ArticleSleep2023
Integration of genome-scale data identifies candidate sleep regulators.
Article in Sleep, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
10 citing papers in PubMed, 10 citations in OpenAlex.
- A patient-derived mouse model reproduces molecular, neurological, and sleep symptoms of SHINE syndrome.Human molecular genetics · 2026Article
- Objective prediction of siesta based on machine learning and association with obesity.Sleep health · 2026Article
- Sleep and activity patterns in autism.Autism : the international journal of research and practice · 2026Article
- Postnatal choline supplementation improves sleep in a rat model of developmental alcohol exposure.Alcohol, clinical & experimental research · 2025Article
- The NFκB Dif is required for behavioral and molecular correlates of sleep homeostasis in Drosophila.Sleep · 2024Article
- Elucidating sleep disorders: a comprehensive bioinformatics analysis of functional gene sets and hub genes.Frontiers in immunology · 2024Article
- Lifelong Chronic Sleep Disruption in a Mouse Model of Traumatic Brain Injury.Neurotrauma reports · 2024Article
- Using Bioinformatics and Machine Learning to Predict the Genetic Characteristics of Ferroptosis-Cuproptosis-Related Genes Associated with Sleep Deprivation.Nature and science of sleep · 2024Article
- Current Considerations in the Diagnosis and Treatment of Circadian Rhythm Sleep-Wake Disorders in Children.Seminars in pediatric neurology · 2023Article
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Authors and funding
11 authors at 3 institutions in 1 country.
Funding
Abstract
STUDY
objectivesGenetics impacts sleep, yet, the molecular mechanisms underlying sleep regulation remain elusive. In this study, we built machine learning models to predict sleep genes based on their similarity to genes that are known to regulate sleep.
methodsWe trained a prediction model on thousands of published datasets, representing circadian, immune, sleep deprivation, and many other processes, using a manually curated list of 109 sleep genes.
resultsOur predictions fit with prior knowledge of sleep regulation and identified key genes and pathways to pursue in follow-up studies. As an example, we focused on the NF-κB pathway and showed that chronic activation of NF-κB in a genetic mouse model impacted the sleep-wake patterns.
conclusionOur study highlights the power of machine learning in integrating prior knowledge and genome-wide data to study genetic regulation of complex behaviors such as sleep.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.