Behavioral Neuroscience in the Era of Genomics: Tools and Lessons for Analyzing High-Dimensional Datasets.
behavioral analysis
large datasets
variance
Journal
International journal of molecular sciences
ISSN: 1422-0067
Titre abrégé: Int J Mol Sci
Pays: Switzerland
ID NLM: 101092791
Informations de publication
Date de publication:
30 Mar 2022
30 Mar 2022
Historique:
received:
10
02
2022
revised:
26
03
2022
accepted:
29
03
2022
entrez:
12
4
2022
pubmed:
13
4
2022
medline:
14
4
2022
Statut:
epublish
Résumé
Behavioral neuroscience underwent a technology-driven revolution with the emergence of machine-vision and machine-learning technologies. These technological advances facilitated the generation of high-resolution, high-throughput capture and analysis of complex behaviors. Therefore, behavioral neuroscience is becoming a data-rich field. While behavioral researchers use advanced computational tools to analyze the resulting datasets, the search for robust and standardized analysis tools is still ongoing. At the same time, the field of genomics exploded with a plethora of technologies which enabled the generation of massive datasets. This growth of genomics data drove the emergence of powerful computational approaches to analyze these data. Here, we discuss the composition of a large behavioral dataset, and the differences and similarities between behavioral and genomics data. We then give examples of genomics-related tools that might be of use for behavioral analysis and discuss concepts that might emerge when considering the two fields together.
Identifiants
pubmed: 35409169
pii: ijms23073811
doi: 10.3390/ijms23073811
pmc: PMC8998543
pii:
doi:
Types de publication
Journal Article
Review
Langues
eng
Sous-ensembles de citation
IM
Subventions
Organisme : Israel Science Foundation
ID : 174/19 & 384/14 and 2958/21 & 3363/21
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