| http://purl.uniprot.org/citations/34109382 | http://www.w3.org/1999/02/22-rdf-syntax-ns#type | http://purl.uniprot.org/core/Journal_Citation |
| http://purl.uniprot.org/citations/34109382 | http://www.w3.org/2000/01/rdf-schema#comment | "Attention deficit hyperactivity disorder (ADHD) is a common neurodevelopmental disorder. Although genome-wide association studies (GWAS) identify the risk ADHD-associated variants and genes with significant P-values, they may neglect the combined effect of multiple variants with insignificant P-values. Here, we proposed a convolutional neural network (CNN) to classify 1033 individuals diagnosed with ADHD from 950 healthy controls according to their genomic data. The model takes the single nucleotide polymorphism (SNP) loci of P-values $\le{1\times 10^{-3}}$, i.e. 764 loci, as inputs, and achieved an accuracy of 0.9018, AUC of 0.9570, sensitivity of 0.8980 and specificity of 0.9055. By incorporating the saliency analysis for the deep learning network, a total of 96 candidate genes were found, of which 14 genes have been reported in previous ADHD-related studies. Furthermore, joint Gene Ontology enrichment and expression Quantitative Trait Loci analysis identified a potential risk gene for ADHD, EPHA5 with a variant of rs4860671. Overall, our CNN deep learning model exhibited a high accuracy for ADHD classification and demonstrated that the deep learning model could capture variants' combining effect with insignificant P-value, while GWAS fails. To our best knowledge, our model is the first deep learning method for the classification of ADHD with SNPs data."xsd:string |
| http://purl.uniprot.org/citations/34109382 | http://purl.org/dc/terms/identifier | "doi:10.1093/bib/bbab207"xsd:string |
| http://purl.uniprot.org/citations/34109382 | http://purl.uniprot.org/core/author | "Feng X."xsd:string |
| http://purl.uniprot.org/citations/34109382 | http://purl.uniprot.org/core/author | "Li H."xsd:string |
| http://purl.uniprot.org/citations/34109382 | http://purl.uniprot.org/core/author | "Liu L."xsd:string |
| http://purl.uniprot.org/citations/34109382 | http://purl.uniprot.org/core/author | "Qian Q."xsd:string |
| http://purl.uniprot.org/citations/34109382 | http://purl.uniprot.org/core/author | "Wang Y."xsd:string |
| http://purl.uniprot.org/citations/34109382 | http://purl.uniprot.org/core/author | "Cheng Li S."xsd:string |
| http://purl.uniprot.org/citations/34109382 | http://purl.uniprot.org/core/date | "2021"xsd:gYear |
| http://purl.uniprot.org/citations/34109382 | http://purl.uniprot.org/core/name | "Brief Bioinform"xsd:string |
| http://purl.uniprot.org/citations/34109382 | http://purl.uniprot.org/core/pages | "bbab207"xsd:string |
| http://purl.uniprot.org/citations/34109382 | http://purl.uniprot.org/core/title | "Deep learning model reveals potential risk genes for ADHD, especially Ephrin receptor gene EPHA5."xsd:string |
| http://purl.uniprot.org/citations/34109382 | http://purl.uniprot.org/core/volume | "22"xsd:string |
| http://purl.uniprot.org/citations/34109382 | http://www.w3.org/2004/02/skos/core#exactMatch | http://purl.uniprot.org/pubmed/34109382 |
| http://purl.uniprot.org/citations/34109382 | http://xmlns.com/foaf/0.1/primaryTopicOf | https://pubmed.ncbi.nlm.nih.gov/34109382 |
| http://purl.uniprot.org/uniprot/#_A0A384MU00-mappedCitation-34109382 | http://www.w3.org/1999/02/22-rdf-syntax-ns#object | http://purl.uniprot.org/citations/34109382 |
| http://purl.uniprot.org/uniprot/#_B7ZKJ3-mappedCitation-34109382 | http://www.w3.org/1999/02/22-rdf-syntax-ns#object | http://purl.uniprot.org/citations/34109382 |
| http://purl.uniprot.org/uniprot/#_B7ZKW7-mappedCitation-34109382 | http://www.w3.org/1999/02/22-rdf-syntax-ns#object | http://purl.uniprot.org/citations/34109382 |
| http://purl.uniprot.org/uniprot/#_F8VP57-mappedCitation-34109382 | http://www.w3.org/1999/02/22-rdf-syntax-ns#object | http://purl.uniprot.org/citations/34109382 |
| http://purl.uniprot.org/uniprot/#_F8W9W0-mappedCitation-34109382 | http://www.w3.org/1999/02/22-rdf-syntax-ns#object | http://purl.uniprot.org/citations/34109382 |
| http://purl.uniprot.org/uniprot/#_P54756-mappedCitation-34109382 | http://www.w3.org/1999/02/22-rdf-syntax-ns#object | http://purl.uniprot.org/citations/34109382 |
| http://purl.uniprot.org/uniprot/#_Q59FT4-mappedCitation-34109382 | http://www.w3.org/1999/02/22-rdf-syntax-ns#object | http://purl.uniprot.org/citations/34109382 |
| http://purl.uniprot.org/uniprot/A0A384MU00 | http://purl.uniprot.org/core/mappedCitation | http://purl.uniprot.org/citations/34109382 |
| http://purl.uniprot.org/uniprot/P54756 | http://purl.uniprot.org/core/mappedCitation | http://purl.uniprot.org/citations/34109382 |