PBMDA: A novel and effective path-based computational model for miRNA-disease association prediction

PLoS Computational Biology

Volumn 13, Issue 3, 2017, Pages

  You, Zhu Hong ^a   Huang, Zhi An ^b   Zhu, Zexuan ^b   Yan, Gui Ying ^c   Li, Zheng Wei ^d   Wen, Zhenkun ^b   Chen, Xing ^d  

^a XINJIANG TECHNICAL INSTITUTE OF PHYSICS AND CHEMISTRY   (China)

^b SHENZHEN UNIVERSITY   (China)

^c CHINESE ACADEMY OF SCIENCES   (China)

^d CHINA UNIVERSITY OF MINING AND TECHNOLOGY   (China)

Author keywords

[No Author keywords available]

Indexed keywords

ASSOCIATION REACTIONS; COMPUTATIONAL METHODS; DIAGNOSIS; FORECASTING; RNA; SEMANTICS;

BIOLOGICAL EXPERIMENTS; BIOLOGICAL PROCESS; CASE-STUDIES; COMPLEX DISEASE; COMPUTATIONAL MODELLING; DISEASE ASSOCIATIONS; MOLECULAR MECHANISM; PATH-BASED; PREDICTION MODELLING; RELIABLE PERFORMANCE;

TUMORS;

MICRORNA; TUMOR MARKER;

ALGORITHM; ARTICLE; COLON CANCER; DISEASE ASSOCIATION; ESOPHAGUS CANCER; HUMAN; KIDNEY CANCER; MATHEMATICAL COMPUTING; MATHEMATICAL MODEL; MOLECULAR DYNAMICS; PHENOTYPE; PREDICTION; RELIABILITY; VALIDATION STUDY; BIOLOGICAL MODEL; COMPUTER SIMULATION; GENETIC ASSOCIATION STUDY; GENETIC PREDISPOSITION; GENETICS; NEOPLASMS; PREVALENCE; PROCEDURES; PROGNOSIS; RISK ASSESSMENT; RISK FACTOR; SIGNAL TRANSDUCTION; STATISTICAL MODEL;

BIOMARKERS, TUMOR; COMPUTER SIMULATION; GENETIC ASSOCIATION STUDIES; GENETIC PREDISPOSITION TO DISEASE; HUMANS; MICRORNAS; MODELS, GENETIC; MODELS, STATISTICAL; NEOPLASMS; PREVALENCE; PROGNOSIS; RISK ASSESSMENT; RISK FACTORS; SIGNAL TRANSDUCTION;

EID: 85016736049     PISSN: 1553734X     EISSN: 15537358     Source Type: Journal    
DOI: 10.1371/journal.pcbi.1005455     Document Type: Article

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