Additional resources
Our goal is to initiate the cross-talk between clinicians, geneticists and basic scientists, thereby creating teams focused on understanding the phenotype/genotype relationships. Thus a broad range of resources is required to advance the scientific knowledge.
Here is a list of additional resources that could be explored or support your studies to make exciting breakthroughs that can directly impact patient care
PrediXcan
A gene-based association method that directly tests the molecular mechanisms through which genetic variation affects phenotype. PredixVU can detect known and new genes associated with disease traits and provide insights into the mechanism of these associations.
https://www.scandb.org/PXCAN/index.html
BioVU
BioVU is Vanderbilt’s collection, or “bank,” of de-identified DNA samples. Researchers are using these samples to study the links between genes and disease and between genes and how a patient might respond to a prescribed medication.
https://victr.vumc.org/what-is-biovu/
ClinVar
ClinVar provides a freely available archive of reports of relationships among medically important variants and phenotypes. ClinVar now accepts direct submissions with rich, structured details of phenotype, interpretation of functional and clinical significance, methodology used to capture variant calls and supporting evidence. ClinVar thus provides all users access to a broader set of clinical interpretations than they may have collected on their own and the promise of a comprehensive site for obtaining current and historical data. ClinVar is available to individual users and organizations that want to incorporate the data into local applications and workflows.
http://www.ncbi.nlm.nih.gov/clinvar/
Other online servers to predict mutant phenotypes
https://www.gtexportal.org/home/
https://www.ncbi.nlm.nih.gov/clinvar/
https://www.internationalgenome.org/home
https://gnomad.broadinstitute.org/
https://www.omim.org/statistics/geneMap
https://useast.ensembl.org/info/docs/tools/vep/index.html
PDB
Knowing the 3D structure of a biological macromolecule is essential for understanding its role in human health and disease. The Protein Data Bank (PDB) was established as the 1st open access digital data resource in all of biology and medicine. RCSB PDB helps to enable open access to the accumulating knowledge of 3D structure, function, and evolution of biological macromolecules, expanding the frontiers of fundamental biology, biomedicine, and biotechnology.
Grant funding possibilities
https://www.vanderbilt.edu/provost/internal-funding/trans-institutional-programs/
https://research.vanderbilt.edu/researchadministration/limitedsubmission/
https://vanderbilt.infoready4.com/#homePage