A transcriptomics data-driven gene space accurately predicts liver cytopathology and drug-induced liver injury

Nature Communications

Volumn 8, Issue , 2017, Pages

  Kohonen, Pekka ^a   Parkkinen, Juuso A ^b   Willighagen, Egon L ^a,c   Ceder, Rebecca ^a   Wennerberg, Krister ^d   Kaski, Samuel ^b,d   Grafström, Roland C ^a  

^a KAROLINSKA INSTITUTE   (Sweden)

^b AALTO UNIVERSITY   (Finland)

^c MAASTRICHT UNIVERSITY   (Netherlands)

^d UNIVERSITY OF HELSINKI   (Finland)

Author keywords

[No Author keywords available]

Indexed keywords

ANATOMY; CELLS AND CELL COMPONENTS; DATA SET; DRUG; EXPERIMENTAL STUDY; GENE; GENETIC ANALYSIS; GENOMICS; HISTOPATHOLOGY; INJURY; PREDICTION; PROBABILITY; TOXICITY;

ACCURACY; ARTICLE; CONTROLLED STUDY; CYTOPATHOLOGY; CYTOTOXICITY; CYTOTOXICITY ASSAY; HIGH THROUGHPUT SCREENING; HUMAN; HUMAN CELL; LIVER CELL; NONHUMAN; PREDICTIVE VALUE; RAT; TOXIC HEPATITIS; TOXICOGENETICS; TRANSCRIPTOMICS; ANIMAL; BIOLOGICAL MODEL; DRUG EFFECT; GENE EXPRESSION PROFILING; GENETICS; LIVER; METABOLISM; PATHOLOGY;

RATTUS;

DRUG; PROTEIN;

ANIMALS; CHEMICAL AND DRUG INDUCED LIVER INJURY; GENE EXPRESSION PROFILING; HEPATOCYTES; HUMANS; LIVER; MODELS, BIOLOGICAL; PHARMACEUTICAL PREPARATIONS; PROTEINS; RATS; TOXICOGENETICS;

EID: 85021759690     PISSN: None     EISSN: 20411723     Source Type: Journal    
DOI: 10.1038/ncomms15932     Document Type: Article

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