A systems biology approach to the digital behaviorome. Issue 20 (April 2020)

• Record Type: Journal Article
• Authors: Rashidisabet, Homa; Thomas, Paul J.; Ajilore, Olusola; Zulueta, John; Moore, Raeanne C.; Leow, Alex
• Is Part Of: Current opinion in systems biology. Issue 20(2020)
• Page Start: 8
• Page End: 16
• Publication Date: 2020-04
• Subjects: Digital behaviorome -- Digital phenotyping -- Passive sensor data -- Connected technology -- Neuropsychiatric disorders -- Systems biology -- Keystroke dynamics -- Big data analytics; Systems biology -- Periodicals; 570
• DOI: 10.1016/j.coisb.2020.07.003
• Languages: English
• ISSNs: 2452-3100

Abstract

Abstract: This review article summarizes how emerging connected technologies (e.g., smartphones and wearables) may provide novel avenues to understand an individual's behavior through the lens of systems biology. First, we surveyed recent research efforts that leveraged the multimodal high temporal resolution data derived from connected devices to build digital phenotypes and/or discover digital biomarkers of the behaviorome. We write this review with a particular emphasis on the detection, diagnosis, and symptom monitoring of neuropsychiatric disorders, as these pathologies may manifest primarily as disruptions to the behaviorome. We then discussed new opportunities and challenges these state-of-art research efforts bring as they intersect with other areas of natural and social sciences. Ultimately, we suggest how incorporating systems biology and connected technologies data can lead to a better understanding of complex neuropsychiatric disorders. Highlights: Digital behaviorome is a subset of a person's behavior measurable by connected devices via a systems biology approach. A review on the feasibility and validity of building the digital behaviorome via sensor data for neuropsychiatric research. Because of high-temporal resolution sensors equipped in modern connected devices, digital behaviorome holds tremendous potential.