ArticleCommunicative & integrative biology2013
Modeling the genetic basis for human sleep disorders in Drosophila.
Article in Communicative & integrative biology, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Effects of Gallic Acid on Sleep and Circadian Rhythm in aThe Yale journal of biology and medicine · 2026Article
- TfAP-2 is required for night sleep in Drosophila.BMC neuroscience · 2016Article
- Drosophila sodium channel mutations: Contributions to seizure-susceptibility.Experimental neurology · 2015Review
- Evidence that natural selection maintains genetic variation for sleep in Drosophila melanogaster.BMC evolutionary biology · 2015Article
- Unraveling the complexities of circadian and sleep interactions with memory formation through invertebrate research.Frontiers in systems neuroscience · 2014Review
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Sleep research in Drosophila is not only here to stay, but is making impressive strides towards helping us understand the biological basis for and the purpose of sleep-perhaps one of the most complex and enigmatic of behaviors. Thanks to over a decade of sleep-related studies in flies, more molecular methods are being applied than ever before towards understanding the genetic basis of sleep disorders. The advent of high-throughput technologies that can rapidly interrogate whole genomes, epigenomes and proteomes, has also revolutionized our ability to detect genetic variants that might be causal for a number of sleep disorders. In the coming years, mutational studies in model organisms such as Drosophila will need to be functionally connected to information being generated from these whole-genome approaches in humans. This will necessitate the development of appropriate methods for interpolating data and increased analytical power to synthesize useful network(s) of sleep regulatory pathways-including appropriate discriminatory and predictive capabilities. Ultimately, such networks will also need to be interpreted in the context of fundamental neurobiological substrates for sleep in any given species. In this review, we highlight some emerging approaches, such as network analysis and mathematical modeling of sleep distributions, which can be applied to contemporary sleep research as a first step to achieving these aims. These methodologies should favorably impact not only a mechanistic understanding of sleep, but also future pharmacological intervention strategies to manage and treat sleep disorders in humans.
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Registered trials
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