Scientific discovery as a combinatorial optimisation problem: How best to navigate the landscape of possible experiments?

BioEssays

Volumn 34, Issue 3, 2012, Pages 236-244

  Kell, Douglas B ^a,b  

^a UNIVERSITY OF MANCHESTER   (United Kingdom)

^b INSTITUTE OF FOOD RESEARCH   (United Kingdom)

Author keywords

Automation; Epistemology; Evolutionary computing; Heuristics; Scientific discovery

Indexed keywords

IMMUNOGLOBULIN ENHANCER BINDING PROTEIN; NUCLEIC ACID;

ARTICLE; BAYESIAN LEARNING; BIOTECHNOLOGY; COMBINATORIAL CHEMISTRY; COMPUTER MODEL; DRUG TARGETING; EPISTEMOLOGY; EVOLUTION; FERMENTATION; GENETIC ENGINEERING; LANDSCAPE; LEARNING ALGORITHM; METABOLIC ENGINEERING; REPRODUCTIVE FITNESS; SCIENTIFIC LITERATURE; SYNTHETIC BIOLOGY;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; BAYES THEOREM; BIOLOGICAL EVOLUTION; COMPUTATIONAL BIOLOGY; COMPUTERS; DATA MINING; DRUG DISCOVERY; HUMANS; METABOLIC ENGINEERING; SENSITIVITY AND SPECIFICITY; SYNTHETIC BIOLOGY;

EID: 84857045254     PISSN: 02659247     EISSN: 15211878     Source Type: Journal    
DOI: 10.1002/bies.201100144     Document Type: Article

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