KNIME for reproducible cross-domain analysis of life science data

Journal of Biotechnology

Volumn 261, Issue , 2017, Pages 149-156

  Fillbrunn, Alexander ^a   Dietz, Christian ^a   Pfeuffer, Julianus ^b   Rahn, René ^c   Landrum, Gregory A ^d   Berthold, Michael R ^a,d  

^a UNIVERSITY OF KONSTANZ   (Germany)

^b UNIVERSITY OF TÜBINGEN   (Germany)

^c FREIE UNIVERSITÄT BERLIN   (Germany)

^d KNIMEcom AG   (Switzerland)

Author keywords

KNIME; Life science; Workflow systems

Indexed keywords

DATA FLOW ANALYSIS; DATA VISUALIZATION; IMAGE PROCESSING; MASS SPECTROMETRY; OPEN SOURCE SOFTWARE; OPEN SYSTEMS;

DATA EXPLORATION; DATA TRANSFORMATION; KNIME; LIFE-SCIENCES; NEXT-GENERATION SEQUENCING; REPRODUCIBILITIES; SCIENTIFIC COMMUNITY; WORK-FLOW SYSTEMS;

METADATA;

ARTICLE; BIOMEDICINE; COMPARATIVE STUDY; DATA ANALYSIS; IMAGE PROCESSING; KNIME; PRIORITY JOURNAL; SOFTWARE; WORKFLOW; BIOLOGY; HIGH THROUGHPUT SEQUENCING; MASS SPECTROMETRY;

BIOLOGICAL SCIENCE DISCIPLINES; COMPUTATIONAL BIOLOGY; HIGH-THROUGHPUT NUCLEOTIDE SEQUENCING; IMAGE PROCESSING, COMPUTER-ASSISTED; MASS SPECTROMETRY; SOFTWARE;

EID: 85028043725     PISSN: 01681656     EISSN: 18734863     Source Type: Journal    
DOI: 10.1016/j.jbiotec.2017.07.028     Document Type: Review

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