Affiliation:
1. Laboratoire Gulliver UMR 7083 CNRS ESPCI Paris PSL Research University 10 rue Vauquelin Paris 75005 France
2. LIMMS CNRS‐Institute of Industrial Science IRL 2820 University of Tokyo Tokyo 153‐8505 Japan
Abstract
AbstractDNA as an informational polymer has, for the past 30 years, progressively become an essential molecule to rationally build chemical reaction networks endowed with powerful signal‐processing capabilities. Whether influenced by the silicon world or inspired by natural computation, molecular programming has gained attention for diagnosis applications. Of particular interest for this review, molecular classifiers have shown promising results for disease pattern recognition and sample classification. Because both input integration and computation are performed in a single tube, at the molecular level, this low‐cost approach may come as a complementary tool to molecular profiling strategies, where all biomarkers are quantified independently using high‐tech instrumentation. After introducing the elementary components of molecular classifiers, some of their experimental implementations are discussed either using digital Boolean logic or analog neural network architectures.
Funder
European Research Council
Subject
General Biochemistry, Genetics and Molecular Biology,Biomedical Engineering,Biomaterials
Cited by
5 articles.
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