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Bioinformatics applications should develop or use new computational or informatics methods, software and tools for managing, visualizing, analyzing, and interpreting complex biomedical data. Alternatively, they may use data science methods and tools to extract and discover new knowledge about biological systems. The scope of studies includes the development of computational, mathematical/statistical approaches for biomedical data integration, curation, analysis and interpretation. Topics also include studies of microbiomes and their interactions with the physical environment and host organisms.
Jean Yuan, Ph.D. Email: jean.yuan@nih.gov Biographical Sketch
Biostatistics areas of interest include development of advanced statistical techniques and methodologies for study design, data analysis and interpretation. The scope of studies includes nucleic acid sequencing, -omics, bioimaging, high-throughput technologies in data from molecular and cellular biology, pharmacology, to populational studies.
Multi-scale modeling applications should develop new computational algorithms and mathematical methods for integrative understanding of biomedical systems that may span temporal and spatial domains. The system scale ranges from macromolecules to cells, tissues, organs and organelles. Topics include macromolecular interactions, cellular processes and communication, tissue formation, and tissue/organ function.
Han Nguyen, Ph.D. Email: han.nguyen@nih.gov Biographical Sketch
The health informatics area focuses on the development of informatics and computational methods/tools for electronic health records and other biomedical data. Areas of interest include methodology development for data privacy and harmonization, data integration and analysis, and ontology development. Topics also include models of biomedical processes, population pharmacokinetics and pharmacodynamics, pharmacovigilance, drug discovery and repurposing.
