“Right now there is no simple way, short of spending years reading papers, to find genes that have been linked to nerve regeneration, which is the goal of spinal cord and nervous system research,” said the NIH grant’s principal investigator, Vance Lemmon, Ph.D., professor of neurological surgery, the Walter G. Ross Distinguished Chair in Developmental Neuroscience and member of The Miami Project to Cure Paralysis research faculty. “There are just too many studies for investigators to keep up with, so we need ways to allow them to search the literature much more efficiently and find information relevant to spinal cord injury. That’s what we propose to do.”
Awarded by the National Institute of Neurological Disorders and Stroke, the four-year grant solidifies UM’s growing reputation as the go-to institution for the development of chemoinformatics tools and ontologies that allow massive and diverse data sets to be integrated, queried, interpreted and analyzed across multiple disciplines. In addition to Lemmon, the grant’s co-principal investigators are John L. Bixby, Ph.D., professor of molecular and cellular pharmacology and neurological surgery and fellow Miami Project member, Stephan Schürer, Ph.D., research assistant professor of molecular and cellular pharmacology, and Ubbo Visser, Ph.D., associate professor of computer science.
Tentatively called RegenBase – for Regeneration Database – the proposed knowledge-based system will incorporate and build on the BioAssay Ontology that Schürer, Lemmon and their team of UM programmers and computer scientists developed with a federal stimulus grant to enable chemists and biologists on the hunt for new therapeutic agents to quickly search repositories of thousands of experiments on hundreds of thousands of small-molecule compounds.
Until the BioAssay Ontology was released into the public domain last year, the value of such chemical compound repositories to the drug discovery process was limited because researchers could not easily search, compare or query their huge data sets, nor integrate them with other data sources.
RegenBase is designed to remove the same roadblocks scientists encounter while searching the diverse data produced by neuroscientists and cell biologists studying nervous system injury, disease and cell motility, all with the hope of regenerating nerve function and promoting nerve protection. Currently, their efforts are slowed by the difficulty of collecting, analyzing, and displaying information from thousands of different experiments conducted on nervous system injury and interpreting them based on knowledge from other areas, such as genomics, cell biology, cancer, immunology and drug discovery.
To resolve that issue, the UM team plans to link RegenBase with the BioAssay Ontology, as well as other biomedical domain-level ontologies, which will allow scientists anywhere in the world to link data and results from studies on gene expression in nervous system injury and disease to data and knowledge from other domains that emphasize molecular targets and small molecules that perturb their function, ultimately speeding the development of novel therapeutics.
“One of the goals is to allow us to find compounds that are active on specific genes or proteins and then use those in new experiments on regeneration and protection,” Lemmon explained. “For example, in our experiments, we might find a class of genes whose expression changed dramatically after injury. By using RegenBase, we may find these same genes were implicated in neuroprotection, so we could search for compounds that inhibit the activity of the proteins that are coded for by these genes, and test to see if they prevent cells from dying, or improve regeneration. RegenBase will help us open that door.”
Underscoring UM’s growing prominence in chemoinformatics, the BioAssay Ontology project, which is ongoing, was recently leveraged into a new NIH-funded collaboration with scientists at Harvard, The Broad Institute, Columbia, Yale and the University of Arizona to incorporate more molecular and biochemical data from the Library of Integrated Network-based Cellular Signatures (LINCS) program.
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