Generating Information-Rich High-Throughput Experimental Materials Genomes using Functional Clustering via Multitree Genetic Programming and Information Theory

ACS Combinatorial Science

Volumn 17, Issue 4, 2015, Pages 224-233

  Suram, Santosh K ^a   Haber, Joel A ^a   Jin, Jian ^b   Gregoire, John M ^a  

^a CALIFORNIA INSTITUTE OF TECHNOLOGY   (United States)

^b LAWRENCE BERKELEY NATIONAL LABORATORY   (United States)

Author keywords

Clustering; Combinatorial science; Down selection; Functional relationships; High throughput experimentation; Informatics; Information theory; Materials genomes; Multitree genetic programming

Indexed keywords

ALGORITHM; CLUSTER ANALYSIS; COMBINATORIAL CHEMISTRY; GENOME; INFORMATION SCIENCE; MATERIALS TESTING; PROCEDURES;

ALGORITHMS; CLUSTER ANALYSIS; COMBINATORIAL CHEMISTRY TECHNIQUES; GENOME; INFORMATION THEORY; MATERIALS TESTING;

EID: 84927934764     PISSN: 21568952     EISSN: None     Source Type: Journal    
DOI: 10.1021/co5001579     Document Type: Article

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