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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Page: 1 2 Hits 1 – 20 of 32 1 Next-gen sequencing identifies non-coding variation disrupting miRNA-binding sites in neurological disorders Devanna, P; Chen, X S; Ho, J; Gajewski, D; Smith, S D; Gialluisi, A; Francks, C; Fisher, S E; Newbury, D F; Vernes, S C. - 2021 Abstract: Funding: This work was funded by a Marie Curie Career Integration Grant and by a Max Planck Research Group Grant both awarded to SCV. The work of the Newbury lab is funded by the Medical Research Council (G1000569/1 and MR/J003719/1). XSC, AG, CF and SEF were supported by the Max Planck Society. The UK Medical Research Council and the Wellcome Trust (Grant ref: 102215/2/13/2) and the University of Bristol provided core support for ALSPAC. The work of the Wellcome Trust Centre in Oxford is supported by the Wellcome Trust (090532/Z/09/Z). JH was supported by a scholarship from the Agency for Science, Technology, and Research, Singapore. The work of SDS is supported by the grant HD027802 from NIH. ; Understanding the genetic factors underlying neurodevelopmental and neuropsychiatric disorders is a major challenge given their prevalence and potential severity for quality of life. While large-scale genomic screens have made major advances in this area, for many disorders the genetic underpinnings are complex and poorly understood. To date the field has focused predominantly on protein coding variation, but given the importance of tightly controlled gene expression for normal brain development and disorder, variation that affects non-coding regulatory regions of the genome is likely to play an important role in these phenotypes. Herein we show the importance of 3 prime untranslated region (3'UTR) non-coding regulatory variants across neurodevelopmental and neuropsychiatric disorders. We devised a pipeline for identifying and functionally validating putatively pathogenic variants from next generation sequencing (NGS) data. We applied this pipeline to a cohort of children with severe specific language impairment (SLI) and identified a functional, SLI-associated variant affecting gene regulation in cells and post-mortem human brain. This variant and the affected gene (ARHGEF39) represent new putative risk factors for SLI. Furthermore, we identified 3'UTR regulatory variants across autism, schizophrenia and bipolar disorder NGS cohorts demonstrating their impact on neurodevelopmental and neuropsychiatric disorders. Our findings show the importance of investigating non-coding regulatory variants when determining risk factors contributing to neurodevelopmental and neuropsychiatric disorders. In the future, integration of such regulatory variation with protein coding changes will be essential for uncovering the genetic causes of complex neurological disorders and the fundamental mechanisms underlying health and disease. ; Publisher PDF ; Peer reviewed Keyword: 3' Untranslated Regions/genetics; Adult; Autistic disorder/genetics; Binding sites/genetics; Bipolar disorder/genetics; Child; Cohort studies; DAS; DNA; Female; Gene expression regulation/genetics; Genetic predisposition to Disease; Genetic variation/genetics; Genomics; High-throughput nucleotide sequencing/methods; Humans; intergenic/genetics; Language development disorders/genetics; Male; Mental disorders/genetics; microRNAs/genetics; Nervous system diseases/genetics; Neurodevelopmental disorders/genetics; QH301; QH301 Biology; QH426; QH426 Genetics; RC0321; RC0321 Neuroscience. Biological psychiatry. Neuropsychiatry; Schizophrenia/genetics; Sequence analysis/methods URL: https://doi.org/10.1038/mp.2017.30 http://hdl.handle.net/10023/21699 BASE Hide details 2 Natural SQL: Making SQL Easier to Infer from Natural Language Specifications Gan, Y; Chen, X; Xie, J. - 2021 BASE Show details 3 Towards Robustness of Text-to-SQL Models against Synonym Substitution Gan, Y; Chen, X; Huang, Q. - 2021 BASE Show details 4 Correcting Knowledge Base Assertions Chen, J.; Chen, X.; Horrocks, I.. - : Association for Computing Machinery, 2020 BASE Show details 5 Study of central exclusive [Image: see text] production in proton-proton collisions at [Formula: see text] and 13TeV Sirunyan, A. M.; Tumasyan, A.; Adam, W.... In: Eur Phys J C Part Fields (2020) BASE Show details 6 The relationship between English proficiency and humour appreciation among English L1 users and Chinese L2 users of English Chen, X.; Dewaele, Jean-Marc. - : De Gruyter, 2019 BASE Show details 7 The flowering of positive psychology in Foreign Language Teaching and Acquisition research Dewaele, Jean-Marc; Chen, X.; Padilla, A.. - : Frontiers Media, 2019 BASE Show details 8 Exploiting future word contexts in neural network language models for speech recognition Chen, X.; Liu, X.; Wang, Y.. - : Institute of Electrical and Electronics Engineers (IEEE), 2019 BASE Show details 9 Survival percentages of atraumatic restorative treatment (ART) restorations and sealants in posterior teeth: an updated systematic review and meta-analysis [<Journal>] Amorim, R. G. de [Verfasser]; Frencken, J. E. [Verfasser]; Raggio, D. P. [Verfasser]. DNB Subject Category Language Show details 10 Disparities in Diabetes Care Quality by English Language Preference in Community Health Centers Leung, LB; Vargas-Bustamante, A; Martinez, AE... In: Leung, LB; Vargas-Bustamante, A; Martinez, AE; Chen, X; & Rodriguez, HP. (2018). Disparities in Diabetes Care Quality by English Language Preference in Community Health Centers. Health Services Research, 53(1), 509 - 531. doi:10.1111/1475-6773.12590. UCLA: Retrieved from: http://www.escholarship.org/uc/item/40x4d7fn (2018) BASE Show details 11 Phonetic and graphemic systems for multi-genre broadcast transcription Wang, Y.; Chen, X.; Gales, M.J.F.. - : IEEE, 2018 BASE Show details 12 Active memory networks for language modeling Chen, O.; Ragni, A.; Gales, M.. - : International Speech Communication Association (ISCA), 2018 BASE Show details 13 Future word contexts in neural network language models Chen, X.; Liu, X.; Ragni, A.. - : IEEE, 2018 BASE Show details 14 Phonetic and graphemic systems for multi-genre broadcast transcription ... Wang, Yu; Chen, X; Gales, Mark. - : Apollo - University of Cambridge Repository, 2018 BASE Show details 15 Phonetic and graphemic systems for multi-genre broadcast transcription Wang, Yu; Chen, X; Gales, Mark. - : IEEE, 2018. : https://ieeexplore.ieee.org/document/8462353, 2018. : ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings, 2018 BASE Show details 16 Future word contexts in neural network language models Chen, X.; Liu, X.; Ragni, A.. - : IEEE, 2017 BASE Show details 17 Investigating bidirectional recurrent neural network language models for speech recognition Chen, X.; Ragni, A.; Liu, X.. - : International Speech Communication Association (ISCA), 2017 BASE Show details 18 Search for dark matter produced in association with heavy-flavor quark pairs in proton-proton collisions at [Formula: see text] Sirunyan, A. M.; Tumasyan, A.; Adam, W.. - : Springer Berlin Heidelberg, 2017 BASE Show details 19 Developing Universal Dependencies for Mandarin Chinese Leung, H.; Poiret, R.; Wong, T.... In: The 12th Workshop on Asian Language Resources ; https://halshs.archives-ouvertes.fr/halshs-01509329 ; The 12th Workshop on Asian Language Resources, 2016, Osaka, Japan (2016) BASE Show details 20 Multi-language neural network language models Ragni, A.; Dakin, E.; Chen, X.. - : International Speech Communication Association (ISCA), 2016 BASE Show details Page: 1 2

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