproducibility and sensitivity in identifying human proteins by shotgun proteomics.

Identifying proteins in cell extracts by shotgun proteomics involves digesting the proteins, sequencing the resulting peptides by data-dependent mass spectrometry (MS/MS), and searching protein databases to identify the proteins from which the peptides are derived. Manual analysis and direct spectral comparison reveal that scores from two commonly used search programs (Sequest and Mascot) validate less than half of potentially identifiable MS/MS spectra (class positive) from shotgun analyses of the human erythroleukemia K562 cell line. Here we demonstrate increased sensitivity and accuracy using a focused search strategy along with a peptide sequence validation script that does not rely exclusively on XCorr or Mowse scores generated by Sequest or Mascot, but uses consensus between the search programs, along with chemical properties and scores describing the nature of the fragmentation spectrum (ion score and RSP). The approach yielded 4.2% false positive and 8% false negative frequencies in peptide assignments. The protein profile is then assembled from peptide assignments using a novel peptide-centric protein nomenclature that more accurately reports protein variants that contain identical peptide sequences. An Isoform Resolver algorithm ensures that the protein count is not inflated by variants in the protein database, eliminating approximately 25% of redundant proteins. Analysis of soluble proteins from a human K562 cells identified 5130 unique proteins, with approximately 100 false positive protein assignments.