Use of big data and machine learning algorithms to extract possible treatment targets in neurodevelopmental disorders

MA Malik, SV Faraone, T Michoel, J Haavik - Pharmacology & Therapeutics, 2023 - Elsevier
Neurodevelopmental disorders (NDDs) impact multiple aspects of an individual's
functioning, including social interactions, communication, and behaviors. The underlying …

[HTML][HTML] Bringing machine learning to research on intellectual and developmental disabilities: Taking inspiration from neurological diseases

C Gupta, P Chandrashekar, T Jin, C He… - Journal of …, 2022 - Springer
Abstract Intellectual and Developmental Disabilities (IDDs), such as Down syndrome,
Fragile X syndrome, Rett syndrome, and autism spectrum disorder, usually manifest at birth …

[HTML][HTML] Pathogenic mechanisms in neurodevelopmental disorders: advances in cellular models and multi-omics approaches

R Hollstein, A Peron, KS Wendt… - Frontiers in Cell and …, 2023 - frontiersin.org
Omics technologies have triggered a transformation in the field of clinical genetics and
molecular biology. The evaluation of the whole genome in terms of genomic variations …

[PDF][PDF] DeepND: Deep multitask learning of gene risk for comorbid neurodevelopmental disorders

I Beyreli, O Karakahya, AE Cicek - Patterns, 2022 - cell.com
Autism spectrum disorder and intellectual disability are comorbid neurodevelopmental
disorders with complex genetic architectures. Despite large-scale sequencing studies, only …

[HTML][HTML] Can Deep Learning Hit a Moving Target? A Scoping Review of Its Role to Study Neurological Disorders in Children

S Sargolzaei - Frontiers in Computational Neuroscience, 2021 - frontiersin.org
Neurological disorders dramatically impact patients of any age population, their families,
and societies. Pediatrics are among vulnerable age populations who differently experience …

Annual research review: discovery science strategies in studies of the pathophysiology of child and adolescent psychiatric disorders‐promises and limitations

Y Zhao, FX Castellanos - Journal of Child Psychology and …, 2016 - Wiley Online Library
Background Psychiatric science remains descriptive, with a categorical nosology intended to
enhance interobserver reliability. Increased awareness of the mismatch between categorical …

[HTML][HTML] Genomic insights and advanced machine learning: characterizing autism spectrum disorder biomarkers and genetic interactions

LD Nahas, A Datta, AM Alsamman, MH Adly… - Metabolic Brain …, 2024 - Springer
Abstract Autism Spectrum Disorder (ASD) is a complex neurodevelopmental condition
characterized by altered brain connectivity and function. In this study, we employed …

[HTML][HTML] Machine learning for neurodevelopmental disorders

C Moreau, C Deruelle, G Auzias - Machine Learning for Brain Disorders, 2023 - Springer
Neurodevelopmental disorders (NDDs) constitute a major health issue with> 10% of the
general worldwide population affected by at least one of these conditions—such as autism …

Harnessing deep learning into hidden mutations of neurological disorders for therapeutic challenges

S Yang, SH Kim, M Kang, JY Joo - Archives of Pharmacal Research, 2023 - Springer
The relevant study of transcriptome-wide variations and neurological disorders in the
evolved field of genomic data science is on the rise. Deep learning has been highlighted …

[HTML][HTML] Identifying genetics-based mechanisms and treatments for neurodevelopmental and psychiatric disorders through data integration

K Pang, L Wang, S Chang - Frontiers in Genetics, 2023 - frontiersin.org
Recent genome-wide association and exome/genome sequencing studies have
revolutionized our understanding of the genetic architecture of complex diseases including …