Inflammatory diseases, which include many infectious and autoimmune diseases, malignant tumors, cardiovascular diseases, diabetes, and another chronic noninfectious disease (NCDs) that fall under the category of inflammatory diseases, have emerged as one of the major threats affecting the health of the global population as a result of increasing urbanization, the aging process, and lifestyle changes. These illnesses are becoming major public health issues that pose a serious threat to both human health and socioeconomic sustainability. New methods for disease prevention, diagnosis, and therapy will be developed by doing research on the mechanisms of inflammation occurrence and progression among these diverse diseases.
Biomedical research in pharmacology and medicine in the 21st century is undergoing a change from conventional laboratory methods to new digital methods facilitated by the application of high-performance computing and big data analytic methods. The challenges of big data in biomedical research of pharmacology and medicine include big data capturing, analysis, information retrieval, transfer and visualization, and information privacy protection. The research domains have encompassed the amount, variety, and velocity of big data in addition to other pertinent technology methods such as high throughput data analysis, machine learning, natural language processing, medical knowledge representation, and healthcare decision making. When these techniques are used simultaneously on the same biospecimen, they produce information with astounding molecular accuracy that can be enhanced by various imaging data types, biosignals, or clinical records.
This Special Issue aims to provide the academic frontiers in computational methods for biomedical research of pharmacology and medicine in healthcare big data. It intends to bring together new findings of inflammation disease research related to big data, bioinformatics, and precision medicine. Papers having strong linkages to inflammatory disease-associated multi-omic integration, big data analytics, and health monitoring/diagnostic applications are encouraged. In addition, experimental verification related to inflammation disease except for big data analysis for biomedical research is considered necessary.
This Research Topic welcomes the submissions of all types covering, but not limited to, the following areas:
• Using proteomics and metabonomics to explain inflammation-related research
• Advances in inflammation disease multi-omic integration
• Bioinformatics and experimental verification for inflammatory diseases
• Network pharmacology of new drugs in the treatment of inflammation disease
• Computational modeling, data integration, and large-scale recommenders for medicine
• Predictive analytics on biomedical/ health big data
• Machine learning and deep learning for biomedical/health big data in inflammation disease
• Biomedical and health big data management and analytics in inflammation disease
• Inflammation disease drugs molecular network modeling/visualization
• Laboratory validation of inflammation disease key pathogenic genes
• Intelligent pharmacogenomic analysis in inflammation disease
• Progress in inflammation disease pathological research
• Precision medicine in the treatment of inflammatory diseases
• Inflammation disease clinical big data analysis
Inflammatory diseases, which include many infectious and autoimmune diseases, malignant tumors, cardiovascular diseases, diabetes, and another chronic noninfectious disease (NCDs) that fall under the category of inflammatory diseases, have emerged as one of the major threats affecting the health of the global population as a result of increasing urbanization, the aging process, and lifestyle changes. These illnesses are becoming major public health issues that pose a serious threat to both human health and socioeconomic sustainability. New methods for disease prevention, diagnosis, and therapy will be developed by doing research on the mechanisms of inflammation occurrence and progression among these diverse diseases.
Biomedical research in pharmacology and medicine in the 21st century is undergoing a change from conventional laboratory methods to new digital methods facilitated by the application of high-performance computing and big data analytic methods. The challenges of big data in biomedical research of pharmacology and medicine include big data capturing, analysis, information retrieval, transfer and visualization, and information privacy protection. The research domains have encompassed the amount, variety, and velocity of big data in addition to other pertinent technology methods such as high throughput data analysis, machine learning, natural language processing, medical knowledge representation, and healthcare decision making. When these techniques are used simultaneously on the same biospecimen, they produce information with astounding molecular accuracy that can be enhanced by various imaging data types, biosignals, or clinical records.
This Special Issue aims to provide the academic frontiers in computational methods for biomedical research of pharmacology and medicine in healthcare big data. It intends to bring together new findings of inflammation disease research related to big data, bioinformatics, and precision medicine. Papers having strong linkages to inflammatory disease-associated multi-omic integration, big data analytics, and health monitoring/diagnostic applications are encouraged. In addition, experimental verification related to inflammation disease except for big data analysis for biomedical research is considered necessary.
This Research Topic welcomes the submissions of all types covering, but not limited to, the following areas:
• Using proteomics and metabonomics to explain inflammation-related research
• Advances in inflammation disease multi-omic integration
• Bioinformatics and experimental verification for inflammatory diseases
• Network pharmacology of new drugs in the treatment of inflammation disease
• Computational modeling, data integration, and large-scale recommenders for medicine
• Predictive analytics on biomedical/ health big data
• Machine learning and deep learning for biomedical/health big data in inflammation disease
• Biomedical and health big data management and analytics in inflammation disease
• Inflammation disease drugs molecular network modeling/visualization
• Laboratory validation of inflammation disease key pathogenic genes
• Intelligent pharmacogenomic analysis in inflammation disease
• Progress in inflammation disease pathological research
• Precision medicine in the treatment of inflammatory diseases
• Inflammation disease clinical big data analysis
