Education:
Ph.D., 2015, George Mason University, Manassas, VA
M.S., 2013, George Mason University, Manassas, VA
B.A., 2006, University of Colorado at Boulder, Boulder, CO
Biography
Daniel Veltri is a bioinformatics data scientist and the federal lead for BCBB’s Clinical and Laboratory Informatics Systems group and co-lead of the Data Science, Biostatistics, and Informatics Support Team. He specializes in applying machine learning to clinical, genomic, and proteomic data and has the authored popular tools AMP Scanner for predicting antimicrobial peptides and SimpleSynteny for visualizing synteny across multiple genomes.