A framework for analytical characterization of monoclonal antibodies based on reactivity profiles in different tissues
Author(s) -
Elizabeth J. Rossin,
TsungI Lin,
Hsiu J. Ho,
Steven J. Mentzer,
Saumyadipta Pyne
Publication year - 2011
Publication title -
bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.599
H-Index - 390
eISSN - 1367-4811
pISSN - 1367-4803
DOI - 10.1093/bioinformatics/btr468
Subject(s) - monoclonal antibody , characterization (materials science) , reactivity (psychology) , computer science , computational biology , antibody , chemistry , biology , immunology , materials science , nanotechnology , medicine , pathology , alternative medicine
Monoclonal antibodies (mAbs) are among the most powerful and important tools in biology and medicine. MAb development is of great significance to many research and clinical applications. Therefore, objective mAb classification is essential for categorizing and comparing mAb panels based on their reactivity patterns in different cellular species. However, typical flow cytometric mAb profiles present unique modeling challenges with their non-Gaussian features and intersample variations. It makes accurate mAb classification difficult to do with the currently used kernel-based or hierarchical clustering techniques.
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