Selected article for: "analysis method and linear combination"

Author: Hoffmann, Geoffrey W.
Title: Proteomic analyser with applications to diagnostics and vaccines
  • Cord-id: kaxcxynk
  • Document date: 2004_6_21
  • ID: kaxcxynk
    Snippet: This paper describes a method for proteomic analysis with applications to diagnostics and vaccines. A panel of N (⪢1) reagents called X(j), with j=1 to N, is used. The binding strength of each of the X(j) reagents to each other is measured, for example by an ELISA assay, giving an N×N matrix K. The matrix K is used to define another set of N reagents called Y(j), with j=1 to N, each of which is a linear combination of the X(j) reagents and each of which is tailored to be complementary to one
    Document: This paper describes a method for proteomic analysis with applications to diagnostics and vaccines. A panel of N (⪢1) reagents called X(j), with j=1 to N, is used. The binding strength of each of the X(j) reagents to each other is measured, for example by an ELISA assay, giving an N×N matrix K. The matrix K is used to define another set of N reagents called Y(j), with j=1 to N, each of which is a linear combination of the X(j) reagents and each of which is tailored to be complementary to one of the X(j) reagents. Each of the N pairs of reagents X(j) and Y(j) defines an axis in an N-dimensional shape space. The definition of these axes facilitates proteomic analysis of diverse biological samples, for example, mixtures of proteins such as serum samples or T cell extracts. A method for defining and measuring similarity between pairs of biological samples and between sets of biological samples in the context of the set of N reagent pairs is described. This leads to methods for using the N reagent pairs in the diagnosis of diseases and in the formulation of preventive and therapeutic vaccines. The relationship of this work to previous research on shape space is discussed.

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