Quantifying critical states of complex diseases using single-sample dynamic network biomarkers

PLoS Computational Biology

Volumn 13, Issue 7, 2017, Pages

  Liu, Xiaoping ^a,b,c,d   Chang, Xiao ^a,b   Liu, Rui ^e   Yu, Xiangtian ^c   Chen, Luonan ^a,c,f   Aihara, Kazuyuki ^a  

^a INSTITUTE OF INDUSTRIAL SCIENCE   (Japan)

^b ANHUI UNIVERSITY OF FINANCE AND ECONOMICS   (China)

^c INSTITUTE OF BIOCHEMISTRY AND CELL BIOLOGY   (China)

^d SHANDONG UNIVERSITY   (China)

^e SOUTH CHINA UNIVERSITY OF TECHNOLOGY   (China)

^f SHANGHAITECH UNIVERSITY   (China)

Author keywords

[No Author keywords available]

Indexed keywords

CRITICAL CURRENT DENSITY (SUPERCONDUCTIVITY); DIAGNOSIS; DISEASES; FORECASTING; PATHOLOGY; VIRUSES;

CLINICAL PRACTICES; COMPLEX DISEASE; CRITICAL-STATE; DYNAMIC NETWORK; EARLY WARNING; INFLUENZA VIRUS; MULTIPLE SAMPLES; NOVEL METHODS; SINGLE SAMPLE; VIRUS INFECTION;

BIOMARKERS;

BIOLOGICAL MARKER; TUMOR MARKER;

ACCURACY; ALGORITHM; ARTICLE; DISEASE COURSE; INFLUENZA; LUNG CANCER; MEDICAL PROCEDURES; METASTASIS; PREDICTION; SCORING SYSTEM; SINGLE SAMPLE DYNAMIC NETWORK BIOMARKER; STOMACH CANCER; SYMPTOM; THYROID CANCER; COMPUTER ASSISTED DIAGNOSIS; HUMAN; METABOLISM; NEOPLASMS; PROCEDURES; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY; SIGNAL TRANSDUCTION; STATISTICAL ANALYSIS;

ALGORITHMS; BIOMARKERS, TUMOR; DATA INTERPRETATION, STATISTICAL; DIAGNOSIS, COMPUTER-ASSISTED; DISEASE PROGRESSION; HUMANS; NEOPLASMS; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; SIGNAL TRANSDUCTION;

EID: 85026408588     PISSN: 1553734X     EISSN: 15537358     Source Type: Journal    
DOI: 10.1371/journal.pcbi.1005633     Document Type: Article

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