The FaceBase Consortium: a comprehensive resource for craniofacial researchers.
James F BrinkleyShannon FisherMatthew P HarrisGreg HolmesJoan E HooperEthylin Wang JabsKenneth L JonesCarl KesselmanOphir D KleinRichard L MaasMary L MarazitaLicia SelleriRichard A SpritzHarm van BakelAxel ViselTrevor J WilliamsJoanna Wysockanull nullYang ChaiPublished in: Development (Cambridge, England) (2016)
The FaceBase Consortium, funded by the National Institute of Dental and Craniofacial Research, National Institutes of Health, is designed to accelerate understanding of craniofacial developmental biology by generating comprehensive data resources to empower the research community, exploring high-throughput technology, fostering new scientific collaborations among researchers and human/computer interactions, facilitating hypothesis-driven research and translating science into improved health care to benefit patients. The resources generated by the FaceBase projects include a number of dynamic imaging modalities, genome-wide association studies, software tools for analyzing human facial abnormalities, detailed phenotyping, anatomical and molecular atlases, global and specific gene expression patterns, and transcriptional profiling over the course of embryonic and postnatal development in animal models and humans. The integrated data visualization tools, faceted search infrastructure, and curation provided by the FaceBase Hub offer flexible and intuitive ways to interact with these multidisciplinary data. In parallel, the datasets also offer unique opportunities for new collaborations and training for researchers coming into the field of craniofacial studies. Here, we highlight the focus of each spoke project and the integration of datasets contributed by the spokes to facilitate craniofacial research.
Keyphrases
- quality improvement
- healthcare
- gene expression
- high throughput
- endothelial cells
- electronic health record
- public health
- big data
- end stage renal disease
- genome wide association
- mental health
- ejection fraction
- single cell
- high resolution
- chronic kidney disease
- newly diagnosed
- dna methylation
- data analysis
- induced pluripotent stem cells
- preterm infants
- case control
- prognostic factors
- rna seq
- transcription factor
- deep learning
- health information
- risk assessment
- artificial intelligence
- patient reported outcomes
- patient reported
- mass spectrometry
- climate change
- soft tissue
- heat shock
- affordable care act