Behavioral barcoding in the cloud: embracing data-intensive digital phenotyping in neuropharmacology.
For decades, studying the behavioral effects of individual drugs and genetic mutations has been at the heart of efforts to understand and treat nervous system disorders. High-throughput technologies adapted from other disciplines (e.g., high-throughput chemical screening, genomics) are changing the scale of data acquisition in behavioral neuroscience. Massive behavioral datasets are beginning to emerge, particularly from zebrafish labs, where behavioral assays can be performed rapidly and reproducibly in 96-well, high-throughput format. Mining these datasets and making comparisons across different assays are major challenges for the field. Here, we review behavioral barcoding, a process by which complex behavioral assays are reduced to a string of numeric features, facilitating analysis and comparison within and across datasets.
Cardiovascular Research Center and Division of Cardiology, Department of Medicine, Massachusetts General Hospital, Harvard Medical School, 149 13th Street, Charlestown, MA 02129, USA.
David
D
Kokel
Andrew J
AJ
Rennekamp
Asmi H
AH
Shah
Urban
U
Liebel
Randall T
RT
Peterson
D000818:Animals; D001522:Behavior, Animal / Q000187:drug effects*; D019295:Computational Biology; D057225:Data Mining; D016208:Databases, Factual; D055808:Drug Discovery / Q000379:methods*; D009480:Neuropharmacology / Q000379:methods*; D015027:Zebrafish