The Human Plasma Proteome History, Character, and Diagnostic Prospects

'Stealth' corona-core nanoparticles surface modified by polyethylene glycol (PEG): influences of the corona (PEG chain length and surface density) and of the core composition on phagocytic uptake and plasma protein adsorption.

(1996). Progress with Proteome Projects: Why all Proteins Expressed by a Genome Should be Identified and How To Do It. Biotechnology and Genetic Engineering Reviews: Vol. 13, No. 1, pp. 19-50.

Progress with Proteome Projects: Why all Proteins Expressed by a Genome Should be Identified and How To Do It

http://plasmaproteome.com/Papers/Non-redundant%20plasma%20proteome%20MCP.pdf

The Human Plasma Proteome A Nonredundant List Developed by Combination of Four Separate Sources

The goal of proteomics is a comprehensive, quantitative description of protein expression and its changes under the influence of biological perturbations such as disease or drug treatment. Quantitative analysis of protein expression data obtained by high-throughput methods has led us to define the concept of “regulatory homology” and use it to begin to elucidate the basic structure of gene expression control in vivo. Such investigations lay the groundwork for construction of comprehensive databases of mechanisms (cataloguing possible biological outcomes), the next logical step after the soon to be completed cataloguing of genes and gene products. Mechanism databases provide a roadmap towards effective therapeutic intervention that is more direct than that offered by conventional genomics approaches.

Proteome and proteomics: New technologies, new concepts, and new words

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 protein spots shown on HR 2D-PAGE images. Classification programs help the physician to find disease-associated patterns from a given set of two-dimensional gel electrophoresis images and to form diagnostic rules. Prototype expert systems that use these rules to establish a diagnosis from new HR 2D-PAGE images have been developed. They successfully diagnosed cirrhosis of the liver and were able to distinguish a variety of cancer types from biopsies known to be cancerous.

The MELANIE project: From a biopsy to automatic protein map interpretation by computer

Protein heterogeneity of lipoprotein particles containing apolipoprotein A-I without apolipoprotein A-II and apolipoprotein A-I with apolipoprotein A-II isolated from human plasma.

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 heuristic clustering analysis. This program is a step toward machine learning. In this publication, we describe the classification method and the preliminary results obtained with liver biopsy electrophoretograms. Heuristic clustering is also compared to other classification techniques.

Automatic classification of two-dimensional gel electrophoresis pictures by heuristic clustering analysis: a step toward machine learning.

Isoelectric focusing in mixed carrier ampholyte-immobilized pH gradients (CA-IPG) is an effective way to separate proteins by charge. A method to prepare CA-IPG in capillary tubes and the description of the equipment used are outlined. Two-dimensional gel electrophoresis patterns of human serum and liver biopsies, with isoelectric focusing and CA-IPG as the first dimension, are presented. The comparison with two-dimensional gel electrophoresis patterns obtained by conventional carrier ampholyte pH gradient separation shows the excellent resolution and potential of this technique.

Immobilized pH gradients in capillary tubes and two-dimensional gel electrophoresis

We developed an expert system to analyze and interpret protein maps. This system, Melanie (medical electrophoresis analysis interactive expert), can distinguish between normal and cirrhotic liver and identify various types of cancer on the basis of protein patterns in biopsy specimens. Our findings suggest that some diseases associated with toxic compounds or modifications of the human genome can be diagnosed by expert systems that analyze protein maps. The combination of protein mapping and computer analysis could result in a clinically useful "molecular scanner". The massive amount of information analyzed and stored in such studies requires new strategies, including centralized databases and image transmission over networks. Increased understanding of protein expression and regulation will enhance the importance of the human genome project in medicine and biology.

A F Muller

Papers

The MELANIE project: From a biopsy to automatic protein map interpretation by computer

Protein heterogeneity of lipoprotein particles containing apolipoprotein A-I without apolipoprotein A-II and apolipoprotein A-I with apolipoprotein A-II isolated from human plasma.

Automatic classification of two-dimensional gel electrophoresis pictures by heuristic clustering analysis: a step toward machine learning.

Immobilized pH gradients in capillary tubes and two-dimensional gel electrophoresis

A clinical molecular scanner: the Melanie project.