Multi-omic data integration enables discovery of hidden biological regularities

Nature Communications

Volumn 7, Issue , 2016, Pages

  Ebrahim, Ali ^a   Brunk, Elizabeth ^a,b   Tan, Justin ^a   O'Brien, Edward J ^c   Kim, Donghyuk ^a   Szubin, Richard ^a   Lerman, Joshua A ^c   Lechner, Anna ^d   Sastry, Anand ^a   Bordbar, Aarash ^a   Feist, Adam M ^a,b   Palsson, Bernhard O ^a,b,c,e  

^a UNIVERSITY OF CALIFORNIA SAN DIEGO   (United States)

^b Chalmers University of Technology   (Denmark)

^c UNIVERSITY OF CALIFORNIA   (United States)

^d UNIVERSITY OF CALIFORNIA   (United States)

^e UNIVERSITY OF CALIFORNIA SAN DIEGO   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

MESSENGER RNA; BACTERIAL PROTEIN; BACTERIAL RNA; ENZYME;

BACTERIUM; DATA SET; ENZYME ACTIVITY; GROWTH RATE; PROTEIN; PROTEOMICS; RNA;

ARTICLE; BACTERIAL GENOME; BIOMICS; ESCHERICHIA COLI; GENOMICS; IN VIVO STUDY; PROTEIN MOTIF; PROTEIN SECONDARY STRUCTURE; PROTEIN STRUCTURE; PROTEOMICS; QUANTITATIVE ANALYSIS; RIBOSOME; TRANSCRIPTOMICS; TURNOVER TIME; BIOLOGICAL MODEL; GENE EXPRESSION PROFILING; GENETICS; INFORMATION PROCESSING; METABOLISM; PHYSIOLOGY; PROCEDURES;

ESCHERICHIA COLI;

BACTERIAL PROTEINS; DATASETS AS TOPIC; ENZYMES; ESCHERICHIA COLI; GENE EXPRESSION PROFILING; MODELS, BIOLOGICAL; PROTEOMICS; RIBOSOMES; RNA, BACTERIAL; RNA, MESSENGER;

EID: 84992648219     PISSN: None     EISSN: 20411723     Source Type: Journal    
DOI: 10.1038/ncomms13091     Document Type: Article

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