Translational bioinformatics (TBI) is a multi-disciplinary and rapidly emerging field of biomedical data sciences and informatics technologies that efficiently translate basic molecular, genetic, cellular, and clinical data into clinical products or health implications. TBI is a relatively young discipline that spans a wide spectrum from big data to diagnostics and therapeutics. TBI involves applying novel methods to the storage, analysis, and interpretation of a massive volume of ‘omics data, and it bridges the gap between bench research and real-world application to human health. Many health-related topics are increasingly falling within the scope of TBI, including rare and complex human disease, cancer, biomarkers, pharmacogenomics, drug repositioning, and clinical decision support systems. Precision medicine attempts to determine individual solutions based on the genomic, environmental, and clinical profiles of each individual, providing an opportunity to incorporate individual genomic data into patient care. While a plethora of genomic signatures have successfully demonstrated their predictive power, they are merely statistically-significant differences between dichotomized phenotypes that are in fact severely heterogeneous. Despite many translational barriers, connecting the molecular world to the clinical world and vice versa will undoubtedly benefit human health in the near future. This Research Topic aims to present original research, commentaries, perspectives, and reviews on the current trends in translational bioinformatics. Example topics include (but are not limited to)
• Precision Medicine
• Next-generation sequencing for Personal Genomics, Cancer Genomics and Metagenomics
• Rare and Common Variants of Human Genome
• Phenome-wide association study (PheWAS)
• Epigenomics, non-coding RNAs, and DNA methylation analysis
• Genome-Phenome-Envirome Associations
• Biomarkers, Drug Discovery and Pharmacogenomics
• Biomedical Text/Data Mining and Visualization
• Network Biology/Medicine and Pathway/Regulation Analysis
• Biomedical Intelligence, Clinical Informatics, and Health Record
• Semantic Biology/Medicine and Biomedical Ontologies
Translational bioinformatics (TBI) is a multi-disciplinary and rapidly emerging field of biomedical data sciences and informatics technologies that efficiently translate basic molecular, genetic, cellular, and clinical data into clinical products or health implications. TBI is a relatively young discipline that spans a wide spectrum from big data to diagnostics and therapeutics. TBI involves applying novel methods to the storage, analysis, and interpretation of a massive volume of ‘omics data, and it bridges the gap between bench research and real-world application to human health. Many health-related topics are increasingly falling within the scope of TBI, including rare and complex human disease, cancer, biomarkers, pharmacogenomics, drug repositioning, and clinical decision support systems. Precision medicine attempts to determine individual solutions based on the genomic, environmental, and clinical profiles of each individual, providing an opportunity to incorporate individual genomic data into patient care. While a plethora of genomic signatures have successfully demonstrated their predictive power, they are merely statistically-significant differences between dichotomized phenotypes that are in fact severely heterogeneous. Despite many translational barriers, connecting the molecular world to the clinical world and vice versa will undoubtedly benefit human health in the near future. This Research Topic aims to present original research, commentaries, perspectives, and reviews on the current trends in translational bioinformatics. Example topics include (but are not limited to)
• Precision Medicine
• Next-generation sequencing for Personal Genomics, Cancer Genomics and Metagenomics
• Rare and Common Variants of Human Genome
• Phenome-wide association study (PheWAS)
• Epigenomics, non-coding RNAs, and DNA methylation analysis
• Genome-Phenome-Envirome Associations
• Biomarkers, Drug Discovery and Pharmacogenomics
• Biomedical Text/Data Mining and Visualization
• Network Biology/Medicine and Pathway/Regulation Analysis
• Biomedical Intelligence, Clinical Informatics, and Health Record
• Semantic Biology/Medicine and Biomedical Ontologies
