ArticleTranslational psychiatry2018
Brain-specific functional relationship networks inform autism spectrum disorder gene prediction.
Article in Translational psychiatry, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.
What it found
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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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Who cites it
29 citing papers in PubMed, 67 citations in OpenAlex.
- Age of machine learning: new trends in autism spectrum disorder prediction.Frontiers in microbiology · 2025Review
- LIMO-GCN: a linear model-integrated graph convolutional network for predicting Alzheimer disease genes.Briefings in bioinformatics · 2024Article
- Imperfect gold standard gene sets yield inaccurate evaluation of causal gene identification methods.Communications biology · 2024Review
- Distinct Alterations in Dendritic Spine Morphology in the Absence of β-Neurexins.International journal of molecular sciences · 2024Article
- Review: Cancer and neurodevelopmental disorders: multi-scale reasoning and computational guide.Frontiers in cell and developmental biology · 2024Review
- A network-based method for associating genes with autism spectrum disorder.Frontiers in bioinformatics · 2024Article
- Microbiome-Gut-Mucosal-Immune-Brain Axis and Autism Spectrum Disorder (ASD): A Novel Proposal of the Role of the Gut Microbiome in ASD Aetiology.Behavioral sciences (Basel, Switzerland) · 2023Review
- Role of Artificial Intelligence for Autism Diagnosis Using DTI and fMRI: A Survey.Biomedicines · 2023Article
- Prioritizing de novo autism risk variants with calibrated gene- and variant-scoring models.Human genetics · 2022Article
- DeepND: Deep multitask learning of gene risk for comorbid neurodevelopmental disorders.Patterns (New York, N.Y.) · 2022Article
- Excess ribosomal protein production unbalances translation in a model of Fragile X Syndrome.Nature communications · 2022Article
- A Bayesian framework to integrate multi-level genome-scale data for Autism risk gene prioritization.BMC bioinformatics · 2022Article
- An integrated brain-specific network identifies genes associated with neuropathologic and clinical traits of Alzheimer's disease.Briefings in bioinformatics · 2022Article
- Comprehensive Survey of Recent Drug Discovery Using Deep Learning.International journal of molecular sciences · 2021Review
- Cortical overgrowth in a preclinical forebrain organoid model of CNTNAP2-associated autism spectrum disorder.Nature communications · 2021Article
- "Guilt by association" is not competitive with genetic association for identifying autism risk genes.Scientific reports · 2021Article
- Circulating Non-Coding RNAs as a Signature of Autism Spectrum Disorder Symptomatology.International journal of molecular sciences · 2021Article
- Clustering Analysis Supports the Detection of Biological Processes Related to Autism Spectrum Disorder.Genes · 2020Article
- A Review of Machine Learning Methods of Feature Selection and Classification for Autism Spectrum Disorder.Brain sciences · 2020Review
- Identification of amygdala-expressed genes associated with autism spectrum disorder.Molecular autism · 2020Article
Corrections and comments
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Authors and funding
6 authors at 3 institutions in 2 countries.
Funding
Abstract
Autism spectrum disorder (ASD) is a neuropsychiatric disorder with strong evidence of genetic contribution, and increased research efforts have resulted in an ever-growing list of ASD candidate genes. However, only a fraction of the hundreds of nominated ASD-related genes have identified de novo or transmitted loss of function (LOF) mutations that can be directly attributed to the disorder. For this reason, a means of prioritizing candidate genes for ASD would help filter out false-positive results and allow researchers to focus on genes that are more likely to be causative. Here we constructed a machine learning model by leveraging a brain-specific functional relationship network (FRN) of genes to produce a genome-wide ranking of ASD risk genes. We rigorously validated our gene ranking using results from two independent sequencing experiments, together representing over 5000 simplex and multiplex ASD families. Finally, through functional enrichment analysis on our highly prioritized candidate gene network, we identified a small number of pathways that are key in early neural development, providing further support for their potential role in ASD.
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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.