2 articles published in JoVE
Targeted Next-generation Sequencing and Bioinformatics Pipeline to Evaluate Genetic Determinants of Constitutional Disease Allison A. Dilliott1,2, Sali M.K. Farhan3, Mahdi Ghani4, Christine Sato4, Eric Liang5, Ming Zhang4, Adam D. McIntyre1, Henian Cao1, Lemuel Racacho6,7, John F. Robinson1, Michael J. Strong1,8, Mario Masellis9,10, Dennis E. Bulman6,7, Ekaterina Rogaeva4, Anthony Lang10,11, Carmela Tartaglia4,10, Elizabeth Finger12,13, Lorne Zinman9, John Turnbull14, Morris Freedman10,15, Rick Swartz9, Sandra E. Black9,16, Robert A. Hegele1,2 1Robarts Research Institute, Schulich School of Medicine and Dentistry, Western University, 2Department of Biochemistry, Schulich School of Medicine and Dentistry, Western University, 3Analytic and Translational Genetics Unit, Center for Genomic Medicine, Harvard Medical School, Massachusetts General Hospital, Stanley Centre for Psychiatric Research, Broad Institute of MIT and Harvard, 4Tanz Centre for Research in Neurodegenerative Diseases, University of Toronto, 5 Targeted next-generation sequencing is a time- and cost-efficient approach that is becoming increasingly popular in both disease research and clinical diagnostics. The protocol described here presents the complex workflow required for sequencing and the bioinformatics process used to identify genetic variants that contribute to disease.
Applications of EEG Neuroimaging Data: Event-related Potentials, Spectral Power, and Multiscale Entropy Jennifer J. Heisz1, Anthony R. McIntosh1 1Rotman Research Institute, Baycrest Neuroimaging researchers typically consider the brain's response as the mean activity across repeated experimental trials and disregard signal variability over time as "noise". However, it is becoming clear that there is signal in that noise. This article describes the novel method of multiscale entropy for quantifying brain signal variability in the time domain.