Abstract: The disclosed subject matter relates to a method of simultaneously identifying and determining the levels of expression of cysteine-containing proteins in normal and perturbed cells, a method for determining peptide expression levels between a first biological sample and a second biological sample, and a method for quantitative proteomic analysis of two or more peptide populations, and compounds and reagents related thereto.

Abstract: The present invention relates to a system and methods for identifying differential peptide expression in one or more peptide populations. Each population is labeled with a discernable label and provides a mechanism to resolve mixed peptide populations using mass spectroscopy-based techniques. Spectra produced by the peptide sample are used to interrogate a spectral database in which peptide sequences of known spectra are stored. In addition to providing sequence information, the methods presented herein may be used to determine qualitative and quantitative measurements of peptide expression. These measurements may further be used to determine proteomic differences and novel peptide expression.

Abstract: The present invention relates to a system and methods for identifying differential peptide expression in one or more peptide populations. Each population is labeled with a discernable label and provides a mechanism to resolve mixed peptide populations using mass spectroscopy-based techniques. Spectra produced by the peptide sample are used to interrogate a spectral database in which peptide sequences of known spectra are stored. In addition to providing sequence information, the methods presented herein may be used to determine qualitative and quantitative measurements of peptide expression. These measurements may further be used to determine proteomic differences and novel peptide expression.

Abstract: The present invention relates to a system and methods for facilitating the analysis of proteomic expression data. In this system, complex sequence-correlated peptide expression information and mass spectrum data are processed and stored in a relational database. Using a parallel computational method, the expression data and results are parsed and associated to rapidly yield peptide sequence information. The system automates necessary tasks associated with peptide data analysis and organizes large amounts of information needed to perform the data analysis in a logical and accessible manner.