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Trends Biotechnol DOI:10.1016/j.tibtech.2012.05.001

Behavioral barcoding in the cloud: embracing data-intensive digital phenotyping in neuropharmacology.

Publication TypeJournal Article
Year of Publication2012
AuthorsKokel, D, Rennekamp, AJ, Shah, AH, Liebel, U, Peterson, RT
JournalTrends Biotechnol
Volume30
Issue8
Pages421-5
Date Published2012 Aug
ISSN1879-3096
KeywordsAnimals, Behavior, Animal, Computational Biology, Data Mining, Databases, Factual, Drug Discovery, Neuropharmacology, Zebrafish
Abstract

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.

URLhttp://linkinghub.elsevier.com/retrieve/pii/S0167-7799(12)00060-1
DOI10.1016/j.tibtech.2012.05.001
Pubmed

http://www.ncbi.nlm.nih.gov/pubmed/22652049?dopt=Abstract

Alternate JournalTrends Biotechnol.
PubMed ID22652049
PubMed Central IDPMC3401323
Grant ListR21 MH085205 / MH / NIMH NIH HHS / United States
K01MH091449 / MH / NIMH NIH HHS / United States
MH085205 / MH / NIMH NIH HHS / United States
K01 MH091449 / MH / NIMH NIH HHS / United States
T32 HL007208 / HL / NHLBI NIH HHS / United States
T32HL07208 / HL / NHLBI NIH HHS / United States
R01 MH086867 / MH / NIMH NIH HHS / United States
MH086867 / MH / NIMH NIH HHS / United States