A methodology for exploring biomarker - phenotype associations: Application to flow cytometry data and systemic sclerosis clinical manifestations

BMC Bioinformatics

Volumn 16, Issue 1, 2015, Pages

  Huang, Hongtai ^a   Fava, Andrea ^b   Guhr, Tara ^b   Cimbro, Raffaello ^b   Rosen, Antony ^b   Boin, Francesco ^b,c   Ellis, Hugh ^a  

^a JOHNS HOPKINS UNIVERSITY   (United States)

^b JOHNS HOPKINS UNIVERSITY SCHOOL OF MEDICINE   (United States)

^c UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

Conditional random forests; Flow cytometry; Gene set enrichment analysis; Interstitial lung disease; Scleroderma

Indexed keywords

ARTIFICIAL INTELLIGENCE; BIOLOGICAL ORGANS; BIOMARKERS; CLASSIFICATION (OF INFORMATION); DECISION TREES; FLOW CYTOMETRY; GENES; LEARNING SYSTEMS; MULTIVARIABLE SYSTEMS; PATIENT TREATMENT; PULMONARY DISEASES; RANDOM PROCESSES; RISK ASSESSMENT; SET THEORY; STOCHASTIC MODELS; STOCHASTIC SYSTEMS;

CLINICAL MANIFESTATION; COORDINATED MOVEMENT; GENE SET ENRICHMENT ANALYSIS; INTERSTITIAL LUNG DISEASE; RANDOM FORESTS; SCLERODERMA; STOCHASTIC SIMULATIONS; THERAPEUTIC INTERVENTION;

DIAGNOSIS;

BIOLOGICAL MARKER;

COHORT ANALYSIS; DISEASE COURSE; FLOW CYTOMETRY; HUMAN; LUNG DISEASES, INTERSTITIAL; MACHINE LEARNING; METABOLISM; PHENOTYPE; PROCEDURES; RECEIVER OPERATING CHARACTERISTIC; SCLERODERMA, SYSTEMIC; SUPPORT VECTOR MACHINE;

BIOMARKERS; COHORT STUDIES; DISEASE PROGRESSION; FLOW CYTOMETRY; HUMANS; LUNG DISEASES, INTERSTITIAL; MACHINE LEARNING; PHENOTYPE; ROC CURVE; SCLERODERMA, SYSTEMIC; SUPPORT VECTOR MACHINE;

EID: 84941636848     PISSN: None     EISSN: 14712105     Source Type: Journal    
DOI: 10.1186/s12859-015-0722-x     Document Type: Article

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