Christian Pellegrini

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Among the many applications of mass spectrometry, biomarker pattern discovery from protein mass spectra has aroused considerable interest in the past few years. While research efforts have raised hopes of early and less invasive diagnosis, they have also brought to light the many issues to be tackled before mass-spectra-based proteomic patterns become(More)
We addressed the problem of discriminating between 24 diseased and 17 healthy specimens on the basis of protein mass spectra. To prepare the data, we performed mass to charge ratio (m/z) normalization, baseline elimination, and conversion of absolute peak height measures to height ratios. After preprocessing, the major difficulty encountered was the(More)
The interpretation of two-dimensional gel electrophoresis (2-DGE) profiles can be facilitated by artificial intelligence and machine learning programs. We have incorporated into our 2-DGE computer analysis system (termed MELANIE-Medical Electrophoresis Analysis Interactive Expert system) a program which automatically classifies 2-DGE patterns using(More)
The goals of the MELANIE project are to determine if disease-associated patterns can be detected in high resolution two-dimensional polyacrylamide gel electrophoresis (HR 2D-PAGE) images and if a diagnosis can be established automatically by computer. The ELSIE/MELANIE system is a set of computer programs which automatically detect, quantify, and compare(More)
Image processing in biomedical research has become customary, along with use of colour displays to run image processing packages. The performance of softwares is highly dependent on the device they run on: architecture of colour display, depth of frame buffer, existence of look-up table, etc. Knowledge of such basic features is therefore becoming very(More)
In this paper we describe a divide-and-combine strategy for decomposition of a complex prediction problem into simpler local sub-problems. We rstly show how to perform a soft decomposition via clustering of input data. Such decomposition leads to a partition of the input space into several regions which may overlap. Therefore, to each region is assigned a(More)
Although two-dimensional (2-D) gel electrophoresis is one of the most powerful techniques for analyzing protein mixtures, its application in routine clinical laboratories is currently limited, because it is time-consuming, complex, and relatively expensive. Here we describe a method for automatically running and staining "high-resolution" mini 2-D(More)
TH ESE pr esent ee a la Facult e des Sciences de l'Universit e de Gen eve pour obtenir le grade de Docteur es sciences, mention informatique par Murhimanya MUHUGUSA de Bukavu (Za re) Th ese No 2903 Gen eve 1997 La Facult e des sciences, sur le pr eavis de Messieurs J. Harms, professeur ordinaire et directeur de th ese (D epartement d'informatique), C.(More)
Knowledge Acquisition by the Domain Expert Using the Tool HEMATOOL p. 122 Application of Inductive Logic Programming for Learning ECG Waveforms p. 126 Knowledge Discovery from a Breast Cancer Database p. 130 An Adaptive Two-Tier Menu Approach to Support On-Line Entry of Diagnoses p. 134 Machine Learning Applied to Diagnosis of Sport Injuries p. 138 A(More)
A powerful data processing methodology for analysis and classification of two-dimensional gels is introduced. The approach is based on correspondence analysis (CA) and ascendant hierarchical classification (AHC), and significantly differs from the more classical principal-component decomposition. Starting with a series of gels, each having a large number of(More)