Summary
The identification of genomic alterations such as single nucleotide polymorphisms (SNP), insertions/deletions, and other structural changes is the first step to understanding their possible roles in disease development followed by large studies to assess their actual significance and predictive power as disease biomarkers. Careful execution and understanding of each step in the DNA analysis workflow is required to produce high quality, reliable downstream analysis data you can count on. In general, DNA analysis begins with the purification of high quality genomic DNA, followed by total DNA quantitation and depending on the goals of the experiment, one or more downstream assays to either identify new mutations or determine if one or more known mutations is present in a sample.
This webinar will review each step of the DNA analysis workflow, highlight the key challenges faced and provide solutions to help overcome those challenges.
Speaker
Eric Vincent, PhD
Genomics Product Manager
Promega Corporation
Eric earned his Ph.D. in Biochemistry at The University of Iowa where he studied TGF-Beta mediated signaling involved with epithelial to mesenchymal cell transformation during the development of cardiac valves using techniques like molecular biology, RNA expression analysis and confocal microscopy. Prior to joining Promega he performed post-doctoral research at the Cincinnati Children’s Hospital in the Molecular Cardiovascular Biology Department where he studied pattern formation and the role of signaling cascades in early cardiac development using techniques such assite-directed mutagenesis, transfection and creation of transgenic mouse models. Eric worked for six and one-half years in the Promega Technical Services department helping scientists design, troubleshoot and optimize assays. Eric then transitioned to product management working closely with R & D and customers to create new tools to aid researchers’ genomic studies.