Uncovering distinct protein-network topologies in heterogeneous cell populations

BMC Systems Biology

Volumn 9, Issue 1, 2015, Pages

  Wieczorek, Jakob ^a   Malik Sheriff, Rahuman S ^b,c,d   Fermin, Yessica ^a   Grecco, Hernán E ^b,e   Zamir, Eli ^b   Ickstadt, Katja ^a  

^a TU DORTMUND UNIVERSITY   (Germany)

^b MAX PLANCK INSTITUTE OF MOLECULAR PHYSIOLOGY   (Germany)

^c EUROPEAN BIOINFORMATICS INSTITUTE   (United Kingdom)

^d MRC CLINICAL SCIENCES CENTRE   (United Kingdom)

^e UNIVERSIDAD DE BUENOS AIRES   (Argentina)

Author keywords

Bayesian analysis; Cluster analysis; Intercellular variability; Network analysis; Protein networks; Reverse engineering; Unmixing

Indexed keywords

EPIDERMAL GROWTH FACTOR; MITOGEN ACTIVATED PROTEIN KINASE; NERVE GROWTH FACTOR; RAF PROTEIN;

ANIMAL; BAYES THEOREM; BIOLOGICAL MODEL; BIOLOGY; DRUG EFFECTS; METABOLISM; PC12 CELL LINE; PROCEDURES; PROTEIN PROTEIN INTERACTION; RAT;

ANIMALS; BAYES THEOREM; COMPUTATIONAL BIOLOGY; EPIDERMAL GROWTH FACTOR; MITOGEN-ACTIVATED PROTEIN KINASES; MODELS, BIOLOGICAL; NERVE GROWTH FACTOR; PC12 CELLS; PROTEIN INTERACTION MAPS; RAF KINASES; RATS;

EID: 84933499980     PISSN: None     EISSN: 17520509     Source Type: Journal    
DOI: 10.1186/s12918-015-0170-2     Document Type: Article

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