After two generations of software systems for the analysis of two-dimensional electrophoresis (2-DE) images, a third generation of such software packages has recently emerged that combines state-of-the-art graphical user interfaces with comprehensive spot data analysis capabilities. A key characteristic common to most of these software packages is that many of their tools are implementations of algorithms that resulted from research areas such as image processing, vision, artificial intelligence or machine learning. This article presents the main algorithms implemented in the Melanie II 2-D PAGE software package. The applications of these algorithms, embodied as the feature of the program, are explained in an accompanying article (R. D. Appel et al.; Electrophoresis 1997, 18, 2724-2734).

Identification and characterization of all proteins expressed by a genome in biological samples represent major challenges in proteomics. Today's commonly used high-throughput approaches combine two-dimensional electrophoresis (2-DE) with peptide mass fingerprinting (PMF) analysis. Although automation is often possible, a number of limitations still adversely affect the rate of protein identification and annotation in 2-DE databases: the sequential excision process of pieces of gel containing protein; the enzymatic digestion step; the interpretation of mass spectra (reliability of identifications); and the manual updating of 2-DE databases. We present a highly automated method that generates a fully annotated 2-DE map. Using a parallel process, all proteins of a 2-DE are first simultaneously digested proteolytically and electrotransferred onto a poly(vinylidene difluoride) membrane. The membrane is then directly scanned by MALDI-TOF MS. After automated protein identification from the obtained peptide mass fingerprints using PeptIdent software (http://www.expasy.ch/tools/peptident.html), a fully annotated 2-D map is created on-line. It is a multidimensional representation of a proteome that contains interpreted PMF data in addition to protein identification results. This "MS-imaging" method represents a major step toward the development of a clinical molecular scanner.

Images obtained from high-throughput mass spectrometry (MS) contain information that remains hidden when looking at a single spectrum at a time. Image processing of liquid chromatography-MS datasets can be extremely useful for quality control, experimental monitoring and knowledge extraction. The importance of imaging in differential analysis of proteomic experiments has already been established through two-dimensional gels and can now be foreseen with MS images. We present MSight, a new software designed to construct and manipulate MS images, as well as to facilitate their analysis and comparison.

Bioinformatics tools for proteomics, also called proteome informatics tools, span today a large panel of very diverse applications ranging from simple tools to compare protein amino acid compositions to sophisticated software for large-scale protein structure determination. This review considers the available and ready to use tools that can help end-users to interpret, validate and generate biological information from their experimental data. It concentrates on bioinformatics tools for 2-DE analysis, for LC followed by MS analysis, for protein identification by PMF, by peptide fragment fingerprinting and by de novo sequencing and for data quantitation with MS data. It also discloses initiatives that propose to automate the processes of MS analysis and enhance the quality of the obtained results.

Although two-dimensional electrophoresis (2-DE) computer analysis software packages have existed ever since 2-DE technology was developed, it is only now that the hardware and software technology allows large-scale studies to be performed on low-cost personal computers or workstations, and that setting up a 2-DE computer analysis system in a small laboratory is no longer considered a luxury. After a first attempt in the seventies and early eighties to develop 2-DE analysis software systems on hardware that had poor or even no graphical capabilities, followed in the late eighties by a wave of innovative software developments that were possible thanks to new graphical interface standards such as XWindows, a third generation of 2-DE analysis software packages has now come to maturity. It can be run on a variety of low-cost, general-purpose personal computers, thus making the purchase of a 2-DE analysis system easily attainable for even the smallest laboratory that is involved in proteome research. Melanie II 2-D PAGE, developed at the University Hospital of Geneva, is such a third-generation software system for 2-DE analysis. Based on unique image processing algorithms, this user-friendly object-oriented software package runs on multiple platforms, including Unix, MS-Windows 95 and NT, and Power Macintosh. It provides efficient spot detection and quantitation, state-of-the-art image comparison, statistical data analysis facilities, and is Internet-ready. Linked to proteome databases such as those available on the World Wide Web, it represents a valuable tool for the "Virtual Lab" of the post-genome area.